Marijuana and the Cannabinoids

Marijuana and the Cannabinoids
Edited by
Mahmoud A. ElSohly, PhD
Marijuana and the Cannabinoids
F O R E N S I C
S C I E N C E AND MEDICINE
Steven B. Karch, MD, SERIES EDITOR
HERBAL PRODUCTS: TOXICOLOGY AND CLINICAL PHARMACOLOGY, SECOND EDITION,
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CRIMINAL POISONING: INVESTIGATIONAL GUIDE FOR LAW ENFORCEMENT, TOXICOLOGISTS, FORENSIC
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MARIJUANA AND THE CANNABINOIDS, edited by Mahmoud A. ElSohly, 2006
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FORENSIC SCIENTISTS, AND ATTORNEYS, by John H. Trestrail, III, 2000
MARIJUANA AND
THE CANNABINOIDS
Edited by
Mahmoud A. ElSohly, PhD
The School of Pharmacy, The University of Mississippi;
ElSohly Laboratories Inc., Oxford, MS
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Marijuana and the cannabinoids / edited by Mahmoud A. ElSohly.
p. ; cm. -- (Forensic science and medicine)
Includes bibliographical references and index.
ISBN 1-58829-456-0 (alk. paper)
1. Cannabinoids. I. ElSohly, Mahmoud A. II. Series.
[DNLM: 1. Cannabinoids. 2. Cannabis. QV 77.7 M33515 2006]
QP801.C27M355 2006
615'.7827--dc22
2006012285
Preface
v
Although primarily used today as one of the most prevalent illicit leisure drugs,
the use of Cannabis sativa L., commonly referred to as marijuana, for medicinal
purposes has been reported for more than 5000 years. Marijuana use has been shown
to create numerous health problems, and, consequently, the expanding use beyond
medical purposes into recreational use (abuse) resulted in control of the drug through
international treaties.
Much research has been carried out over the past few decades following the
identification of the chemical structure of THC in 1964. The purpose of Marijuana
and the Cannabinoids is to present in a single volume the comprehensive knowledge
and experience of renowned researchers and scientists. Each chapter is written
independently by an expert in his/her field of endeavor, ranging from the botany, the
constituents, the chemistry and pharmacokinetics, the effects and consequences of
illicit use on the human body, to the therapeutic potential of the cannabinoids.
Mahmoud A. ElSohly, PhD

Contents
vii
Preface ................................................................................................................ v
Contributors ...................................................................................................... ix
CHAPTER 1
Cannabis and Natural Cannabis Medicines
Robert C. Clarke and David P. Watson ................................................................ 1
CHAPTER 2
Chemistry and Analysis of Phytocannabinoids
and Other Cannabis Constituents
Rudolf Brenneisen................................................................................................ 17
CHAPTER 3
Chemical Fingerprinting of Cannabis as a Means of Source Identification
Mahmoud A. ElSohly, Donald F. Stanford,
and Timothy P. Murphy .............................................................................. 51
CHAPTER 4
Marijuana Smoke Condensate: Chemistry and Pharmacology
Hala N. ElSohly and Mahmoud A. ElSohly ...................................................... 67
CHAPTER 5
Pharmacology of Cannabinoids
Lionel P. Raymon and H. Chip Walls ................................................................ 97
CHAPTER 6
The Endocannabinoid System and the Therapeutic Potential
of Cannabinoids
Billy R. Martin .................................................................................................... 125
CHAPTER 7
Immunoassays for the Detection of Cannabis Abuse:
Technologies, Development Strategies, and Multilevel Applications
Jane S-C. Tsai ..................................................................................................... 145
CHAPTER 8
Mass Spectrometric Methods for Determination
of Cannabinoids in Physiological Specimens
Rodger L. Foltz ................................................................................................... 179
CHAPTER 9
Human Cannabinoid Pharmacokinetics and Interpretation
of Cannabinoid Concentrations in Biological Fluids and Tissues
Marilyn A. Huestis and Michael L. Smith ....................................................... 205
CHAPTER 10
Medical and Health Consequences of Marijuana
Jag H. Khalsa ..................................................................................................... 237
CHAPTER 11
Effects of Marijuana on the Lung and Immune Defenses
Donald P. Tashkin and Michael D. Roth ......................................................... 253
CHAPTER 12
Marijuana and Driving Impairment
Barry K. Logan ................................................................................................... 277
CHAPTER 13
Postmortem Considerations
Steven B. Karch .................................................................................................. 295
CHAPTER 14
Cannabinoid Effects on Biopsychological, Neuropsychiatric,
and Neurological Processes
Richard E. Musty ................................................................................................ 303
Index ........................................................................................................................... 317
viii Contents
Contributors
ix
RUDOLF BRENNEISEN, PhD • Department of Clinical Research, Laboratory
for Phytopharmacology, Bioanalytics and Pharmacokinetics, University of Bern,
Bern, Switzerland
ROBERT C. CLARKE, BA • International Hemp Association, Amsterdam, The Netherlands
HALA N. ELSOHLY, PhD • National Center for Natural Products Research, Research
Institute of Pharmaceutical Sciences, The School of Pharmacy, The University
of Mississippi, Oxford, MS
MAHMOUD A. ELSOHLY, PhD • National Center for Natural Products Research, Research
Institute of Pharmaceutical Sciences, The School of Pharmacy, The University
of Mississippi; ElSohly Laboratories Inc., Oxford, MS
RODGER L. FOLTZ, PhD • Center for Human Toxicology, University of Utah, Salt Lake
City, UT
MARILYN A. HUESTIS, PhD • Chemistry and Drug Metabolism, Intramural Research
Program, National Institute on Drug Abuse, National Institutes of Health,
Baltimore, MD
STEVEN B. KARCH, MD • Consultant Pathologist/Toxicologist, Berkeley, CA
JAG H. KHALSA, PhD • Chief, Medical Consequences Branch, Division
of Pharmacotherapies and Medical Consequences of Drug Abuse (DPMCDA),
National Institute on Drug Abuse, Bethesda, MD
BARRY K. LOGAN, PhD • Washington State Toxicologist and Director of Forensic
Laboratory Services Bureau, Washington State Patrol, Seattle, WA
BILLY R. MARTIN, PhD • Louis and Ruth Harris Professor and Chair, Department
of Pharmacology and Toxicology, Virginia Commonwealth University,
Richmond, VA
TIMOTHY P. MURPHY, BA • ElSohly Laboratories Inc., Oxford, MS
RICHARD E. MUSTY, PhD • Department of Psychology, University of Vermont,
Burlington, VT
LIONEL P. RAYMON, PharmD, PhD • Kaplan Medical, Pharmacology Chair and Department
of Pathology, Miller School of Medicine, University of Miami, Miami, FL
MICHAEL D. ROTH, MD • Professor of Medicine, Division of Pulmonary and Critical
Care, Department of Medicine, David Geffen School of Medicine, University
of California at Los Angeles, Los Angeles, CA
x Contributors
MICHAEL L. SMITH, PhD, DABFT • Division of Forensic Toxicology, Office of the Armed
Forces Medical Examiner, Rockville, MD
DONALD F. STANFORD, MS • National Center for Natural Products Research, Research
Institute of Pharmaceutical Sciences, School of Pharmacy, The University
of Mississippi, Oxford, MS
DONALD P. TASHKIN, MD • Professor of Medicine, Division of Pulmonary and Critical
Care, Department of Medicine, David Geffen School of Medicine, University
of California at Los Angeles, Los Angeles, CA
JANE S-C. TSAI, PhD • Director, Research and Development, Roche Diagnostics,
Indianapolis, IN
H. CHIP WALLS, BS • Technical Director, Forensic Toxicology Laboratory, Miller School
of Medicine, University of Miami, School of Medicine, Homestead, FL
DAVID P. WATSON • CEO, HortaPharm BV, Amsterdam, The Netherlands
Cannabis and Natural Cannabis Medicines 1
From: Forensic Science and Medicine: Marijuana and the Cannabinoids
Edited by: M. A. ElSohly © Humana Press Inc., Totowa, New Jersey
1
Chapter 1
Cannabis and Natural Cannabis
Medicines
Robert C. Clarke and David P. Watson
1. INTRODUCTION
Cannabis plants produce many compounds of possible medical importance. This
chapter briefly explains the life cycle, origin, early evolution, and domestication of
Cannabis, plus provides a brief history of drug Cannabis breeding and looks into the
future of Cannabis as a source of medicines. Cannabis is among the very oldest of
economic plants providing humans with fiber for spinning, weaving cloth, and making
paper; seed for human foods and animal feeds; and aromatic resin containing compounds
of recreational and medicinal value. Human selection for varying uses and
natural selection pressures imposed by diverse introduced climates have resulted in a
wide variety of growth forms and chemical compositions. Innovative classical breeding
techniques have been used to improve recreational drug forms of Cannabis, resulting
in many cannabinoid-rich cultivars suitable for medical use. The biosynthesis of
cannabinoid compounds is unique to Cannabis, and cultivars with specific chemical
profiles are being developed for diverse industrial and pharmaceutical uses.
2. LIFE CYCLE AND ECOLOGY
Cannabis is an annual crop plant propagated from seed and grows vigorously
when provided an open sunny location with light well-drained soil, ample nutrients,
and water. Cannabis can reach up to 5 m (16 ft.) in height in a 4- to 8-month spring-toautumn
growing season. Feral Cannabis populations are frequently found in association
with human habitation. Disturbed lands such as active and disused farm fields,
roadsides, railways, trails, trash piles, and exposed riverbanks are ideal habitats for
2 Watson and Clarke
wild and feral Cannabis because they provide open niches exposed to adequate sunlight.
Seeds usually germinate in 3–7 days. During the first 2–3 months of growth,
juvenile plants respond to increasing day length with a more vigorous vegetative growth
characterized by an increasing number of leaflets on each leaf. Later in the season
(after the summer solstice), shorter days (actually longer nights) induce flowering and
complete the life cycle. Cannabis begins to flower when exposed to short day lengths
of 12–14 hours or less (long nights of 10–12 hours or more) depending on its latitude
of origin. However, a single evening of interrupted darkness can disrupt flowering and
delay maturation. Conversely, a day or two of short day length can induce flowering
that may be irreversible in early-maturing varieties. If an individual plant grows with
sufficient space, as in seed or resin production, flower-bearing limbs will grow from
small growing points located at the base of the leaf petioles originating from nodes
along the main stalk. The flowering period is characterized by leaves bearing decreasing
numbers of leaflets and an accompanying change from vegetative growth and biomass
accumulation to floral induction, fertilization, seed maturation, and resin
production (1).
Cannabis is normally dioecious (male and female flowers developing on separate
plants), and the gender of each plant is anatomically indistinguishable before flowering.
However, Mandolino and Ranalli (2) report success using random amplified
polymorphic DNA analysis to identify male-specific DNA markers, and female-associated
DNA polymorphisms were also described by Hong et al. (3). The floral development
of male and female plants varies greatly. Whereas male flowers with five
petals and prominent stamens hang in loose clusters along a relatively leafless upright
branch, the inconspicuous female flowers are crowded into dense clusters along with
small leaflets at the base of each larger leaf along the branch (see Fig. 1). Pollen grains
require air currents to carry them to the female flowers, resulting in fertilization and
consequent seed set. Viable pollen can be carried by the wind for considerable distance
(4); the male plants cease shedding pollen after 2–4 weeks and usually die before
the seeds in the female plants ripen. Pollen has been frozen and successfully used for
seed production up to 3 years later.
The single seed in each female flower ripens in 3–8 weeks and will either be
harvested, be eaten by birds or rodents, or fall to the ground, where they may germinate
the following spring. This completes the natural 4- to 6-month life cycle. A large
female plant can produce up to half a kilogram of seed. Cannabis seeds are a balanced
source of essential fatty acids and easily digestible proteins and are suitable for use as
whole foods and dietary supplements. Essential fatty acids have been shown to have
many important physiological roles, and hemp seed oil is a valuable nutraceutical (5).
Recent research has confirmed that topical application of hemp seed oil is effective in
treating ear, nose, and throat ailments (6).
3. FIELD CROP PRODUCTION
When industrial hemp crops are grown for fiber or seed, both male and female
plants are usually left standing in the field until harvest. Most medical Cannabis is
grown for its psychoactive resin by a different technique. In the early 1970s, a handful
Cannabis and Natural Cannabis Medicines 3
Fig. 1. Medical Cannabis cultivars grown in the United Kingdom by GW Pharmaceuticals,
which form the basis for GW’s development of prescription medicines. The
larger inflorescence (A) is a cannabidiol (CBD)-rich cultivar containing only traces of
Δ9-tetrahydrocannabinol (THC), and the smaller inflorescence (B) is a THC-rich
cultivar containing only traces of CBD.
4 Watson and Clarke
of North American illicit marijuana cultivators began to grow sinsemilla (Spanish for
“without seed”) marijuana that within a few years became the predominant style of
North American and European marijuana production. The sinsemilla effect is achieved
by eliminating male plants from the fields, leaving only the unfertilized and therefore
seedless female plants to mature for later flower and/or resin harvest.* In lieu of setting
seed in the earliest flowers, the female plants continue to produce additional flowers
covered by resin glands, which increases the percentage of psychoactive and medically
valuable Δ9-tetrahydrocannabinol (THC) or other cannabinoids in these flowers.
Yields of terpenoid-rich essential oils produced in the resin glands along with the
closely related terpenophenolic cannabinoids are also significantly raised in seedless
flowers (7). Throughout the 1980s, the vast majority of domestically produced North
American and European drug Cannabis was grown from seed in outdoor gardens, but
during the 1990s the popularity of growing sinsemilla in greenhouses and indoors
under artificial lights grew rapidly.
4. GREENHOUSE AND GROW ROOM PRODUCTION
Most Cannabis presently used for medical purposes is grown indoors under artificial
lights. Modern indoor growers most often grow their own clones under halide
and sodium vapor light systems set up in attics, bedrooms, or basements. Crops grown
from seed are typically made up of large male and female plants that require a lot of
space and exhibit a wide range of physical and biochemical characteristics. A Cannabis
breeder relies on this variation as genetic potential for improving varieties,
whereas a drug Cannabis producer wants a profitable and uniform crop and uses female
clones to improve grow room yields. Consequently, vegetative production of female
clones and the production of seedless flowers preclude the possibility of seed production
and variety improvement. Vegetatively propagated crops are preferred because
indoor garden space is limited, only female Cannabis plants produce resin of medical
value, and it is both inconvenient and expensive to purchase reliable drug Cannabis
seed. In addition, the legal systems of many nations penalize growers of more plants
(vegetative, male or female) with harsher penalties. Under artificial growing conditions,
crops are reproduced vegetatively by rooting cuttings of only select female plants,
transplanting, and inducing flowering almost immediately so that the mature crop is
short and compact. Cuttings of one plant are all genetically identical members of a
single clone, so they will all respond in the same way to environmental influences and
will be very similar in appearance. When environmental influences remain constant,
the clone will yield serial crops of nearly identical uniform seedless females each time
it is grown.
Female “mother” plants used for cutting stock must be maintained in a constantly
vegetative state under 18-hour or longer day lengths or they will begin to flower.
Serial cuttings can be removed, rooted, grown under long day length, and used to
replace older mother plants indefinitely. If the mother plants remain free of viruses or
other pathogens, there is no loss of vigor after multiple rounds of vegetative propaga-
*This technique was first encountered by British working in India, but we are unsure of its history prior
to 1800.
Cannabis and Natural Cannabis Medicines 5
tion. Serially propagated clones have been maintained for more than 20 years. Whenever
flowering plants are required, small rooted cuttings (10–30 cm tall) are moved
into a flowering room with a day length of 10–13 hours to mature in 7–14 weeks.*
Vegetatively produced plants can fully mature when they are less than 1 m (3 ft.)
tall and form flowers from top to bottom and look like a rooted branch from a large
plant grown from seed. The length of time between the induction of flowering and full
maturity of the female floral clusters depends largely on the variety being grown and
the day length. Some cultivars mature much more quickly than others, and plants tend
to be shorter when mature than those of slower-ripening varieties. Cannabis plants
mature faster when they are given shorter day lengths of 10 hours, but most cultivars
have an optimum day length requirement for maximum flower production in the shortest
time—around 12–13 hours. Under ideal environmental conditions and expert management,
yields of dried flowers commonly reach 400 g/m2 per crop cycle. As a result
of multiple cropping four or five times per year, total annual yields can add up to more
than 2 kg of dried flowers per square meter.
In vitro techniques combined with low temperatures would allow long-term storage
of wide varieties of living germplasm and could be an important storage technique
for germplasm collections and breeders. Several research groups have reported success
with vegetatively reproducing and initiating shooting in undifferentiated callus
tissue and rooting of branch tips. The induction of rooting in callus and branch tips is
straightforward. However, inducing shoots in callus tissue has proven more problematic
and needs additional improvement (2,8). Further research and commercial applications
of in vitro techniques are expected in the near future.
5. RESIN GLAND ANATOMY AND DEVELOPMENT
As resin gland development commences, the medically important cannabinoids
and the associated terpenes begin to appear. Although the cannabinoids are odorless,
terpenes are the primary aromatic principles found in the essential oil of Cannabis
(9,10). Most interesting economically and medically are the cannabinoid-rich terpenoid
secretions of the head cells of glandular hairs densely distributed across the myriad
surfaces of the female flowers. Male plants are of no consequence in medicine production
because they develop few glandular trichomes and consequently produce few
cannabinoids or terpenes. Solitary resin glands most often form at the tips of slender
stalks that form as extensions of the plant surface and glisten in the light. The cluster
of one to two dozen glandular head cells atop each stalk secretes aromatic terpenecontaining
resins with very high percentages of cannabinoids (>80%) that collects in
vesicles under a thin membrane surrounding the secretory head cells. The secreted
resin component is in large part physically segregated from the secretory cells (11).
This isolates the resin from the atmosphere as well as membrane-bound enzyme systems
within the secretory cells, possibly protecting the terpenes and cannabinoids from
oxidative degradation and enzymatic change. At the base of each cluster of resin head
*Cannabis breeders maintain male clones in the same way and induce them to flower whenever pollen
is required to produce seed. However, males are often more difficult than females to maintain in the vegetative
state.
6 Watson and Clarke
cells lies an abscission layer allowing the resin gland and secreted resin to be easily
removed by mechanical means (see Fig. 2). Hashish or charas is simply millions of
resin glands that have been rubbed, shaken, or washed from fresh or dry plants and
compressed into a dense mass (11).
Resin glands containing cannabinoids and terpenes may have an adaptive significance
in reducing insect and fungal attack (12). However, Cannabis crops are subject
to infestation by a wide variety of pests (13), particularly under greenhouse and
grow room conditions.
6. CANNABINOID AND TERPENOID BIOSYNTHESIS
It is not surprising that cannabinoids are produced along with terpenoid compounds.
Terpenes comprise a large group of compounds synthesized from C10 isoprene
subunits. Monoterpenes (C10) and sesquiterpenes (C15) are the classes most commonly
found in Cannabis. Terpenoids are the primary aromatic constituents of Cannabis
resin, although they constitute only a small percentage of organic solvent extracts.
Cannabinoids are terpenophenolic compounds chemically related to the terpenoid compounds
as the ring structure is derived from a geranyl pyrophosphate C10 terpenoid
subunit. Cannabinoids make up a large portion of the resin and can make up as much
as 30% by weight of dried flowering tops. Cannabinoids are not significantly present
in extracts prepared by steam distillation (15).
Fig. 2. Microscope photograph and drawing of a Cannabis resin gland. The secretory
head cells are easily visible within the transparent blister of cannabinoid and terpenoid-
rich resin. (Photo courtesy of David Potter, drawing from ref. 14.)
Cannabis and Natural Cannabis Medicines 7
Our basic understanding of the biosynthesis of the major cannabinoids comes
largely from the research of Yukihiro Shoyama and colleagues at Kyushu University
in Japan (16,17). Cannabinoid biosynthesis begins with the incorporation of geranyl
pyrophosphate (a terpenoid compound) with either a C10 polyketide for the propyl (C3
side chain) or a C12 polyketide for the pentyl (C5 side chain) cannabinoid series into
either cannabigerovarin (CBGV) or cannabigerol (CBG), respectively. Research by
Etienne de Meijer at HortaPharm B.V. in the Netherlands shows that there is a single
allele (Pr) controlling the propyl pathway to CBGV and another allele (Pe) controlling
the pentyl pathway to CBG. The biosyntheses of THC, cannabidiol (CBD), and
cannabichromene (CBC) (or tetrahydrocannabivarin [THCV], cannabidivarin [CBDV],
or cannabichromavarin [CBCV]) are controlled by a suite of three enzymes, each controlled
by a single allele: T, D, and C, respectively. The three enzymes can likely use
either propyl CBGV or pentyl CBG for the propyl and pentyl pathways, depending on
which substrate is available. This hypothesis was verified by Flachowsky et al. (18).
Continued research by de Meijer et al. (19) (see Fig. 3) has shown that CBD and THC
biosynthesis are controlled by a pair of co-dominant alleles, which code for isoforms
of the same synthase, each with a different specificity for converting the common
precursor CBG into either CBD or THC. The group also identified by random amplified
polymorphic DNA analysis three chemotype-associated DNA markers that show
tight linkage to chemotype and co-dominance.
7. MEDICAL VALUES OF TERPENES
The terpenoid compounds found in Cannabis resin are numerous, vary widely
among varieties, and produce aromas that are often characteristic of the plant’s geographic
origin. Although more than 100 different named terpenes have been identified
from Cannabis, no more than 40 known terpenes have been identified in a single plant
sample, and many more remain unnamed (11). Terpenes are produced via multibranched
biosynthetic pathways controlled by genetically determined enzyme systems. This situation
presents plant breeders with a wide range of possible combinations for developing
medical Cannabis varieties with varying terpenoid profiles and specifically targeted
medical uses. Preliminary breeding experiments confirm that the terpenoid profiles of
widely differing parents are frequently reflected in the hybrid progeny.
Only recently have Cannabis essential oils become economically important as
flavorings and fragrances (17). Early Cannabis medicines were formulated from alcoholic
whole flower or resin extracts and contained terpenes, although they were not
recognized to be of medical importance. Several of the monoterpenes and sesquiterpenes
found in Cannabis and derived from other botanical and synthetic sources are
used in commercial medicines. Other as-yet-unidentified terpenes may be unique to
Cannabis. The highly variable array of terpenoid side-chain substitutions results in a
range of human physiological responses. Certain terpenes stimulate the membranes of
the pulmonary system, soothe the pulmonary passages, and facilitate the absorption of
other compounds (15). Terpenoid compounds are incorporated into pulmonary medical
products such as bronchial inhalers and cough suppressants. Casual studies indicate
that when pure THC is smoked, it produces subjectively different effects than it
does when combined with trace amounts of mixed Cannabis terpenes. Clinical trials
8 Watson and Clarke
using whole plant extracts of known cannabinoid content and varying terpenoid profiles
will determine whether terpenoid compounds have an effect on the pharmacokinetics
of the cannabinoids.
8. CANNABIS’S ORIGIN, DOMESTICATION, AND DISPERSAL
Cannabis originated either in the riverine valleys of Central Asia or in northern
South Asia along the foothills of the Himalayas and was first cultivated in China on a
large scale for fiber and seed production and soon after in India for resin production.
Various cultures have traditionally used Cannabis for different purposes. European
and East Asian societies most often used Cannabis for its strong fibers and nutritious
seeds. Species of Cannabis from these regions are usually relatively low in THC
(average <1%>20% dry
weight) at the expense of CBD.
Cannabis and Natural Cannabis Medicines 13
Pure indica varieties are still highly prized breeding stock, and new indica introductions
from Central Asia are occasionally received. Sativa varieties from Mexico, South
Africa, and Korea are gaining favor with breeders because they mature early but do
not suffer from the drawbacks of many indicas. Recently, Cannabis breeders have
become more interested in variations in subjective effects between different clones
and are developing varieties with enhanced medical efficacy based on feedback from
medical Cannabis users.
Genetic modification has also reached Cannabis. Researchers in Scotland have
successfully transferred genes for gray mold resistance to an industrial hemp variety
(28). Because Botrytis is one of the leading pests of Cannabis, causing crop loss and
contaminating medical supplies, the transfer of resistance into medical varieties would
be of great value. In addition, other agronomically valuable traits may also be transferred
to Cannabis, such as additional pest resistance, increased yields of medically
valuable compounds, tolerance of environmental extremes, and sexual sterility. However,
so far the acceptance of genetically modified (GM) organisms has been timid.
The European Union, for example, has installed strict regulations to prevent the accidental
release of GM crop plants, and production of GM Cannabis in the European
Union may be impractical. Cannabis presents a particularly high risk for transmitting
genetically modified genes to industrial hemp crops and weedy Cannabis because it is
wind-pollinated. If sterile female GM clones could be developed and used for production,
then gene transfer would be blocked. Genes coding for cannabinoid biosynthesis
might also be transferred from Cannabis to less politically sensitive organisms.
GW Pharmaceuticals Ltd. in the United Kingdom is engaged in the development
of prescription medicines derived from Cannabis and, as part of its research program
Fig. 5. Both recreational and medical Cannabis typically originate from either seeded
plants used primarily for traditional hashish production or seedless plants grown
primarily for “sinsemilla” marijuana and occasionally for modern hashish production.
THC, Δ9-tetrahydrocannabinol; CBD, cannabidiol.
14 Watson and Clarke
to develop novel cannabinoid medicines, supports an ongoing breeding project to
develop high-yielding Cannabis cultivars of known cannabinoid profile. The aims of
this research are to create varieties that produce only one of the four major cannabinoid
compounds (e.g., THC, CBD, CBC, CBG, or their propyl homologs) as well as
selected varieties with consistently uniform mixed cannabinoid and terpenoid profiles.
These uniform profiles allow for the formulation of nonsmoked medicinal products,
which can meet the strict quality standards of international regulatory authorities.
A sublingual spray application of plant-derived THC and CBD began clinical trials
for relief of multiple sclerosis-associated symptomology in 1999. These clinical trials
have gone on to include patients with neuropathic pain and cancer pain.
14. CONCLUSION
Cannabis has had a long association with humans, and anecdotal evidence for its
medical efficacy is plentiful. Since the 1970s, modern North American and European
drug Cannabis varieties have resulted largely from crosses made by clandestine breeders
between South Asian sativa marijuana varieties that spread early throughout South
and Southeast Asia, Africa, and the New World and Central Asian indica hashish
varieties. These hybrid varieties are now commonly used in Western societies for
medical Cannabis.
Largely as a response to increased law enforcement and the limited commercial
availability of high-quality medical grade Cannabis, patients growing their own plants
and self-medicating is a trend rapidly spreading across North America, Europe, and
around the globe. The political climate surrounding medical Cannabis legislation has
become more informed, compassionate, and lenient. Cannabis cultivation for personal
medical use will eventually be legalized or tolerated in many jurisdictions, if not by the
public openly favoring legalization, then by increasing governmental awareness of the
inefficiency inherent in attempted prohibition of a popular and effective medicine.
Pharmaceutical research companies are developing new natural cannabinoid formulations
and delivery systems that will meet government regulatory requirements.
As clinical trials prove successful and the understanding of Cannabis’s efficacy and
safety as a modern medicine spreads, patients can look forward to a steady flow of
new Cannabis medicines providing effective relief from a growing number of indications.
REFERENCES
1. Clarke, R. C. (1981) Marijuana Botany, Berkeley: Ronin Publishing.
2. Mandolino, G. and Ranalli, P. (1999) Advances in biotechnological approaches for hemp
breeding and industry, in Advances in Hemp Research. (Ranalli, P. ,ed.), Haworth Press,
New York, pp. 185–211.
3. Hong, S., Song, S-J., and Clarke, R. C. (2003) Female-associated DNA polymorphisms of
hemp (Cannabis sativa L.) J. Indust. Hemp 1, 5–9.
4. Small, E. and Antle, T. (2003) A preliminary study of pollen dispersal in Cannabis sativa
in relation to wind direction. J. Indust. Hemp 8, 37–50.
5. Deferne, J-L. and Pate, D. W. (1996) Hemp seed oil: a source of valuable essential fatty
acids. J. Int.Hemp Assoc. 3, 1, 4–7.
Cannabis and Natural Cannabis Medicines 15
6. Grigoriev, O. V. (2002) Application of hempseed (Cannabis sativa L.) oil in treatment of
ear, nose and throat (ENT) disorders. J. Indust. Hemp 7, 5–15.
7. Meier, C. and Mediavilla, V. (1998) Factors influencing the yield and the quality of hemp
(Cannabis sativa L.) essential oil. J. Int. Hemp Assoc. 5, 16–20.
8. Liu, Y. and Tang, X. (1984) Green seedling of hemp acquired by tissue culture. China’s
Fibre Crops 2, 19, 29 [in Chinese].
9. Hendriks, H., Malingre, T. M., Batterman, S., and Bos, R. (1978) The essential oil of Cannabis
sativa L. Pharm. Weekbl. 113, 413–424.
10. Ross, R. A. and ElSohly, M. A. (1996) The volatile oil composition of fresh and air-dried
buds of Cannabis sativa L. J. Nat. Prod. 59, 49–51.
11. Clarke, R. C. (1998) Hashish!, Red Eye Press, Los Angeles.
12. Pate, D. W. (1994) Chemical ecology of Cannabis. J. Int. Hemp Assoc. 1, 29, 32–37.
13. McPartland, J., Clarke, R. C., and Watson, D. P. (2000) Hemp Diseases and Pests, CAB
International, Wallingford, UK.
14. Briosi, G. and Tognini, F. (1894) Intorno alla anatomia della canapa (Cannabis sativa L.)
parte prima—organi sessual, Atti dell’ Instituto Botanico di Pavia, Serie I, Vol. 3.
15. McPartland, J. and Mediavilla, V. (2002) Cannabis and Cannabinoids: Pharmacology and
Therapeutic Potential (Grotenhermen, F. and Russo, E., eds.), Haworth Integrative Healing
Press, New York, pp. 401–409.
16. Taura, F., Morimoto, S., Shoyama, Y., and Mechoulam, R. (1995) First direct evidence for the
mechanism of delta-1-tetrahydrocannabinol acid biosynthesis. J. Am. Chem. Soc. 117, 9766–9767.
17. Taura, F., Morimoto, S., and Shoyama, Y. (1996) Purification and characterization of
cannabidiolic-acid synthase from Cannabis sativa L. Biochemical analysis of a novel enzyme
that catalyzes the oxidocyclization of cannabigerolic acid to cannabidiolic acid. J.
Biol. Chem. 271, 17411–17416.
18. Flachowsky, H., Schumann, E., Weber, W. E., and Peil, A. (2000) AFLP-marker for male
plants of hemp (Cannabis sativa L.) Poster presented at the 3rd Bioresource Hemp Symposium,
Wolfsburg, Germany, September 13–16.
19. de Meijer, E. P. M., Bagatta, M., Carboni, A., et al. (2003) The inheritance of chemical
phenotype in Cannabis sativa L. Genetics 163, 335–346.
20. Small, E. and Cronquist, A. (1976) A practical and natural taxonomy for Cannabis. Taxon
25, 405–435.
21. Schultes, R. E., Klein, W. M., Plowman, T., and Lockwood, T. E. (1974) Cannabis: an example
of taxonomic neglect. Botanical Museum Leaflets, Harvard University 23, 337–364.
22. Serebriakova, T. I. (1940) Fiber plants, in Flora of Cultivated Plants. Vol.4, Part1 (Wulff,
E. V., ed.), State Printing Office, Moscow and Leningrad [in Russian].
23. Vavilov, N. and Bukinich, D. D. (1929) Agricultural Afghanistan. Bull. Appl. Bot. Genet.
Plant Breed.Supp. 33, 378–382, 474, 480, 584–585, 604.
24. Hillig, K. W. and Mahlberg, P. G. (2004) Genetic evidence for speciation in Cannabis
(Cannabaceae). Genet. Resources Crop Evol. 52, 161–180.
25. de Meijer, E. P. M. (1999) Cannabis germplasm resources, in Advances in Hemp Research
(Ranalli, P., ed.), Haworth Press, New York, pp. 133–151.
26. HortaPharm, personal communication (1998) HortaPharm BV develops industrial Cannabis
cultivars and provided the starting materials GW Pharmaceuticals breeding project
in the United Kingdom.
27. Gierenger, D. (1999) Medical Cannabis potency testing. Bull. Multidisc. Assoc. Psychedel.
Stud. 9, 20–22.
28. MacKinnon, L. (2003) Genetic transformation of Cannabis sativa Linn: a multi purpose
fibre crop, doctoral thesis, University of Dundee, Scotland.
16 Watson and Clarke
Chemistry of Cannabis Constituents 17
From: Forensic Science and Medicine: Marijuana and the Cannabinoids
Edited by: M. A. ElSohly © Humana Press Inc., Totowa, New Jersey
17
Chapter 2
Chemistry and Analysis
of Phytocannabinoids
and Other Cannabis Constituents
Rudolf Brenneisen
1. THE CHEMISTRY OF PHYTOCANNABINOIDS AND NONCANNABINOID-TYPE
CONSTITUENTS
1.1. Phytocannabinoids
1.1.1. Introduction
The Cannabis plant and its products consist of an enormous variety of chemicals.
Some of the 483 compounds identified are unique to Cannabis, for example, the
more than 60 cannabinoids, whereas the terpenes, with about 140 members forming
the most abundant class, are widespread in the plant kingdom. The term “cannabinoids”
represents a group of C21 terpenophenolic compounds found until now uniquely
in Cannabis sativa L. (1). As a consequence of the development of synthetic cannabinoids
(e.g., nabilone [2], HU-211 [dexanabinol; ref. {3}, or ajulemic acid [CT-3; ref.
4]) and the discovery of the chemically different endogenous cannabinoid receptor
ligands (“endocannabinoids,” e.g., anandamide, 2-arachidonoylglycerol) (5,6), the term
“phytocannabinoids” was proposed for these particular Cannabis constituents (7).
1.1.2. Chemistry and Classification
So far, 66 cannabinoids have been identified. They are divided into 10 subclasses
(8–10) (see Table 1).
18 Brenneisen
1. Cannabigerol (CBG) type: CBG was the first cannabinoid identified (11), and its precursor
cannabigerolic acid (CBGA) was shown to be the first biogenic cannabinoid
formed in the plant (12). Propyl side-chain analogs and a monomethyl ether derivative
are other cannabinoids of this group.
2. Cannabichromene (CBC) type: Five CBC-type cannabinoids, mainly present as C5-
analogs, have been identified.
3. Cannabidiol (CBD) type: CBD was isolated in 1940 (13), but its correct structure was
first elucidated in 1963 by Mechoulam and Shvo (14). Seven CBD-type cannabinoids
with C1 to C5 side chains have been described. CBD and its corresponding acid CBDA
Table 1
Cannabinoids
(continued)
Chemistry of Cannabis Constituents 19
are the most abundant cannabinoids in fiber-type Cannabis (industrial hemp). Isolated
in 1955, CBDA was the first discovered cannabinoid acid.
4. Δ9-Tetrahydrocannabinol (THC) type: Nine THC-type cannabinoids with C1 to C5
side chains are known. The major biogenic precursor is the THC acid A, whereas
Table 1 (continued)
(continued)
20 Brenneisen
THC acid B is present to a much lesser extent. THC is the main psychotropic principle;
the acids are not psychoactive. THC (6a,10a-trans-6a,7,8,10a-tetrahydro-6,6,9-
trimethyl-3-pentyl-6H-dibenzo[b,d]pyran-1-ol) was first isolated in 1942 (15), but the
correct structure assignment by Gaoni and Mechoulam took place in 1964 (16).
Table 1 (continued)
(continued)
Chemistry of Cannabis Constituents 21
5. Δ8-THC type: Δ8-THC and its acid precursor are considered as THC and THC acid
artifacts, respectively. The 8,9 double-bond position is thermodynamically more stable
than the 9,10 position. Δ8-THC is approx 20% less active than THC.
Table 1 (continued)
(continued)
22 Brenneisen
6. Cannabicyclol (CBL) type: Three cannabinoids characterized by a five-atom ring and
C1-bridge instead of the typical ring A are known: CBL, its acid precursor, and the C3
side-chain analog. CBL is known to be a heat-generated artifact from CBC.
7. Cannabielsoin (CBE) type: Among the five CBE-type cannabinoids, which are artifacts
formed from CBD, are CBE and its acid precursors A and B.
Table 1 (continued)
(continued)
Chemistry of Cannabis Constituents 23
8. Cannabinol (CBN) and Cannabinodiol (CBND) types: Six CBN- and two CBND-type
cannabinoids are known. With ring A aromatized, they are oxidation artifacts of THC
and CBD, respectively. Their concentration in Cannabis products depends on age and
storage conditions. CBN was first named in 1896 by Wood et al. (17) and its structure
elucidated in 1940 (18).
Table 1 (continued)
(continued)
24 Brenneisen
9. Cannabitriol (CBT) type: Nine CBT-type cannabinoids have been identified, which
are characterized by additional OH substitution. CBT itself exists in the form of both
isomers and the racemate, whereas two isomers (9-a- and 9-b-hydroxy) of CBTV
were identified. CBDA tetrahydrocannabitriol ester (ester at 9-hydroxy group) is the
only reported ester of any naturally occurring cannabinoids.
10. Miscellaneous types: Eleven cannabinoids of various unusual structure, e.g., with a furano
ring (dehydrocannabifuran, cannabifuran), carbonyl function (cannabichromanon, 10-
oxo-δ-6a-tetrahydrocannabinol), or tetrahydroxy substitution (cannabiripsol), are known.
Table 1 (continued)
(continued)
Chemistry of Cannabis Constituents 25
1.1.3. THC Potency Trends
From 1980 to 1997, a total of 35,213 samples of confiscated Cannabis products
(Cannabis, hashish, hashish oil) representing more than 7717 tons seized in the United
States were analyzed by gas chromatography (GC) (19). The mean THC concentration
increased from less than 1.5% in 1980 to 4.2% in 1997. The maximum levels
found were 29.9 and 33.1% in marijuana and sinsemilla Cannabis, respectively. Hashish
Table 1 (continued)
(continued)
26 Brenneisen
and hashish oil showed no particular potency trend. The highest THC concentrations
measured were 52.9 and 47.0%, respectively. Two studies performed in Switzerland
from 1981 to 1985 (20) and 2002 to 2003 (21) found mean THC concentrations in
marijuana samples of 1.4 and 12.9%, respectively. Maximum levels were 4.8 and 28.4%,
respectively. Reasons for this enormous increase in potency include progress in breed-
Table 1 (continued)
(continued)
Chemistry of Cannabis Constituents 27
ing, the tendency to cultivate under indoor conditions, and the worldwide access to
and exchange of seeds originating from high-THC cultivars via the Internet (22).
1.1.4. THC in Hemp Seed Products
The presence of THC in hemp seed products is predominantly the result of external
contact of the seed hull with cannabinoid-containing resins in bracts and leaves
during maturation, harvesting, and processing (23–25). The seed kernel is not entirely
free of THC but contains, depending on the hemp variety, less than 0.5 μg/g. Studies
on hemp oil conducted in the United States, Germany, and Switzerland have shown
THC levels from 11 to 117, 4 to 214, and up to 3568 μg/g, respectively (24,26–28).
These high levels were attributed to seeds from THC-rich, “drug-type” varieties, and
the lack of adequate cleaning procedures. In recent years, more careful seed drying
and cleaning have considerably lowered the THC content of seeds and oil available in
the United States (23,24). However, oils and hulled seeds containing 10–20 and 2–3 μg/g
THC, respectively, are still found on the US market.
Table 1 (continued)
28 Brenneisen
1.2. Noncannabinoid-Type Constituents
1.2.1. Terpenoids
The typical scent of Cannabis results from about 140 different terpenoids. Isoprene
units (C5H8) form monoterpenoids (C10 skeleton), sesquiterpenoids (C15),
diterpenoids (C20), and triterpenoids (C30; see Table 2). Terpenoids may be acyclic,
monocyclic, or polycyclic hydrocarbons with substitution patterns including alcohols,
ethers, aldehydes, ketones, and esters. The essential oil (volatile oil) can easily be
obtained by steam distillation or vaporization. The yield depends on the Cannabis
type (drug, fiber) and pollination; sex, age, and part of the plant; cultivation (indoor,
outdoor etc.); harvest time and conditions; drying; and storage (29–31). For example,
fresh buds from an Afghani variety yielded 0.29% essential oil (32). Drying and storage
reduced the content from 0.29 after 1 week and 3 months to 0.20 and 0.13%,
respectively (32). Monoterpenes showed a significantly greater loss than sesquiterpenes,
but none of the major components completely disappeared in the drying process.
About 1.3 L of essential oil per ton resulted from freshly harvested outdoor-grown
Cannabis, corresponding to about 10 L/ha (29). The yield of nonpollinated
(“sinsemilla”) Cannabis at 18 L/ha was more than twofold compared with pollinated
Cannabis (8 L/ha) (30). Sixty-eight components were detected by GC and GC/mass
spectrometry (MS) in fresh bud oil distilled from high-potency, indoor-grown Cannabis
(32). The 57 identified constituents were 92% monoterpenes, 7% sesquiterpenes,
and approx 1% other compounds (ketones, esters; refs. 9 and 32). The dominating
monoterpenes were myrcene (67%) and limonene (16%). In the essential oil from
outdoor-grown Cannabis, the monoterpene concentration varied between 47.9 and
92.1% of the total terpenoid content (29). The sesquiterpenes ranged from 5.2 to 48.6%.
The most abundant monoterpene was β-myrcene, followed by trans-caryophyllene,
α-pinene, trans-ocimene, and α-terpinolene. “Drug-type” Cannabis generally contained
less caryophyllene oxide than “fiber-type” Cannabis. Even in “drug-type” Cannabis,
the THC content of the essential oil was not more than 0.08% (29). In the
essential oil of five different European Cannabis cultivars, the dominating terpenes
were myrcene (21.1–35.0%), α-pinene (7.2–14.6%), α-terpinolene (7.0–16.6%), transcaryophyllene
(12.2.–18.9%), and α-humulene (6.1–8.7%; ref. 33). The main differences
between the cultivars were found in the contents of α-terpinolene and α-pinene.
Other terpenoids present only in traces are sabinene, α-terpinene, 1,8-cineole
(eucalyptol), pulegone, γ-terpinene, terpineol-4-ol, bornyl acetate, α-copaene,
alloaromadendrene, viridiflorene, β-bisabolene, γ-cadinene, trans-β-farnesene, transnerolidol,
and β-bisabolol (29,32,34).
1.2.2. Hydrocarbons
The 50 known hydrocarbons detected in Cannabis consist of n-alkanes ranging
from C9 to C39, 2-methyl-, 3-methyl-, and some dimethyl alkanes (10,35). The
major alkane present in an essential oil obtained by extraction and steam distillation
was the n-C29 alkane nonacosane (55.8 and 10.7%, respectively). Other abundant
alkanes were heptacosane, 2,6-dimethyltetradecane, pentacosane, hexacosane,
and hentriacontane.
Chemistry of Cannabis Constituents 29
1.2.3. Nitrogen-Containing Compounds
Cannabis sativa L. is one of the rare psychotropic plants in which the central
nervous system activity is not linked to particular alkaloids. However, two spermidine-
type alkaloids (see Table 3) have been identified among the more than 70 nitrogen-
containing constituents. Other nitrogenous compounds found are the quartenary
bases choline, trigonelline, muscarine, isoleucine betaine, and neurine. Among the 8
amides are, for example, N-trans-feruloyltyramine, N-p-coumaroyltyramine, and Ntrans-
caffeoyltyramine (see Table 4). Five lignanamide derivatives have been isolated,
including cannabisin A, B, C, and D (see Table 5).
Twelve simple amines, including piperidine, hordenine, methylamine, ethylamine,
and pyrrolidine, are known. The three proteins detected are edestin, zeatin, and
(continued)
Table 2
Terpenoids of the Essential Oil From Cannabis
30 Brenneisen
zeatinnucleoside; the six enzymes are edestinase, glucosidase, polyphenoloxydase,
peptidase, peroxidase, and adenosine-5-phosphatase. The 18 amino acids are of a structure
common for plants.
1.2.4. Carbohydrates
Common sugars are the predominant constituents of this class. Thirteen
monosacharides (fructose, galactose, arabinose, glucose, mannose, rhamnose, etc.),
two disaccharides (sucrose, maltose), and five polysaccharides (raffinose, cellulose,
hemicellulose, pectin, xylan) have been identified so far. In addition, 12 sugar alcohols
Table 2 (continued)
(continued)
Chemistry of Cannabis Constituents 31
and cyclitols (mannitol, sorbitol, glycerol, inositol, quebrachitol, etc.) and two amino
sugars (galactosamine, glucosamine) were found.
1.2.5. Flavonoids
Twenty-three commonly occurring flavonoids have been identified in Cannabis,
existing mainly as C-/O- and O-glycosides of the flavon- and flavonol-type aglycones
Table 2 (continued)
(continued)
32 Brenneisen
apigenin, luteolin, quercetin, and kaempferol (see Table 6; ref. 36). Orientin, vitexin,
luteolin-7-O-glucoside, and apigenin-7-O-glucoside were the major flavonoid glycosides
present in low-THC Cannabis cultivars (37). The cannflavins A and B are unique
to Cannabis (38,39).
1.2.6. Fatty Acids
A total of 33 different fatty acids, mainly unsaturated fatty acids, have been identified
in the oil of Cannabis seeds. Linoleic acid (53–60% of total fatty acids), α-
(continued)
Table 2 (continued)
Chemistry of Cannabis Constituents 33
linolenic acid (15–25%), and oleic acid (8.5–16%) are most common (see Table 7)
(40). Other unsaturated fatty acids are γ-linolenic acid (1–4%), stearidonic acid (0.4–
2%), eicosanoic acid (<0.5%), n =" 8)" n =" 6)" n =" 3)" n =" 2)." n =" 6)."> natural killer cells >> monocytes > polymorphonuclear
neutrophils > T8-lymphocytes > T4-lymphocytes (27). There is no evidence
that this receptor subtype is associated with neuronal tissue. However, there is
evidence that CB2 receptors can be induced in microglia, a cell of macrophage lineage
that is present in brain (28). CB1 and CB2 receptors are activated by THC.
Several cannabinoid receptor signaling pathways have also been identified. Both
cannabinoid receptor subtypes have the molecular signature of G protein-coupled
receptors. Actually, evidence for a G protein-coupled cannabinoid receptor preceded
the cloning of the CB1 receptor (29). There is strong evidence for CB1 receptor coupling
to multiple Gi/o proteins (30). The predominant effects of cannabinoids occur
through inhibitory G protein function, including inhibition of adenylyl cylase, inhibition
of calcium channels (N and Q types), as well as activation of inwardly rectifying
potassium channels (31,32). These actions are highly relevant to neurotransmitter
release, as will be discussed later.
Although evidence of cannabinoid receptors and their signaling pathways was
sufficient to establish biological relevance, identification of the natural ligands was
essential for functional relevance. Three distinct arachidonoyl derivatives have been
identified as natural ligands for the cannabinoid receptors. The amide anandamide
(33), the ester 2-arachidonoyl-glycerol (34,35), and the 2-arachidonoyl glyceryl ether
(36) have been identified thus far as endocannabinoids. These endogenous substances
are considered endocannabinoids because they activate CB1 cannabinoid receptors and
produce effects that are consistent with CB1 cannabinoid receptor activation. Moreover,
the synthetic and degradative pathways for anandamide and 2-
arachidonoylglycerol have been identified in relevant tissues.
There is substantial evidence that a calcium-dependent, energy-independent
transacylase transfers arachidonic acid from the sn-1 position of phosphatidylcholine
to the amino group in phosphatidylethanolamine to form N-arachidonoyl-phosphatidylethanolamine,
with subsequent hydrolysis by a phospholipase D-type enzyme to
form anandamide (37). Inactivation of anandamide occurs primarily via fatty acid
amide hydrolase, an enzyme that has been cloned (38). Blockade or deletion of this
enzyme in mice greatly potentiates the actions of exogenously administered anandamide
(39). Diacylglycerol lipase synthesizes 2-arachidonoylglycerol (40). This enzyme is
required for axonal growth during development and for retrograde synaptic signaling
at mature synapses. The inactivation of 2-arachidonoylglycerol occurs by a
monoglyceride lipase (41). Both of these synthetic and degradative 2-
arachidonoylglycerol enzymes have been cloned.
The discovery that the endogenous cannabinoid system consists of two receptor
subtypes, signaling pathways, endogenous ligands, and synthetic and metabolic pathways
for these ligands provided unique opportunities to understand the mechanisms
through which cannabinoids produce their effects. More importantly, the endogenous
cannabinoid system provides a means for verifying whether cannabinoids are acting
directly or indirectly to produce their wide range of pharmacological effects. At the
128 Martin
same time, the functional role of the endogenous cannabinoid system in normal physiological
processes, as well as in disease states, is beginning to emerge. This chapter is
confined to appetite, emesis, pain, and drug dependence.
3. APPETITE
The desire to consume food represents one of the fundamental physiological processes
essential for survival. It is therefore not surprising that appetite is regulated by
a highly complex integration of hormonal and neuronal systems to maintain homeostasis.
Disruptions of these homeostatic mechanisms can result in either food deprivation
or excess eating. Appetite is also easily disrupted in many disease states, such as
cancer and HIV infection.
There is ample evidence that the endogenous cannabinoid system plays a role in
appetite homeostasis. Although both marijuana and THC have been shown to stimulate
appetite, direct evidence for the involvement of cannabinoid receptors was provided
by a study in which CB1 receptor knockout mice ate less than wild-type mice
following food restriction (42). The selective antagonist, rimonabant (SR 141716),
provided additional support for CB1 receptor involvement in that this compound reduced
food intake in wild-type but not CB1 knockout mice (42). There are several lines of
evidence indicating that the brain is a prominent site for cannabinoid regulation of
appetite. For example, the hypothalamus contains both CB1 receptors and the
endocannabinoids anandamide and 2-arachidonoylglycerol. Direct injections of
anandamide into the hypothalamus of rats induced hyperphagia, an effect that was
blocked by the CB1 receptor antagonist rimonabant (43). In addition, there is evidence
of an interrelationship between the endocannabinoids and leptin, a key anorexigenic
agent that is secreted by adipose tissue and acts within the hypothalamus at the arcuate
nucleus to suppress appetite-stimulating peptides and stimulate the activity of appetite-
reducing peptides. Di Marzo et al. (42) demonstrated that acute treatment with
leptin reduces the levels of anandamide and 2-arachidonoyl glycerol in the hypothalamus
of normal rats. On the other hand, these endocannabinoids were elevated in obese
leptin-deficient ob/ob and obese leptin-receptor-deficient db/db mice.
A second central component of cannabinoid-mediated food intake likely involves
reward pathways and the hedonic aspect of eating. Higgs et al. (44) recently demonstrated
that both THC and anandamide increased sucrose intake in rats, whereas
rimonabant decreased it. Fasting increases levels of anadamide and 2-
arachidonoylglycerol in the nucleus accumbens, a brain structure crucial for reward
(45). Levels of endocannabinoids were not changed in satiated rats. In diet-induced
obese rats there was a significant decrease in CB1 receptor density in hippocampus,
cortex, nucleus accumbens, and entopeduncular nucleus, but not in hypothalamus (46).
Collectively, these data strongly implicate a central mechanism for endocannabinoid
influence on diet.
There are also several suggestions that endocannabinoids act peripherally to regulate
metabolism. Cota et al. (47) found CB1 receptors in adipocytes, thereby raising
the possibility of a direct peripheral lipogenic mechanism. Furthermore, rimonabant
stimulated Acrp30 (adiponectin) messenger RNA expression in adipose tissue and
reduced hyperinsulinemia in obese (fa/fa) rats (48). At present, there is no evidence
Therapeutic Potential of Cannabinoids 129
that CB1 receptor agonists produce opposing effects. Nevertheless, these findings suggest
that the endocannabinoid system may have a direct effect on energy balance and
lipid metabolism.
Based on the above findings, it seems logical that the endocannabinoid system
could be manipulated for the purpose of treating either weight loss or obesity (49).
Indeed, one of the most consistent effects of smoking marijuana is an increase in
appetite. A recent study compared marijuana smoking with oral THC, and both treatments
increased food intake (50). However, the results in patient populations have
been less definitive. Beal et al. (51) examined the effects of THC on appetite and
weight in patients with AIDS-related anorexia. They reported modest improvement in
appetite and mood along with stabilization in weight. Several early investigations
showed that THC increased appetite in cancer patients (52,53). More recently, Jatoi et
al. (54) compared megestrol acetate with THC for palliating cancer-associated anorexia.
They found that megestrol acetate provided superior anorexia palliation among
advance cancer patients. On the other hand, Nelson et al. (55) evaluated the effects of
THC on appetite in advanced cancer patients suffering from anorexia. Most patients
completed the 28-day study and experienced improved appetite. With regard to the
CB1 receptor antagonist rimonabant, it has been shown to be effective in reducing
food intake in both laboratory animals (described earlier) and in promoting weight
loss in humans during recent phase III clinical trials.
4. EMESIS
Although emesis has a dramatic impact on appetite, the mechanisms underlying
emesis trials and nausea/vomiting are quite distinct. In contrast to the predominant
role of the hypothalamus in appetite, the postrema-nucleus tractus solatarius in the
brainstem plays an essential role in emesis. Additionally, the dopaminergic, cholinergic,
and serotonergic systems in the gastrointestinal tract can contribute to emesis.
Several animal studies indicate a direct role for endocannabinoid modulation of emesis.
Darmani et al. (56) showed that CB1 receptor agonists reduced cisplatin-induced
emesis in the least shrew, whereas the antagonist rimonabant produced the opposite
effects. Similar findings were reported with cannabinoid agonists that attenuated
lithium-induced vomiting in the musk shrew (57,58). In addition, combinations of
inactive doses of THC and ondansetron were effective in blocking vomiting in the
musk shrew (58). The musk shrew has also been used to study conditioned retching,
an animal model of anticipatory nausea and vomiting. THC completely suppressed
conditioned retching in this model (59). In addition, cannabinoid agonists suppressed
lithium-induced conditioned rejection, a model of nausea in rats (60). Opioids are
known to be powerful emetogenic agents. Activation of the cannabinoid system was
also effective in blocking opioid-induced vomiting in ferrets (61). CB1 cannabinoid
receptors were strongly implicated in that rimonabant blocked the action of cannabinoid
agonists in this model. Importantly, Darmani et al. (62) found prominent CB1
receptor binding in the nucleus tractus solartius of the shrew. The exact nature of the
role played by endocannabinoids is unclear at this time. A metabolically stable analog
of anandamide blocked vomiting, whereas another endocannabinoid, 2-
arachidonoylglycerol, was emetogenic (62).
130 Martin
As for clinical evidence, anecdotal reports of patients smoking marijuana to control
chemotherapy-induced nausea and vomiting provided the initial clues. These reports
led to clinical studies with THC in which it was found to be useful in patients whose
chemotherapy-induced nausea and vomiting were refractory to other standard
antiemetics available at that time (63). Plasse et al. (53) reported that combinations of
THC and prochlorperazine resulted in enhancement of efficacy as measured by duration
of episodes of nausea and vomiting and by severity of nausea. In addition, the
incidence of psychotropic effects from THC appeared to be decreased by concomitant
administration of prochlorperazine. The combination was significantly more effective
than was either single agent in controlling chemotherapy-induced nausea and vomiting
(64). Nabilone, a synthetic derivative of THC, was also reported to be an effective
oral antiemetic drug for moderately toxic chemotherapy (65). Cannabinoids have also
been found to be effective in treating nausea and vomiting in children undergoing
chemotherapy (66,67). As for the current status of antiemetics, serotonergic anatagonists
such as ondansetron have become the standards for managing emesis. These agents
have proven to be effective in preventing chemotherapy-induced nausea and vomiting
in most patients. However, delayed nausea and vomiting are less well controlled. Therefore,
the search for more effective agents continues. Combination therapy with
ondansetron and THC has not been fully explored. In addition, there is a need for a
higher-efficacy CB1 receptor agonist with fewer side effects.
5. PAIN
Animal studies have firmly established cannabinoid-induced analgesia in a wide
array of acute and chronic pain models (68). Most of this evidence is based on CB1
receptor agonists such as THC and related synthetic derivatives. It has been firmly
established that these effects are being mediated through the endocannabinoid system.
First, there is an excellent correlation between cannabinoid analgesics and their affinity
for the CB1 receptor (69). Second, the CB1 receptor antagonist rimonabant is effective
in blocking the analgesic effects of cannabinoid agonists (70,71). As expected,
the endogenous ligands anandamide and 2-arachidonoylglycerol exhibit analgesic properties
when administered to laboratory animals (34,72). Mice with genetic deletion of
fatty acid amidohydrolase, the enzyme that hydrolyzes anandamide, exhibit enhanced
analgesic activity with exogenously administered anandamide (39). More importantly,
these animals have elevated endogenous anandamide levels as well as an increased
pain threshold, evidence that supports a physiological role for endocannabinoids in
pain perception. Additional evidence for endocannabinoid pain modulation includes
cannabinoid suppression of spinal and thalamic nociceptive neurons, identification of
spinal, supraspinal, and peripheral sites of action, as well as evidence that
endocannabinoids are released upon electrical stimulation of the periaqueductal gray
and following inflammation in the periphery (73,74).
Although nociceptive events will stimulate the release of endocannabinoids, the
exact nature of their actions on pain neurotransmission remains to be fully established.
CB1 receptors are located predominantly on presynaptic terminals, and their activation
results in the inhibition of the neurotransmitter released at this site. Hohman et al.
Therapeutic Potential of Cannabinoids 131
examined the distribution of CB1 receptors in rat dorsal root ganglion and found them
present in only a subset of neurons containing substance P and calcitonin gene-related
peptide (75). There is evidence for localization of CB1 receptors on neurons containing
endogenous opioids. Welch and Stevens (76) demonstrated that cannabinoid agonists
potentiated morphine analgesia in laboratory animals. This laboratory later
demonstrated that THC, but not anandamide, stimulates the release of dynorphin A
(77). While there is an abundance of data illustrating interactions between the opioid
and cannabinoid systems, the exact nature of these interactions remains to be elucidated.
Although there is strong evidence that the endocannabinoid system regulates
pain pathways, the effectiveness of CB1 agonists as analgesics has been equivocal.
Despite intense efforts to develop cannabinoid analgesics, there has been little success
in devising a CB1 receptor agonist that is devoid of behavioral effects. For example,
Noyes et al. (78) found that oral THC was as efficacious as codeine in producing
analgesia in a patient population, but its behavioral side effects precluded the use of
higher doses. As for synthetic cannabinoid derivatives that might be useful as analgesics,
nabitan is one such analog that was evaluated in at least two studies. Jochimsen et
al. (79) failed to observe pain relief in cancer patients, and there was some evidence
for increased pain sensitivity. On the other hand, another research group (13) reported
analgesia comparable to that of codeine in cancer patients. Levonantradol, another
cannabinoid derivative, elicited some benefit for postoperative surgical pain but only
at doses that produced significant behavioral disturbances (80). Several recent clinical
studies have found THC to lack sufficient efficacy in postoperative pain (81), neuropathic
pain (82), and refractory neuropathic pain (83). On the other hand, THC was
found to exert some benefit in treating intractable neuropathic pain in two adolescents
(84). A review of clinical studies regarding cannabinoid agonist treatment of cancer
pain led the author to conclude that the present studies do not justify the use of cannabinoid
agonists for pain management (85).
The evidence suggests that the CB1 receptor agonists that have been developed
thus far are unlikely to be highly efficacious in controlling high-intensity pain. However,
the possibility remains that they might be useful in more moderate pain, particularly
in case in which some of the typical cannabinoid side effects (sedation, dizziness,
etc.) might be more tolerated. Theoretically, CB1 receptor agonists should be effective
as adjuvants to other analgesics. Numerous preclinical studies have shown that THC
will enhance opioid analgesia. However, in a recent study in human experimental pain
models, THC offered relatively small additive analgesic effects when combined with
morphine (86). It remains to be determined whether similar results would occur in
pain patients.
There are several possible explanations for the discrepancy between the analgesic
effects of CB1 receptor agonists in laboratory animals and humans. Certainly, higher
doses can be administered to laboratory animals, and hence greater analgesic effects
achieved, than in humans. Pharmacokinetics may also play a very important part. The
studies that have been carried out thus far have relied on oral administration of THC,
a route that does not allow for easy optimization of treatment. Efforts are underway to
develop alternative formulations of THC to allow for other routes of administration.
132 Martin
Rectal suppositories of THC hemisuccinate have been found to be effective in treating
spasticity and pain (87). A water-soluble analog of THC has been developed that may
be appropriate for intravenous use (88). There have been recent studies demonstrating
that topical administration of cannabinoids produce analgesic effects (89). Moreover,
topical administration produced a synergistic interaction with spinally administered
cannabinoids. A separate group of investigators reported an analgesic interaction
between topical opioids and cannabinoids administered either topically or spinally
(90). These observations reinforce the notion that treatment regimens of opioid and
cannabinoids combinations have yet to be optimized clinically. Unfortunately, a topical
preparation of THC or related cannabinoid is not yet available for clinical use. Another
attractive approach is the inhalation route. An inhalation formulation of THC was developed
years ago, but unfortunately it produced bronchial irritation (91). The recent develop
of a THC aerosol delivered through a metered-dose inhaler holds promise (92).
The discussion so far has been devoted to nonselective CB1 and CB2 agonists,
such as THC, because most of the analgesic literature has been generated with these
compounds. The discovery of the CB2 receptor in nonneuronal tissues such as immune
cells attracted interest in its potential modulation of immune function. However, there
are now numerous reports that CB2 selective agonists have analgesic properties. One
such CB2 selective agonist is AM 1241, which was shown to be highly active in a
thermal pain model in rats (93). It was also shown to suppress capsaicin-induced
hyperalgesia (94). HU 308 is another CB2 selective agonist that has been reported to
produce analgesic effects in rodents (95). The advantage of these compounds is that
they are devoid of the behavioral effects produced by CB1 selective agonists. At present
there are no reports of clinical efficacy of CB2 selective agonists.
6. DRUG DEPENDENCE
Marijuana dependence has long been a controversial issue, in part as a result of
the lack of understanding of drug dependence. It is clear that a major physical withdrawal
syndrome does not occur upon abrupt cessation of marijuana use. Certainly,
dependence on many substances occurs without a prominent physical aspect of the
syndrome. What is clear is that continual use of marijuana can lead to dependence as
defined by the Diagnostic and Statistical Manual of Mental Disorders, 4th ed. criteria,
or essentially the inability to the user to exert control over their use. In actual fact,
an abrupt cannabinoid withdrawal syndrome was described in humans following discontinuation
of a rather rigorous treatment regimen of THC (96,97). Studies in more
recent times have used treatment regimens that more closely reflect typical marijuana
use patterns and have also demonstrated an abstinence symptom that included subjective
effects of anxiety, irritability, and stomach pain, as well as decreases in food
intake, following abrupt withdrawal from continued administration of either oral THC
(98) or marijuana smoke inhalation (99). There have been several efforts to devise
strategies for treating marijuana dependence. Haney et al. (100) found that bupropion
worsened mood during marijuana withdrawal. The antidepressant nefazodone provided
partial relief (101). They also demonstrated that oral THC decreased marijuana
craving and withdrawal signs during abstinence (102).
Therapeutic Potential of Cannabinoids 133
Demonstrating a well-defined abstinence withdrawal syndrome following prolonged
cannabinoid administration in laboratory animals also presented challenges.
Several unconditional behavioral effects, including hyperirritability, tremors, and anorexia,
were reported to occur during THC abstinence (103), while other studies failed
to observe abrupt withdrawal effects following chronic THC administration in dogs
(104) or rats (105,106). Abrupt withdrawal from chronic THC has been reported in
rhesus monkeys (107). The fact that readministration of THC reversed the withdrawal
effects suggested that the animals were cannabinoid-dependent. The development of
rimonabant (70), a selective CB1 receptor cannabinoid antagonist, represented the first
opportunity to determine whether a physical withdrawal syndrome could be precipitated
with an antagonist challenge. Antagonist-precipitated withdrawal is much easier
and more reliable to quantitate than withdrawal following abrupt cessation of the dependence-
producing drug. Indeed, a robust withdrawal syndrome was observed in THCtreated
rats that were challenged with rimonabant (108,109). Subsequent studies verified
precipitated withdrawal in both mice (110) and dogs (111). Another contribution of
rimonabant was that it enabled investigators to carefully document the symptoms of
withdrawal as well as the time course, both of which are critical for assessing abrupt
withdrawal. Subsequently, Aceto et al. (112) were able to document abrupt withdrawal
following cessation of infusion with the synthetic CB1 receptor agonist WIN 55,212.
Although it was important to demonstrate that abrupt and precipitated withdrawal
can be documented, most dependence-producing agents will also be self-administered
by laboratory animals. Unfortunately, THC is not readily self-administered by animals.
There was an early report that rats would self-administer THC (113). However,
it has not been an easy task to get rats to self-administer cannabinoids (114). It has
now been shown that THC can be reliably self-administered in squirrel monkeys
(115,116).
There is now increasing knowledge that the endocannabinoid system participates
in dependence on drugs other than THC. There has always been considerable interest
in the interactions of cannabinoids and opioids as it relates to dependence. Naloxone
has been reported to precipitate withdrawal effects in rats treated chronically with
THC (117,118). Conversely, naloxone was ineffective in precipitating withdrawal in
THC-dependent monkeys (107), pigeons (104), or mice (119). It has long been known
that THC produces a moderate attenuation of naloxone-precipitated withdrawal in
morphine-dependent mice (120,121) and rats (122,123). The endogenous cannabinoids
anandamide (124) and 2-arachidonoylglycerol (125) have both been reported to decrease
naloxone-induced morphine withdrawal.
Actually, the availability of mice lacking either μ-opioid or CB1 receptors has
greatly advanced our understanding of the interrelationship between the opioid and
endocannabinoid systems. CB1
receptor knockout mice exhibited substantial decreases
in both morphine self-administration and naloxone-precipitated morphine withdrawal
(126). In addition, rimonabant reduced the rewarding responses of morphine in the
conditioned place preference paradigm (127). Co-administration of rimonabant and
morphine led to decreases in naloxone-precipitated wet dog shakes and jumping but
had no effects on other indices of opioid withdrawal, including paw tremors, ptosis,
sniffing, and body tremors (127). Repeated administration of rimonabant in rats
134 Martin
implanted with morphine pellets reduced some, but not all, naloxone precipitated withdrawal
effects (128).
The converse also appears to be true, in that opioid receptors may play a modulatory
role on cannabinoid dependence. Rimonabant-precipitated THC withdrawal
symptoms were significantly diminished in pre-proenkephalin-deficient mice compared
to the wild-type mice (129). Similarly, mice lacking the μ-opioid receptor
exhibited significant attenuation of rimonabant-precipitated withdrawal signs compared
with the wild-type controls. These findings implicate a role for opioid system in
the modulation of cannabinoid dependence.
The finding that modulation of the endocannabinoid system is capable of influencing
opioid dependence—and vice versa—raises the possibility that the CB1 receptor
antagonist might influence opioid dependence. Indeed, Navarro et al. (130) found
that rimonabant was capable of blocking heroin self-administration in rats. Several
other laboratories evaluated CB1 receptor agonists and antagonists for their ability to
influence reinstatement of heroin self-administration (131,132). They found that several
CB1 receptor agonists restored heroin-seeking behavior, whereas rimonabant prevented
reinstatement.
The question arises as to whether the endocannabinoid system is involved in
dependence to drugs other than opioids. De Vries et al. (133) reported that the potent
CB1 receptor agonist HU210 provoked relapse to cocaine seeking after prolonged withdrawal
periods. In addition, rimonabant attenuated relapse induced by re-exposure to
cocaine-associated cues or cocaine itself, but not relapse induced by exposure to stress.
On the other hand, another laboratory reported that a CB1 receptor agonist attenuated
the effects of cocaine on brain self-stimulation thresholds, whereas rimonabant did
not alter cocaine’s effects (134). These findings suggest that the endocannabinoid system
plays a greater role in relapse to cocaine use than in maintaining cocaine selfadministration.
Another drug that is frequently used in conjunction with marijuana is alcohol.
There are several indications that the endocannabinoid system may influence alcohol
intake. It has been shown that rimonabant will decrease alcohol self-administration in
laboratory animals (135) and that alcohol preference is reduced by rimonabant (136).
Also, alcohol withdrawal symptoms are absent in CB1 receptor knockout mice, which
provides further support for a role of the endocannabinoid system in alcohol dependence.
Rimonabant has also been evaluated for its potential effects on the motivational
effects of nicotine in the rat (137). Rimonabant decreased nicotine
self-administration but did not substitute for nicotine nor antagonize the nicotine cue
in a nicotine-discrimination procedure. It also blocked nicotine-induced dopamine
release in the shell of the nucleus accumbens and the bed nucleus of the stria terminalis
(137). Dopamine release induced by ethanol in the nucleus accumbens was also reduced
by rimonabant.
The fact that the endocannabinoid system is an active participant in the dependence
on a wide range of drugs argues that it may play a fundamental role in the
perturbation of reward pathways that underlie drug dependence. These results suggest
that activation of the endogenous cannabinoid system may participate in the motivational
and dopamine-releasing effects of nicotine and ethanol as well as possibly other
Therapeutic Potential of Cannabinoids 135
drugs of abuse. Thus, CB1 receptor antagonists may be effective in treating drug
dependence induced by opioids, psychomotor stimulants, nicotine, and ethanol, in
addition to marijuana.
7. SUMMARY
Because the endocannabinoid system represents an important target for addressing
symptoms arising from numerous disease states, the ability to manipulate this
system becomes of paramount importance. At present, the only means of activating
the endocannabinoid system is with CB1 and CB2 receptor agonists. The disadvantage
of CB1 receptor agonists is that they have a broad pharmacological spectrum of action
that limits their clinical utility. Attempts to develop CB1 receptor agonists that have
improved the therapeutic-to-adverse effect ratio have met with limited success. However,
the new evidence that is emerging regarding the multiple signaling pathways
activated by the CB1 receptor provides encouragement that development of agonists
with improved pharmacological profile is possible. Moreover, structure–activity relationship
studies continually provide new chemical templates for agents that activate
the CB1 receptor. In the near term, the most likely success will come from new formulations
of current CB1 receptor agonists that are already approved for clinical use.
As for selective CB2 receptor agonists, there is intense interest in these compounds
as potential therapeutic agents because they will be devoid of the behavioral
effects that currently plague the CB1 receptor agonists. The fact that selective CB2
receptor agonists have been found to be effective in some animal models of pain provides
an exciting possibility for development of new analgesics.
Efforts are also underway to develop inhibitors of the enzymes that degrade
anandamide. Indeed, deletion of this enzyme in mice through genetic engineering resulted
in elevated anandamide levels and increased resistance to pain (39). Highly
potent inhibitors of this enzyme have also been synthesized (138). By elevating
anandamide levels, these inhibitors represent an entirely new strategy for activating
the endocannabinoid system. Elevation of 2-arachidonoylglycerol levels could occur
through the blockade of monoglyceride lipase, the enzyme that metabolizes this
endocannabinoid (41). There are at present no selective inhibitors of this enzyme.
It is also abundantly clear that attenuating the endocannabinoid system has important
therapeutic uses. The CB1 receptor antagonist rimonabant has been shown to
be effective in both animal models and clinical trials for treatment of decreased appetite
and increased weight loss. Moreover, it has been shown to alter alcohol, cocaine,
heroin, and nicotine dependence. Another potential means of attenuating the
endocannabinoid system is through inhibition of the synthesis of anandamide and 2-
arachidonolyglycerol. Although these enzymes have been identified, there are at present
no inhibitors shown to have potential as therapeutic agents in, for example, obesity or
drug dependence.
REFERENCES
1. Mechoulam, R. and Hanus, L. (2000) A historical overview of chemical research on cannabinoids.
Chem. Phys. Lipids 108, 1–13.
136 Martin
2. Grinspoon, L. and Bakalar, J. B. (1993) Marihuana: The Forbidden Medicine. (eds.),
Yale University Press, New Haven, CT, p. 184.
3. Gaoni, Y. and Mechoulam, R. (1964) Hashish. III. Isolation, structure, and partial synthesis
of an active constituent of hashish. J. Am. Chem. Soc. 86, 1646–1647.
4. Noyes, R. Jr., Brunk, S. F., Baram, D. A., and Canter, A. (1975) Analgesic effect of delta-
9-tetrahydrocannabinol. J. Clin. Pharmacol. 15, 139–143.
5. Sallan, S. E., Zinberg, N. E., and Frei, E., 3rd (1975) Antiemetic effect of delta-9-tetrahydrocannabinol
in patients receiving cancer chemotherapy. N. Engl. J. Med. 293, 795–797.
6. Noyes, R. Jr., Brunks, S. F., Avery, D. H., and Canter, A. (1976) Psychologic effects of
oral delta-9-tetrahydrocannabinol in advanced cancer patients. Comp. Psychiatry 17, 641–
646.
7. Regelson, W., Bulter, J. R., Schulz, J., et al. (1976) Δ9-Tetrahydrocannabinol as an effective
antidepressant and appetite-stimulating agent in advanced cancer patients, in The
Pharmacology of Marihuana (Braude, M. C. and Szara, S., eds.), Raven Press, New York,
pp. 763–776.
8. Green, K., Kim, K., and Bowman, K. (1976) Ocular effects of Δ9-tetrahydrocannabinol,
in The Therapeutic Potential of Marihuana (Cohen, S. and Stillman, R., eds.), Plenum
Medical Book, New York, pp. 49–62.
9. Fabre, L. F., McLendon, D. M., and Stark, P. (1978) Nabilone, a cannabinoid, in the
treatment of anxiety: an open-label and double-blind study. Curr. Ther. Res. 24, 161–
169.
10. Cunningham, D., Bradley, C. J., Forrest, G. J., et al. (1988) A randomized trial of oral
nabilone and prochlorperazine compared to intravenous metoclopramide and dexamethasone
in the treatment of nausea and vomiting induced by chemotherapy regimens containing
cisplatin or cisplatin analogues. Eur. J. Cancer Clin. Oncol. 24, 685–689.
11. Cronin, C. M., Sallan, S. E., Gelber, R., Lucas, V. S., and Lazlo, J. (1981) Antiemetic
effect of intramuscular levonantradol in patients receiving anticancer chemotherapy. J.
Clin. Pharmacol. 21, 43S–50S.
12. Koe, B. K. (1981) Levonantradol, a potent cannabinoid-related analgesic, antagonizes
haloperidol-induced activation of striatal dopamine synthesis. Eur. J. Pharmacol. 70,
231–235.
13. Staquet, M., Gantt, C., and Machin, D. (1978) Effect of a nitrogen analog of tetrahydrocannabinol
on cancer pain. Clin. Pharmacol. Ther. 23, 397–401.
14. Razdan, R. K. (1986) Structure-activity relationships in cannabinoids. Pharmacol. Rev.
38, 75–149.
15. Harris, L. S., Carchman, R. A., and Martin, B. R. (1978) Evidence for the existence of
specific cannabinoid binding sites. Life Sci. 22, 1131–1137.
16. Devane, W. A., Dysarz, F. A. III, Johnson, M. R., Melvin, L. S., and Howlett, A. C.
(1988) Determination and characterization of a cannabinoid receptor in rat brain. Mol.
Pharmacol. 34, 605–613.
17. Matsuda, L. A., Lolait S. J., Brownstein, M. J., Young, A. C., and Bonner, T. I. (1990)
Structure of a cannabinoid receptor and functional expression of the cloned cDNA. Nature
346, 561–564.
18. Compton, D. R., Johnson, M. R., Melvin, L.S., and Martin, B. R. (1992) Pharmacological
profile of a series of bicyclic cannabinoid analogs: classification as cannabimimetic
agents. J. Pharmacol. Exp. Ther. 260, 201–209.
19. Howlett, A. C., Barth, F., Bonner, T. I., et al. (2002) International Union of Pharmacology.
XXVII. Classification of cannabinoid receptors. Pharmacol. Rev. 54, 161–202.
20. Herkenham, M., Lynn, A. B., Johnson, M. R., Melvin, L. S., De Costa, B. R., and Rice,
K. C. (1991) Characterization and localization of cannabinoid receptors in rat brain: a
quantitative in vitro autoradiographic study. J. Neurosci. 11, 563–583.
Therapeutic Potential of Cannabinoids 137
21. Gardner, E. L. (2002) Addictive potential of cannabinoids: the underlying neurobiology.
Chem. Phys. Lipids 121, 267–290.
22. Gerdeman, G. and Lovinger, D. M. (2001) CB1 cannabinoid receptor inhibits synaptic
release of glutamate in rat dorsolateral striatum. J. Neurophysiol. 85, 468–471.
23. Hohmann, A. G. and Herkenham, M. (2000) Localization of cannabinoid CB(1) receptor
mRNA in neuronal subpopulations of rat striatum: a double-label in situ hybridization
study. Synapse 37, 71–80.
24. Herkenham, M., Lynn, A. B., De Costa, B. R., and Richfield, E. K. (1991) Neuronal
localization of cannabinoid receptors in the basal ganglia of the rat. Brain Res. 547, 267–
274.
25. Tsou, K., Brown, S., Sanudo-Pena, M. C., Mackie, K., and Walker, J. M. (1998) Immunohistochemical
distribution of cannabinoid CB1 receptors in the rat central nervous system.
Neuroscience 83, 393–411.
26. Munro, S., Thomas, K. L., and Abu-Shaar, M. (1993) Molecular characterization of a
peripheral receptor for cannabinoids. Nature 365, 61–65.
27. Galiegue, S., Mary, S., Marchand, J., et al. (1995) Expression of central and peripheral
cannabinoid receptors in human immune tissues and leukocyte subpopulations. Eur. J.
Biochem. 232, 54–61.
28. Carlisle, S. J., Marciano-Cabral, F., Staab, A., Ludwick, C., and Cabral, G. A. (2002)
Differential expression of the CB2 cannabinoid receptor by rodent macrophages and macrophage-
like cells in relation to cell activation. Int. Immunopharmacol. 2, 69–82.
29. Howlett, A. C. and Fleming, R. M. (1984) Cannabinoid inhibition of adenylate cyclase.
Pharmacology of the response in neuroblastoma cell membranes. Mol. Pharmacol. 26,
532–538.
30. Prather, P. L., Martin, N. A., Breivogel, C. S., and Childers, S. R. (2000) Activation of
cannabinoid receptors in rat brain by WIN 55212-2 produces coupling to multiple G
protein alpha-subunits with different potencies. Mol. Pharmacol. 57, 1000–1010.
31. Mackie, K. and Hille, B. (1992) Cannabinoids inhibit N-type calcium channels in
neurobalstoma-glioma cells. Proc. Natl. Acad. Sci. USA 89, 3825–3829.
32. Mackie, K., Lai, Y., Westenbroek, R., and Mitchell, R. (1995) Cannabinoids activate an
inwardly rectifying potassium conductance and inhibit Q-type calcium currents in AtT20
cells transfected with rat brain cannabinoid receptor. J. Neurosci. 15, 6552–6561.
33. Devane, W. A., Hanus, L., Breuer, A., et al. (1992) Isolation and structure of a brain
constituent that binds to the cannabinoid receptor. Science 258, 1946–1949.
34. Mechoulam, R., Ben-Shabat, S., Hanus, L., et al. (1995) Identification of an endogenous
2-monoglyceride, present in canine gut, that binds to cannabinoid receptors. Biochem.
Pharmacol. 50, 83–90.
35. Sugiura, T., Kondo, S., Sukagawa, A., et al. (1995) 2-Arachidonoyglycerol: a possible endogenous
cannabinoid receptor ligand in brain. Biochem. Biophys. Res. Comm. 215, 89–97.
36. Hanus, L., Abu-Lafi, S., Fride, E., et al. (2001) 2-Arachidonyl glyceryl ether, an endogenous
agonist of the cannabinoid CB1 receptor. Proc. Natl. Acad. Sci. USA 98, 3662–
3665.
37. Schmid, H. H. (2000) Pathways and mechanisms of N-acylethanolamine biosynthesis:
can anandamide be generated selectively? Chem. Phys. Lipids 108, 71–87.
38. Patricelli, M. P., Lashuel, H. A., Giang, D. K., Kelly, J. W., and Cravatt, B. F. (1998)
Comparative characterization of a wild type and transmembrane domain-deleted fatty
acid amide hydrolase: identification of the transmembrane domain as a site for oligomerization.
Biochemistry 37, 15177–15187.
39. Cravatt, B. F., Demarest, K., Patricelli, M. P., et al. (2001) Supersensitivity to anandamide
and enhanced endogenous cannabinoid signaling in mice lacking fatty acid amide hydrolase.
Proc. Natl. Acad. Sci. USA 98, 9371–9376.
138 Martin
40. Bisogno, T., Howell, F., Williams, G., et al. (2003) Cloning of the first sn1-DAG lipases
points to the spatial and temporal regulation of endocannabinoid signaling in the brain. J.
Cell. Biol. 163, 463–468.
41. Dinh, T. P., Carpenter, D., Leslie, F.M., et al. (2002) Brain monoglyceride lipase participating
in endocannabinoid inactivation. Proc. Natl. Acad. Sci. USA 99, 10819–10824.
42. Di Marzo, V., Goparaju, S. K., Wang, L., et al. (2001) Leptin-regulated endocannabinoids
are involved in maintaining food intake. Nature 410, 822–825.
43. Jamshidi, N. and Taylor, D. A. (2001) Anandamide administration into the ventromedial
hypothalamus stimulates appetite in rats. Br. J. Pharmacol. 134, 1151–1154.
44. Higgs, S., Williams, C. M., and Kirkham, T. C. (2003) Cannabinoid influences on palatability:
microstructural analysis of sucrose drinking after delta(9)-tetrahydrocannabinol,
anandamide, 2-arachidonoyl glycerol and SR141716. Psychopharmacology (Berl) 165,
370–377.
45. Kirkham, T. C., Williams, C. M., Fezza, F., and Di Marzo, V. (2002) Endocannabinoid
levels in rat limbic forebrain and hypothalamus in relation to fasting, feeding and satiation:
stimulation of eating by 2-arachidonoyl glycerol. Br. J. Pharmacol. 136, 550–557.
46. Harrold, J. A., Elliott, J. C., King, P. J., Widdowson, P. S., and Williams, G. (2002)
Down-regulation of cannabinoid-1 (CB-1) receptors in specific extrahypothalamic regions
of rats with dietary obesity: a role for endogenous cannabinoids in driving appetite
for palatable food? Brain Res. 952, 232–238.
47. Cota, D., Marsicano, G., Tschoep, M., et al. (2003) The endogenous cannabinoid system
affects energy balance via central orexigenic drive and peripheral lipogenesis. J. Clin.
Invest. 112, 423–431.
48. Bensaid, M., Gary-Bobo, M., Esclangon, A., et al. (2003) The cannabinoid CB1 receptor
antagonist SR141716 increases Acrp30 mRNA expression in adipose tissue of obese fa/
fa rats and in cultured adipocyte cells. Mol. Pharmacol. 63, 908–914.
49. Harrold, J. A. and Williams, G. (2003) The cannabinoid system: a role in both the homeostatic
and hedonic control of eating? Br. J. Nutr. 90, 729–734.
50. Hart, C. L., Ward, A. S., Haney, M., Comer, S. D., Foltin, R. W., and Fischman, M. W.
(2002) Comparison of smoked marijuana and oral delta(9)-tetrahydrocannabinol in humans.
Psychopharmacology (Berl) 164, 407–415.
51. Beal, J. E., Olson, R., Laubenstein, L., et al. (1995) Dronabinol as a treatment for anorexia
associated with weight loss in patients with AIDS. J. Pain Symptom Manage. 10, 89–97.
52. Sallan, S. E., Cronin, C., Zelen, M., and Zinberg, N. E. (1980) Antiemetics in patients
receiving chemotherapy for cancer - a randomized comparison of delta-9-tetrahydrocannabinol
and prochlorperazine. N. Engl. J. Med. 302, 135–138.
53. Plasse, T. F., Gorter, R. W., Krasnow, S. H., Lane, M., Shepard, K. V., and Wadleigh, R.
G. (1991) Recent clinical experience with dronabinol. Pharmacol. Biochem. Behav. 40,
695–700.
54. Jatoi, A., Windschitl, H. E., Loprinzi, C. L., et al. (2002) Dronabinol versus megestrol
acetate versus combination therapy for cancer-associated anorexia: a North Central Cancer
Treatment Group study. J. Clin. Oncol. 20, 567–573.
55. Nelson, K., Walsh, D., Deeter, P., and Sheehan, F. (1994) A phase II study of delta-9-
tetrahydrocannabinol for appetite stimulation in cancer-associated anorexia. J. Palliat.
Care 10, 14–18.
56. Darmani, N. A. (2001) Delta(9)-tetrahydrocannabinol and synthetic cannabinoids prevent
emesis produced by the cannabinoid CB(1) receptor antagonist/inverse agonist SR
141716A. Neuropsychopharmacology 24, 198–203.
57. Parker, L. A., Kwiatkowska, M., Burton, P., and Mechoulam, R. (2004) Effect of cannabinoids
on lithium-induced vomiting in the Suncus murinus (house musk shrew). Psychopharmacology
171, 156–161.
Therapeutic Potential of Cannabinoids 139
58. Kwiatkowska, M., Parker, L. A., Burton, P., and Mechoulam, R. (2004) A comparative
analysis of the potential of cannabinoids and ondansetron to suppress cisplatin-induced
emesis in the Suncus murinus (house musk shrew). Psychopharmacology (Berl) 174,
254–259.
59. Parker, L. A. and Kemp, S. W. (2001) Tetrahydrocannabinol (THC) interferes with conditioned
retching in Suncus murinus: an animal model of anticipatory nausea and vomiting
(ANV). Neuroreport 12, 749–751.
60. Parker, L. A., Mechoulam, R., Schlievert, C., Abbott, L., Fudge, M. L., and Burton, P.
(2003) Effects of cannabinoids on lithium-induced conditioned rejection reactions in a
rat model of nausea. Psychopharmacology (Berl) 166, 156–162.
61. Simoneau, I. I., Hamza, M. S., Mata, H. P., et al. (2001) The cannabinoid agonist
WIN55,212-2 suppresses opioid-induced emesis in ferrets. Anesthesiology 94, 882–
887.
62. Darmani, N. A., Sim-Selley, L. J., Martin, B. R., et al. (2003) Antiemetic and motordepressive
actions of CP55,940: cannabinoid CB1 receptor characterization, distribution,
and G-protein activation. Eur. J. Pharmacol. 459, 83–95.
63. McCabe, M., Smith, F. P., Macdonald, J. S., Woolley, P. V., Goldberg, D., and Schein, P.
S. (1988) Efficacy of tetrahydrocannabinol in patients refractory to standard antiemetic
therapy. Invest. New Drugs 6, 243–246.
64. Lane, M., Vogel, C. L., Ferguson, J., et al. (1991) Dronabinol and prochlorperazine in
combination for treatment of cancer chemotherapy-induced nausea and vomiting. J. Pain
Symptom Manage. 6, 352–359.
65. Ahmedzai, S., Carlyle, D. L., Calder, I. T., and Moran, F. (1983) Anti-emetic efficacy
and toxicity of nabilone, a synthetic cannabinoid, in lung cancer chemotherapy. Br. J.
Cancer. 48, 657–663.
66. Abrahamov, A., Abrahamov, A., and Mechoulam, R. (1995) An efficient new cannabinoid
antiemetic in pediatric oncology. Life Sci. 56, 2097–2102.
67. Chan, H. S., Correia, J. A., and MacLeod, S. M. (1987) Nabilone versus prochlorperazine
for control of cancer chemotherapy-induced emesis in children: a double-blind, crossover
trial. Pediatrics 79, 946–952.
68. Martin, B. R. and Lichtman, A. H. (1998) Cannabinoid transmission and pain perception.
Neurobiol. Dis. 5, 447–461.
69. Compton, D. R., Rice, K. C., De Costa, B. R., Razdan, R. K., and Melvin, L. S. (1993)
Cannabinoid structure-activity relationships: Correlation of receptor binding and in vivo
activities. J. Pharmacol. Exp. Ther. 265, 218–226.
70. Rinaldi-Carmona, M., Barth, F., Heaulme, M., et al. (1994) SR141716A, a potent and
selective antagonist of the brain cannabinoid receptor. FEBS Lett. 350, 240–244.
71. Compton, D. R., Aceto, M. D., Lowe, J., and Martin, B. R. (1996) In vivo characterization
of a specific cannabinoid receptor antagonist (SR141716A): Inhibition of delta-9-
tetrahydrocannabinol-induced responses and apparent agonist activity. J. Pharmacol.
Exp. Ther. 277, 586–594.
72. Smith, P. B., Compton, D. R., Welch, S. P., Razdan, R. K., Mechoulam, R., and Martin,
B. R. (1994) The pharmacological activity of anandamide, a putative endogenous cannabinoid,
in mice. J. Pharmacol. Exp. Ther. 270, 219–227.
73. Walker, J. M., Krey, J. F., Chu, C. J., and Huang, S. M. (2002) Endocannabinoids and
related fatty acid derivatives in pain modulation. Chem. Phys. Lipids 121, 159–172.
74. Walker, J. M., Strangman, N. M., and Huang, S. M. (2001) Cannabinoids and pain. Pain
Res. Manag. 6, 74–79.
75. Hohmann, A. G. and Herkenham, M. (1999) Localization of central cannabinoid CB1
receptor messenger RNA in neuronal subpopulations of rat dorsal root ganglia: a doublelabel
in situ hybridization study. Neurosci. 90, 923–931.
140 Martin
76. Welch, S. P. and Stevens, D. L. (1992) Antinociceptive activity of intrathecally administered
cannabinoids alone, and in combination with morphine, in mice. J. Pharmacol.
Exp. Ther. 262, 10–18.
77. Houser, S. J., Eads, M., Embrey, J. P., and Welch, S. P. (2000) Dynorphin B and spinal
analgesia: induction of antinociception by the cannabinoids CP55,940, delta(9)-THC and
anandamide. Brain Res. 857, 337–342.
78. Noyes, R. Jr., Brunk, S. F., Avery, D. A., and Canter, A. C. (1975) The analgesic properties
of delta-9-tetrahydrocannabinol and codeine. Clin. Pharmacol. Ther. 18, 84–89.
79. Jochimsen, P. R., Lawton, R. L., VerSteeg, K., and Noyes, R. Jr. (1978) Effect of
benzopyranoperidine, a Δ9-THC congener, on pain. Clin. Pharmacol. Ther. 24, 223–227.
80. Jain, A. K., Ryan, J. R., McMahon, F. G., and Smith, G. (1981) Evaluation of intramuscular
levonantradol and placebo in acute post-operative pain. J. Clin. Pharmacol. 21,
3205–3265.
81. Buggy, D. J., Toogood, L., Maric, S., Sharpe, P., Lambert, D. G., and Rowbotham, D. J.
(2003) Lack of analgesic efficacy of oral delta-9-tetrahydrocannabinol in postoperative
pain. Pain 106, 169–172.
82. Attal, N., Brasseur, L., Guirimand, D., Clermond-Gnamien, S., Atlami, S., and
Bouhassira, D. (2004) Are oral cannabinoids safe and effective in refractory neuropathic
pain? Eur. J. Pain 8, 173–177.
83. Clermont-Gnamien, S., Atlani, S., Attal, N., Le Mercier, F., Guirimand, F., and Brasseur,
L. (2002) The therapeutic use of Δ9-tetrahydrocannabinol (dronabinol) in refractory neuropathic
pain. Presse Med. 31, 1840–1845.
84. Rudich, Z., Stinson, J., Jeavons, M., and Brown, S.C. (2003) Treatment of chronic intractable
neuropathic pain with dronabinol: case report of two adolescents. Pain Res. Manag.
8, 221–224.
85. Campbell, F. A., Tramer, M. R., Carroll, D., et al. (2001) Are cannabinoids an effective
and safe treatment option in the management of pain? A qualitative systematic review.
BMJ 323, 13–16.
86. Naef, M., Curatolo, M., Petersen-Felix, S., Arendt-Nielsen, L., Zbinden, A., and
Brenneisen, R. (2003) The analgesic effect of oral delta-9-tetrahydrocannabinol (THC),
morphine, and a THC-morphine combination in healthy subjects under experimental pain
conditions. Pain 105, 79–88.
87. Brenneisen, R., Egli, A., ElSohly, M. A., Henn, V., and Spiess, Y. (1996) The effect of
orally and rectally administered delta 9-tetrahydrocannabinol on spasticity: a pilot study
with 2 patients. Int. J. Clin. Pharmacol. Ther. 34, 446–452.
88. Pertwee, R. G., Gibson, T. M., Stevenson, L. A., et al. (2000) O-1057, a potent watersoluble
cannabinoid receptor agonist with antinociceptive properties. Br. J. Pharmacol.
129, 1577–1584.
89. Dogrul, A., Gul, H., Akar, A., Yildiz, O., Bilgin, F., and Guzeldemir, E. (2003) Topical
cannabinoid antinociception: synergy with spinal sites. Pain 105, 11–16.
90. Yesilyurt, O., Dogrul, A., Gul, H., et al. (2003) Topical cannabinoid enhances topical
morphine antinociception. Pain 105, 303–308.
91. Olsen, J. L., Lodge, J. W., Shapiro, B. J., and Tashkin, D. P. (1976) An inhalation aerosol
of delta-9-Tetrahydrocannabinol. J. Pharm. Pharmacol. 28, 86–86.
92. Wilson, D. M., Peart, J., Martin, B. R., Bridgen, D. T., Byron, P. R., and Lichtman, A. H.
(2002) Physiochemical and pharmacological characterization of a delta(9)-THC aerosol
generated by a metered dose inhaler. Drug Alcohol Depend. 67, 259–267.
93. Malan, T. P. Jr., Ibrahim, M. M., Deng, H., et al. (2001) CB2 cannabinoid receptormediated
peripheral antinociception. Pain 93, 239–245.
94. Hohmann, A. G., Farthing, J. N., Zvonok, A. M., and Makriyannis, A. (2004) Selective
activation of cannabinoid CB2 receptors suppresses hyperalgesia evoked by intradermal
capsaicin. J. Pharmacol. Exp. Ther. 308, 446–453.
Therapeutic Potential of Cannabinoids 141
95. Hanus, L., Breuer, A., Tchilibon, S., et al. (1999) HU-308: a specific agonist for CB(2), a
peripheral cannabinoid receptor. Proc. Natl. Acad. Sci. USA 96, 14228–14233.
96. Jones, R. T., Benowitz, N., and Bachman, J. (1976) Clinical studies of cannabis tolerance
and dependence. Ann. NY Acad. Sci. 282, 221–239.
97. Jones, R. T. and Benowitz, N. (1976) The 30-day trip—clinical studies of cannabis tolerance
and dependence, in Pharmacology of Marihuana (Braude, M. C. and Szara, S., eds.),
Raven Press, New York, pp. 627–642.
98. Haney, M., Ward, A. S., Comer, S. D., Foltin, R. W., and Fischman, M. W. (1999) Abstinence
symptoms following oral THC administration to humans. Psychopharmacology
(Berl) 141, 385–394.
99. Haney, M., Ward, A. S., Comer, S. D., Foltin, R. W., and Fischman, M. W. (1999) Abstinence
symptoms following smoked marijuana in humans. Psychopharmacology (Berl)
141, 395–404.
100. Haney, M., Ward, A. S., Comer, S. D., Hart, C. L., Foltin, R. W., and Fischman, M. W.
(2001) Bupropion SR worsens mood during marijuana withdrawal in humans. Psychopharmacology
(Berl) 155, 171–179.
101. Haney, M., Hart, C. L., Ward, A. S., and Foltin, R. W. (2003) Nefazodone decreases anxiety
during marijuana withdrawal in humans. Psychopharmacology (Berl) 165, 157–165.
102. Haney, M., Hart, C. L., Vosburg, S. K., et al. (2004) Marijuana withdrawal in humans:
effects of oral THC or divalproex. Neuropsychopharmacology 29, 158–170.
103. Kaymakcalan, S. and Deneau, G. A. (1972) Some pharmacologic properties of synthetic
Δ9-tetrahydrocannabinol. Acta Med. Turc. Suppl. 1, 27.
104. McMillan, D. E., Dewey, W. L., and Harris, L. S. (1971) Characteristics of tetrahydrocannabinol
tolerance. Ann. NY Acad. Sci. 191, 83–99.
105. Leite, J. R. and Carlini, E. A. (1974) Failure to obtain “cannabis-directed behavior” and
abstinence syndrome in rats chronically treated with cannabis sativa extracts.
Psychopharmacologia 36, 133–145.
106. Aceto, M.D., Scates, S.M., Lowe, J.A., and Martin, B.R. (1996) Dependence on Δ9-tetrahydrocannabinol:
studies on precipitated and abrupt withdrawal. J. Pharmacol. Exp. Ther. 278, 1290–1295.
107. Beardsley, P. M., Balster, R. L., and Harris, L. S. (1986) Dependence on tetrahydrocannabinol
in rhesus monkeys. J. Pharmacol. Exp. Ther. 239, 311–319.
108. Tsou, K., Patrick, S. L., and Walker, J. M. (1995) Physical withdrawal in rats tolerant to
delta-9-tetrahydrocannabinol precipitated by a cannabinoid receptor antagonist. Eur. J.
Pharmacol. 280, R13–R15.
109. Aceto, M. D., Scates, S. M., Lowe, J. A., and Martin, B. R. (1995) Cannabinoid precipitated
withdrawal by the selective cannabinoid receptor antagonist, SR 141716A. Eur. J.
Pharmacol. 282, R3–R4.
110. Cook, S. A., Lowe, J. A., and Martin, B. R. (1998) CB1 receptor antagonist precipitates
withdrawal in mice exposed to Δ9-tetrahydrocannabinol. J. Pharmacol. Exp. Ther. 285,
1150–1156.
111. Lichtman, A. H., Wiley, J. L., LaVecchia, K. L., et al. (1998) Effects of SR141716A after
acute or chronic cannabinoid administration in dogs. Eur. J. Pharmacol. 357, 139–148.
112. Aceto, M. D., Scates, S. M., and Martin, B. R. (2001) Spontaneous and precipitated withdrawal
with a synthetic cannabinoid, WIN 55212-2. Eur. J. Pharmacol. 416, 75–81.
113. Takahashi, R. N. and Singer, G. (1979) Self-administration of Δ9-tetrahydrocannabinol
by rats. Pharmacol. Biochem. Behav. 11, 737–740.
114. Mansbach, R. S., Nicholson, K. L., Martin, B. R., and Balster, R. L. (1994) Failure of
delta-9-tetrahydrocannabinol and CP 55,940 to maintain intravenous self-administration
under a fixed-interval schedule in rhesus monkeys. Behav. Pharmacol. 5, 219–225.
115. Tanda, G., Munzar, P., and Goldberg, S. R. (2000) Self-administration behavior is maintained
by the psychoactive ingredient of marijuana in squirrel monkeys. Nature Neurosci.
3, 1073–1074.
142 Martin
116. Justinova, Z., Tanda, G., Redhi, G. H., and Goldberg, S. R. (2003) Self-administration of
delta-9-tetrahydrocannabinol (THC) by drug naive squirrel monkeys. Psychopharmacology
(Berl) 169, 135–140.
117. Kaymakcalan, S., Ayhan, I. H., and Tulunay, F. C. (1977) Naloxone-induced or
postwithdrawal abstinence signs in delta-9-tetrahydrocannabinol-tolerant rats. Psychopharmacology
55, 243–249.
118. Hirschhorn, I. D. and Rosecrans, J. A. (1974) Morphine and delta-9-tetrahydrocannabinol:
Tolerance to the stimulus effects. Psychopharmacology 36, 243–253.
119. Lichtman, A. H., Sheikh, S. M., Loh, H. H., and Martin, B. R. (2001) Opioid and cannabinoid
modulation of precipitated withdrawal in Δ(9)-tetrahydrocannabinol and morphinedependent
mice. J. Pharmacol. Exp. Ther. 298, 1007–1014.
120. Bhargava, H. N. (1976) Effect of some cannabinoids on naloxone-precipitated abstinence
in morphine-dependent mice. Psychopharmacology 49, 267–270.
121. Bhargava, H. N. (1978) Time course of the effects of naturally occurring cannabinoids on
morphine abstinence syndrome. Pharmacol. Biochem. Behav. 8, 7–11.
122. Frederickson, R. C. A., Hewes, C. R., and Aiken, J. W. (1976) Correlation between the in
vivo and an in vitro expression of opiate withdrawal precipitated by naloxone: their antagonism
by l-(-)-Δ9-tetrahydrocannabinol. J. Pharmacol. Exp. Ther. 199, 375–384.
123. Hine, B., Friedman, E., Torrelio, M., and Gershon, S. (1975) Morphine-dependent rats:
blockade of precipitated abstinence by tetrahydrocannabinol. Science 187, 443–445.
124. Vela, G., Ruiz-Gayo, M., and Fuentes, J.A. (1995) Anandamide decreases naloxone-precipitated
withdrawal signs in mice chronically treated with morphine. Neuropharmacology
34, 665–668.
125. Yamaguchi, T., Hagiwara, Y., Tanaka, H., et al. (2001) Endogenous cannabinoid, 2-
arachidonoylglycerol, attenuates naloxone-precipitated withdrawal signs in morphinedependent
mice. Brain Res. 909, 121–126.
126. Ledent, C., Valverdej, O., Cossu, G., et al. (1999) Unresponsiveness to cannabinoids and
reduced addictive effects of opiates in CB1 receptor knockout mice. Science 283, 401–
404.
127. Mas-Nieto, M., Pommier, B., Tzavara, E. T., et al. (2001) Reduction of opioid dependence
by the CB(1) antagonist SR141716A in mice: evaluation of the interest in pharmacotherapy
of opioid addiction. Br. J. Pharmacol. 132, 1809–1816.
128. Rubino, T., Massi, P., Vigano, D., Fuzio, D., and Parolaro, D. (2000) Long-term treatment
with SR141716A, the CB1 receptor antagonist, influences morphine withdrawal
syndrome. Life Sci. 66, 2213–2219.
129. Valverde, O., Maldonado, R., Valjent, E., Zimmer, A. M., and Zimmer, A. (2000) Cannabinoid
withdrawal syndrome is reduced in pre-proenkephalin knock-out mice. J.
Neurosci. 20, 9284–9289.
130. Navarro, M., Carrera, M. R. A., Fratta, W., et al. (2001) Functional interaction between
opioid and cannabinoid receptors in drug self-administration. J. Neurosci. 21, 5344–5350.
131. Fattore, L., Spano, M. S., Cossu, G., Deiana, S., and Fratta, W. (2003) Cannabinoid
mechanism in reinstatement of heroin-seeking after a long period of abstinence in rats.
Eur. J. Neurosci. 17, 1723–1726.
132. De Vries, T. J., Homberg, J. R., Binnekade, R., Raaso, H., and Schoffelmeer, A. N. M.
(2003) Cannabinoid modulation of the reinforcing and motivational properties of heroin
and heroin-associated cues in rats. Psychopharmacology (Berl) 168, 164–169.
133. De Vries, T. J., Shaham, Y., Homberg, J. R., et al. (2001) A cannabinoid mechanism in
relapse to cocaine seeking. Nat. Med. 7, 1151–1154.
134. Vlachou, S., Nomikos, G. G., and Panagis, G. (2003) WIN 55,212-2 decreases the reinforcing
actions of cocaine through CB1 cannabinoid receptor stimulation. Behav. Brain
Res. 141, 215–222.
Therapeutic Potential of Cannabinoids 143
135. Freedland, C. S., Sharpe, A. L., Samson, H. H., and Porrino, L. J. (2001) Effects of
SR141716A on ethanol and sucrose self-administration. Alcohol Clin. Exp. Res. 25, 277–
282.
136. Wang, L., Lui, J., Harvey-White, J., Zimmer, A., and Kunos, G. (2003) Endocannabinoid
signaling via cannabinoid receptor 1 is involved in ethanol preference and its age-dependent
decline in mice. Proc. Natl. Acad. Sci. USA 100, 1393–1398.
137. Cohen, C., Perrault, G., Voltz, C., Steinberg, R., and Soubrie, P. (2002) SR141716, a
central cannabinoid (CB1) receptor antagonist, blocks the motivational and dopaminereleasing
effects of nicotine in rats. Behav. Pharmacol. 13, 451–463.
138. Boger, D. L., Sato, H., Lerner, A. E., et al. (2000) Exceptionally potent inhibitors of fatty
acid amide hydrolase: the enzyme responsible for degradation of endogenous oleamide
and anandamide. Proc. Natl. Acad. Sci. USA 97, 5044–5049.
144 Martin
Immunoassays to Detect Cannabis Abuse 145
From: Forensic Science and Medicine: Marijuana and the Cannabinoids
Edited by: M. A. ElSohly © Humana Press Inc., Totowa, New Jersey
145
Chapter 7
Immunoassays for the Detection
of Cannabis Abuse
Technologies, Development Strategies,
and Multilevel Applications
Jane S-C. Tsai
1. INTRODUCTION
The power of molecular recognition and effective interaction of specific binding
partners have been exploited to develop assay technologies for diverse biochemical
analysis. The unique features of immunoglobulins and technological advancement in
antibody engineering and manipulation have made antibodies the most versatile binding
reagents for detecting analytes of interest in a variety of matrices. The term immunoassay
is customarily used to denote antibody-mediated analytical procedures; however,
there are assortments of nomenclature for various immunoassay techniques that usually
are named after the reaction principle of the particular immunoassay format.
A number of immunoassay technologies have been applied to the development
of assays for small molecules such as drug compounds and their metabolites. To date,
these immunoassays have been widely utilized as cost-effective initial tests to efficiently
screen out the negative specimens from further analysis in the two-stage drugsof-
abuse testing (DAT) programs. Subsequently, the non-negative or presumptive positive
specimens are subjected to confirmatory testing with an alternative chemical principle
such as gas (or liquid) chromatography/mass spectrometry (GC/MS or LC/MS).
Proper utilization of DAT technologies requires familiarity with the characteristics
of the analytical methodologies employed. Each of the abused drugs has specific
146 Tsai
requirements and challenges for immunoassay performance. Among the more prominent
challenges for a DAT immunoassay is the ability to react with a desired panel of
structurally related compounds with ideal levels of affinity while excluding the reaction
with other similarly related structures. In certain cases, the desirable cross-reactivity
characteristics may vary depending on the market segments, regulatory
implications, and the goals of the DAT programs. Additionally, each of the biological
sample matrices has unique requirements and challenges for developing a suitable
DAT immunoassay. Good knowledge of the chemistry, metabolism, and cross-reactivity
of the relevant substances is important for the apposite interpretation of the drug
screening assays. These issues are of particular interest when evaluating immunoassays
for detecting cannabis abuse due to the complexity of cannabinoid chemistry and
metabolism. Moreover, the performance and improvement in the gold standard GC/
MS reference methodologies can influence the overall assessment of cannabinoids
immunoassays.
The main objective of this chapter is to provide an overview of the design strategy,
development, and applications of commonly used DAT immunoassays for cannabinoid
analysis. The factors that impact the performance and result interpretations
of these immunoassays in cannabinoid screening are discussed. Examples of comparative
evaluations of cannabinoid immunoassays will also be reviewed. It has long
been recognized that Cannabis-derived substances are the most frequently abused drugs
worldwide (1–3). Likewise, cannabinoids continue to be the most widely investigated
and extensively published illicit drugs.
2. COMMONLY USED IMMUNOASSAYS FOR DRUGS-OF-ABUSE SCREENING
All currently used immunoassay techniques for DAT screening have been developed
and refined over the past few decades. The reaction principles of these immunoassays
have been described in a number of publications and commercial product
information documents. Therefore, this section will provide only a brief overview of
the commonly used drugs-of-abuse screening techniques.
The majority of DAT immunoassays are based on the competition of drug molecules
in the specimen and drug derivatives in the assay reagent for binding to a
prespecified antibody reagent. The discriminatory power of the antibody-binding site
gives the assay specificity, even though the cross-reactivity profile can be influenced
by factors beyond the binding interaction alone.
The immunoassay indicator for monitoring the binding interactions can be labeled
drug-derivative, antibody, or an independently labeled molecule that can specifically
bind to the antigen or antibody. The labels convey a measurable property to meet the
performance requirements of the specific immunoassay.
In general, the heterogeneous type of immunoassay contains excess labeled-binding
reagent in the reaction mixture, and the reaction outcome is determined by the
relative fractions or activities of the “bound” (e.g., solid phase bound) labels. Thus,
heterogeneous competitive immunoassays involve sequential incubation and separation
or washing steps but can generally achieve lower detection limits and wider dynamic
ranges.
Immunoassays to Detect Cannabis Abuse 147
In contrast, the antibody-antigen reactions in the homogeneous immunoassay
systems can modulate the physical properties or activities of the labels in solution or
in a homogeneous suspension of particles. Such features allow the direct detection of
the reaction outcome in the original reaction mixture. Therefore, the homogeneous
immunoassays can be more readily adapted to screening large amounts of samples
using automatic analyzers. During the design, development, and validation of an
immunoassay, the labeled reagent, the specific binding partner, and the reaction modulators
are prepared in specified and stabilized reagent formulations. In an actual testing,
sample and reagents are processed according to the parameters optimized for the
application of the immunoassay on the specific analyzer system.
2.1. Homogeneous Competitive Immunoassays
In recent years, routine laboratory screening of drugs of abuse in urine has mainly
been carried out by homogeneous competitive immunoassays. The most widely used
homogeneous drug-testing immunoassay technologies include enzyme-multiplied
immunoassay technique (EMIT), fluorescence polarization immunoassay (FPIA), kinetic
interaction of microparticles in solution (KIMS), and cloned enzyme donor immunoassay
(CEDIA). The major assay labels and the technologies are implied in the respective
immunoassay nomenclature.
The assay principle of EMIT is based on the modulation of enzyme activities by
the binding of specific antibodies to the enzyme-labeled drug derivatives (4–6). Currently,
EMIT-based DAT immunoassays can be purchased from several companies,
and a common enzyme of choice is the genetically modified glucose-6-phosphate
dehydrogenase (rG6PDH). The oxidation of enzyme substrate G6P to form
glucuronolactone-6-phosphate is coupled with the reduction of the cofactor nicotinamide
adenine dinucleotide (NAD) to NADH. In the absence of drugs in the sample,
the antibodies bind to the enzyme-labeled drugs and inhibit the enzymatic activity.
Free drugs in the specimen compete for antibody binding, so fewer antibodies are
available for binding to the drug–enzyme conjugates and enzymatic activity is less
inhibited. The rate of NADH production, as reflected by the change in absorbance at
340 nm, is directly related to the G6PDH enzyme activity. Therefore, the change of
absorbance can be plotted vs the corresponding calibrator concentration to construct a
calibration curve for running a semi-quantitative assay. The assay can also be run
qualitatively by comparing the sample rate to the calibrated cutoff rate.
The measurement of FPIA relies on detecting the degree of polarization of the
emitted fluorescent light when the fluorophore label is excited with plane-polarized
light (7,8). FPIA requires a specific FP photometer (9,10). A polarization filter (rotational)
and an emission filter (stationary) enables the photomultiplier tube to read
emitted parallel and perpendicular polarized light. The degree of polarization is
dependent on the rate of rotation of the drug–fluorophore conjugate (tracer) in solution.
Small molecules such as tracers can rotate rapidly before light emission occurs,
resulting in depolarization of the emitted light. When bound to the antibody, the tracer
rotates more slowly and the level of fluorescence polarization is higher. An optimized
amount of the tracer competes with free drugs in the sample for binding to a limited
amount of antibodies. Hence the drug concentration is inversely related to the degree
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of polarization. Calibrators containing known amounts of drugs interact with the tracers
and antibodies to produce a calibration curve relating drug concentrations to arbitrary
“milliPolarization” units (mP). The interactions of the drugs in the specimen, the
tracers, and the antibodies under the same condition controlled by the analyzer yield
mP units that can be correlated with the drug level in the specimen by making a comparison
with the calibration curve.
The principle of microparticle agglutination–inhibition tests has been applied to
various drug screening assay formats (11–15). One KIMS DAT format is based on the
competition of microparticle-labeled drug derivatives and the free drugs in the specimen
for binding to a limited amount of free antibodies in solution (14,15). The drug
conjugates are labeled with microparticles through covalent coupling. These drug conjugates
react with free antibodies and form particle aggregates that scatter transmitted
light. The KIMS-II format contains soluble polymer drug derivative conjugates and
microparticle-labeled antibodies (16). The binding of the conjugates to the antibodies
promotes the aggregation and leads to subsequent particle lattice formation. In both
cases, the aggregation reaction in solution results in a kinetic increase in absorbance
values. Free drugs in the sample compete for antibody binding and inhibit the particle
aggregation. The absorbance difference between a defined initial reading and final
reading decreases with increasing drug concentration, and the signal generated can be
monitored spectrophotometrically. The assay can be run qualitatively in comparison
with the cutoff calibrator. The assay can also be run semi-quantitatively using four or
five levels of calibrators to construct a calibration curve via a logit/log fitting function.
The measurement of CEDIA is based on the antibody modulation of the complementation
of two inactive polypeptide fragments to associate in solution to form an
active enzyme. The fragments of the recombinant microbial β-galactosidase are called
the the enzyme donor (ED) and enzyme acceptor (EA). The binding of antibodies to
the drug–ED conjugates can inhibit the spontaneous assembly of active enzymes
(17,18). The CEDIA reagent composition includes the lyophilized EA and ED reagents
and their respective reconstitution buffer solutions. The antibody binding to
drug–ED conjugates in the analyzer reaction cuvet prevents the formation of active
enzymes in the cuvet. Conversely, free drugs in the specimen compete for antibody
binding and allow the drug–ED conjugates to reassociate with the EA fragments. Therefore,
the drug concentration is proportional to the amount of active enzyme formed.
The enzyme catalyzes the hydrolysis of selected substrate such as chlorophenol red-
β-D-galactopyranoside, and the resulting absorbance rate change is measured as a
function of time (mA/min). CEDIA assays can be run either qualitatively or semiquantitatively
based on an appropriate calibration curve.
2.2. Heterogeneous Competitive Immunoassays
A variety of heterogeneous immunoassay formats have been explored and developed;
among those broadly used for DAT are the radioimmunoassay (RIA) and the
enzyme-linked immunosorbent assay (ELISA). Again, the assay labels and principles
of these technologies are implied in their respective immunoassay nomenclature.
Different formulations of RIA have been developed and evaluated for the detection
and quantification of abused drugs in a myriad of biological matrices, including
Immunoassays to Detect Cannabis Abuse 149
urine, blood, serum, plasma, saliva/oral fluids, meconium, hair, and fingernails
(6,14,15,18–23). The most commonly used radiolabel is 125I. Several methods, such as
the double-antibody approach and the coated-tube technique, were developed to
facilitate the effective separation of free, radiolabeled drug derivatives from the bound
complex. The double-antibody approach employs a second antibody to bind the primary
antibody and precipitate the complex formed by primary antibodies and 125I-drug
derivatives. The coat-a-count technique utilizes precoated primary antibodies in the
reaction tube to allow the removal of the free radiolabeled drug derivatives in the
supernatant. The radioactivity from the bound 125I-labeled drugs in the precipitated
complex, or the bound solid phase, is inversely proportional to the amount of drug in
the sample. Thus, the drug concentration in the sample can be determined by mathematically
comparing average counts per minute (CPM) obtained from the sample
with the CPM obtained from the positive reference standard. For quantification, a
dose–response curve can be established by plotting standard concentrations against
corresponding B/B0 (B0 = CPM obtained from the zero-dose control). Alternatively, a
standard curve can be constructed by plotting logit of [B/B0] vs corresponding values
of loge [drug concentration].
Various commercial or esoteric ELISA methodologies have been utilized for
DAT in forensic, clinical, and toxicological laboratories. Currently, there are approximately
a dozen companies that offer an array of ELISA kits for an extended menu of
drug analysis. Commercial ELISA kits can be applied to test forensic matrices such as
urine, blood, serum, oral fluid, sweat, meconium, bile, vitreous humor, and tissue
extracts (24–29). In recent years, the highest volume of laboratory-based oral fluid
DAT has been performed with qualitative microplate enzyme immunoassays (27).
Most of the ELISA kits use high-affinity capture antibody-coated microtiter plates (or
12- × 8-well strips) and enzyme-labeled drug derivatives. One commonly used enzyme
is horseradish peroxidase, which catalyzes the reduction of peroxide and the
oxidation of the substrate tetramethylbenzidine. The reaction is stopped by diluted
acid, and the resulting color can be measured by absorbance at 450 nm. A few ELISA
tests offer the option to qualitatively determine the absence or presence of drugs by
visually comparing the sample well reaction color to that of the cutoff calibrator and
appropriate negative and positive controls. The drug concentration is inversely proportional
to the amount of signal produced. Various instrument platforms for ELISA
are available with optional data management software.
Immunoassays with chemiluminescence detection techniques have the advantages
of lower detection limits, and the signals can be further amplified if coupled
with an enzyme label (30). An example of commercial enzyme-enhanced chemiluminescence
assay for DAT is the IMMULITE® cannabinoid assay. The chemiluminescent
substrate (1,2-dioxetane) is destabilized by the enzyme (alkaline phosphatase),
and the unstable dioxetane intermediate will emit light upon decay back to the ground
state. Although this is a heterogeneous immunoassay in principle, the analyzer for
Immulite assay utilizes a test unit that contains polystyrene beads to capture antibody
and hence separate the reaction components within the unit. The tube is the reaction
vessel for incubations, washes, and signal development. The photon count is mathematically
converted to analyte concentration by the external computer.
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2.3. Point-of-Collection Drug Immunoassays
In the early phases of drug-testing program implementation, the majority of onsite,
point-of-care, or point-of-collection (POC) DAT programs employed instrumentbased
immunoassays that were performed at “on-site, initial screening only testing
facilities” (31–33). Pioneers of noninstrumented DAT on-site testing have been available
since the early 1980s, yet the markets for single-use DAT devices only became
mature in the 1990s (12,13,34–45). In recent years, there has been an increase in the
numbers, and especially in the distributors, of on-site drug testing products. The more
extensive list of the commercial POC drug testing (POCT) products can be found in
reports that include the initial evaluation or inventory of the contemporary on-site
testing products in their study protocols (35–37).
In general, there are three major categories of POCT products. One type consists
of the microparticle agglutination–inhibition based assays with ready-to-dispense liquid
reagents (13,37). Another category of POCT product contains both liquid reagent
and membrane-immobilized reagent, such as membrane enzyme immunoassay or the
ASCEND® multi-immunoassay (37,38). The most widely commercialized and commonly
employed immunoassay for on-site DAT is the membrane-based, dry chemistry,
one-step lateral-flow immunochromatography (37,39–45). The lateral flow test
strip configurations include the colloidal gold-based test strip configuration (40,41,46)
and latex-enhanced immunochromatography (39,47). A number of readers have also
been marketed to assist in interpreting and/or recording the results of the POC test
strips. In addition, a few nonconventional immunoassay technologies have been explored
to utilize small instruments with quantitative ability for on-site drug testing or
monitoring (48–50).
The advantages generally cited for using POCT products include the speed in
obtaining a qualitative determination and the ease of use. Many of the POCT devices
are self-contained, panel-testing devices that can be stored at room temperature.
The ready-to-use devices depend on precalibration during manufacturing. Although
the devices generally have less clear differentiation in near-cutoff result reading, these
assays in routine use have been shown to provide comparable performance with conventional
immunoassays in most drug-screening settings that demand a rapid turnaround
time.
3. CANNABINOID IMMUNOASSAYS
3.1. Cannabinoid Test System
Cannabis is by far the most widely cultivated, trafficked, and abused illicit drug
in the world (1–3). According to the recent Drug Abuse Warning Network update
(51), the rate of drug abuse-related emergency department visits involving marijuana
rose 139% nationally from 1995 to 2002. As reported in the Drug Testing Index series
published by Quest Diagnostics (52), cannabinoid analysis has always had the highest
“drug positivity rate by drug category” among all of the abused drugs tested in workplace
drug-testing programs. Likewise, cannabinoid assays are among the most frequently
performed tests in society drug testing, behavior toxicology, and criminal justice
testing.
Immunoassays to Detect Cannabis Abuse 151
Cannabinoid is a term originally used to denote the unique C21 compounds found
in the plant Cannabis sativa L. (53,54). Recent progress in cannabinoid research has
been extended to various ligands of the cannabinoid receptors and related compounds,
including the transformation products of cannabinoids, synthetic cannabinoid analogs,
and the endocannabinoids, namely, the endogenous ligands of the cannabinoid
receptors (55–58). As reflected by the profuse publications in cannabinoid chemistry,
tremendous efforts have been invested in the isolation of the chemical constituents
and the investigation of the structure–activity relationships of the cannabinoids.
The Cannabis plant contains more than 400 chemical compounds belonging to
18 different classes, including more than 60 phytocannabinoids that contain a typical
C21 structure with pyran and phenolic rings (53–60). Most of the phytocannabinoids
belong to several subclass types, including the tetrahydrocannabinol (Δ9-THC and Δ8-
THC), cannabinol (CBN), cannabidiol (CBD), cannabichromene (CBC), and
cannabigerol types (Fig. 1). The main active constituent of cannabis, and the primary
psychoactive cannabinoid is Δ9-THC (55–59). The nomenclature Δ9-THC is based on
the dibenzopyran numbering system; the same compound can also be called Δ1-THC
according to the monoterpene numbering system (54). Immunoassays for detecting
cannabis abuse in urine have been designed to detect THC metabolites and are generally
referred to as the cannabinoid assay or THC assay.
In The Federal Register (21 CFR 862.3870), the cannabinoid test system is identified
as “a device intended to measure any of the cannabinoids, hallucinogenic compounds
endogenous to marihuana, in serum, plasma, saliva, and urine. Cannabinoid
compounds include Δ9-THC, CBD, CBN, and CBC. Measurements obtained by this
device are used in the diagnosis and treatment of cannabinoid use or abuse and in
monitoring levels of cannabinoids during clinical investigational use.” Quantitatively,
the most important cannabinoids present in the cannabis plant are THC and the much
less prominent constituents CBD, CBN, and CBC (58–60). Immunoassays developed
to detect THC metabolites usually have certain degrees of cross-reactivity with CBN
but have minimal or no detectable level of cross-reactivity with the ring-opened compounds
such as CBD, CBC, and cannabigerol.
In analyzing 35,312 cannabis preparations confiscated in the United States
between 1980 and 1997 (59), ElSohly et al. reported that the average concentrations
for THC were 3.1% in marijuana (herbal cannabis), 5.2% in hashish (cannabis resin),
15.0% in hash oil (liquid cannabis), and 8.0% in sinsemilla (unfertilized flowering
tops from the female Cannabis plant). The average THC content of these cannabis
preparations all showed significant increase over the years. The outcome of a cannabinoid
test can be affected not only by the analytical performance but also by drugadministration
factors such as the potency (%THC) of the drug consumed, the route of
administration, the methods, vehicles, and frequency of drug intake, the timing of
drug use and sample collection, the type of samples tested, and the pharmacokinetics
and pharmacodynamics of cannabinoids (23,61–73).
3.2. Cannabinoids: Pharmacokinetics and Drug Analysis
Cannabinoids immunoassays for each type of biological matrix have to be
designed and interpreted in the context of Δ9-THC absorption and metabolism. The
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pharmacokinetics, metabolism, and excretion profiles of cannabinoids have been comprehensively
studied and reported (20,21,23,54–58,61–76). THC is known to be
extensively metabolized to a large number of compounds, even though most of the
compounds are inactive (73–77). As shown in Fig. 2, Δ9-THC is mainly hydroxylated
Fig. 1. Chemical structure of naturally occurring cannabinoids. 21 CFR 862.3870
defines a “cannabinoid test system” as “a device intended to measure any of the
cannabinoids, hallucinogenic compounds endogenous to marihuana, in serum,
plasma, saliva, and urine. Cannabinoid compounds include Δ9-tetrahydrocannabinol,
cannabidiol, cannabinol, and cannabichromene. Measurements obtained by this
device are used in the diagnosis and treatment of cannabinoid use or abuse and in
monitoring levels of cannabinoids during clinical investigational use.”
Immunoassays to Detect Cannabis Abuse 153
at the allylic positions (C-11 and C-8) and further oxidized. Oxidation also occurs at
the pentyl side chains. Similar biotransformation pathways exist for Δ8-THC (C-7 and
C-11) and other cannabinoids. Smaller quantities of other metabolites are produced by
minor metabolic pathways.
It has been well established that the oxidative metabolism of aliphatic, benzyl,
phenylethyl, and allylic alcohols to the corresponding carbonyl compounds is catalyzed
by numerous cytochrome P450 (CYP) enzymes with overlapping substrate specificity
(74–77). In human liver microsomes, the C-11 position of THC is metabolized
by CYP2C subfamilies, and the C-7 and C-8 positions are metabolized by the CYP3A
isoforms. Pharmacogenetic studies have demonstrated the significant interindividual
variations in CYP-catalyzed metabolism. Metabolite composition varies with specimen
source and experimental conditions. The presence of various amounts of metabolites
in a given biological matrix and their relative binding affinity to the given
antibodies may both contribute to different degrees of cumulative total binding activities
for different immunoassays.
Initial metabolism following inhalation takes place in the lungs and liver to 11-
hydroxy-Δ9-THC (11-OH-THC), which is subsequently oxidized in the liver through
11-oxo-THC as an intermediate to 11-nor-Δ9-tetrahydrocannabinol-9-carboxylic acid
(THC-COOH) and other inactive metabolites. The major THC metabolite in plasma
and urine following smoking is THC-COOH, whereas a higher level of 11-OH-THC
is present in blood after oral ingestion (61–70). In frequent smokers, residual levels of
THC and THC-COOH have been detected for an extended period of time after cessa-
Fig. 2. Metabolic transformation of Δ9-tetrahydrocannabinol (THC). (Note: Analogous
pathways exist for Δ8-THC and cannabichromanon.)
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tion of drug use. Most commercial cannabinoid immunoassays are calibrated with the
major metabolite, THC-COOH, but also have to meet the product design specifications
for the antibody cross-reactivities with THC drug and other THC metabolites
(e.g., 8-α-hydroxy-Δ9-THC, 8-β-hydroxy-Δ9-THC, 8-β,11-di-hydroxy-Δ9-THC, and 11-
OH-THC). Although immunoassays developed for urinalysis can be adapted for alternative
specimen testing, the cross-reactivity characteristics selected for urine drug
screening may not be optimal for other biological matrices. The antibody reactivity
with the parent Δ9-THC is especially important for oral fluid testing.
Glucuronic acid conjugation with Δ9-THC and its hydroxylated and carboxylated
metabolites generates water-soluble compounds; thus THC-COOH and other
metabolites are mainly excreted as their glucuronide conjugates in urine and meconium
(78–86). In routine cannabinoid urinalysis, presumptive positive samples are
confirmed by GC/MS detection of free THC-COOH, which was liberated from its
glucuronide by chemical or enzymatic hydrolysis prior to sample extraction. Kemp et
al. (83) evaluated different hydrolysis methods in the quantification of Δ9-THC and its
major metabolites in urine and demonstrated the inefficiencies of base hydrolysis on
the hydroxylated compounds. There is a species-dependent glucuronidase activity;
hydrolysis with Escherichia coli glucuronidase greatly increased the concentration of
free Δ9-THC and free 11-OH-THC in urine collected following marijuana smoking.
The concentration of free THC-COOH was not significantly affected by hydrolysis
method.
Gustafson et al. (81) analyzed plasma samples collected in a controlled oral Δ9-
THC administration study and found increases of 40% for 11-OH-THC and 42% for
THC-COOH concentration between hydrolyzed and nonhydrolyzed results. ElSohly
and Feng (79) compared the effect of hydrolysis on the detection of Δ9-THC metabolites
in meconium and demonstrated significant levels of 11-OH-THC and 8-β,11-
diOH-Δ9-THC after hydrolysis but none without hydrolysis. Among the samples
examined, one showed an almost 50% increase in THC-COOH concentration as a
result of enzymatic hydrolysis. Analysis of several meconium specimens that “screened
positive for cannabinoids but failed to confirm for THC-COOH” showed significant
amounts of 11-OH-THC and 8-β,11-diOH-Δ9-THC. Hence, the authors suggested that
GC/MS confirmation of cannabinoids in meconium should include analysis for these
metabolites in addition to THC-COOH.
The ratio of glucuronidated vs free THC-COOH in the sample at the time of
immunoassay analysis may influence the comparative immunoassay evaluation.
Employing LC/MS/MS with and without enzyme hydrolysis, Weinmann et al. (86)
determined that the molar concentration ratio of glucuronidated vs free THC-COOH
in urine samples of cannabis users was between 1.3 and 4.5. In studying the profiles of
THC metabolites in urine, Alburges et al. (78) observed that all of the THC-COOH
excreted in the first 8 hours from an infrequent user was in conjugated form, whereas
free THC-COOH could be detected in urine from a frequent user for at least 24 hours.
Skopp et al. (84,85) investigated the dynamic changes of free vs conjugated THCCOOH
in urine and found that free THC-COOH was not detected in 20 out of 38
fresh, authentic samples. At the end of the observation period, 5–81 ng/mL of THCCOOH
was detectable in 11 samples that initially tested negative. The results showed
Immunoassays to Detect Cannabis Abuse 155
that THC-COOH and THC-COOglu, as well as total THC-COOH concentrations, might
undergo dynamic changes in urine samples depending on pH and storage conditions
(85). THC-COOH is the primary urinary cannabinoid analyte quantified by GC/MS
after hydrolysis and extraction. In contrast, immunoassays are calibrated for THCCOOH
detection, and the antibodies generally have variable degrees of cross-reactivity
towards the glucuronidated metabolites.
By and large, the immunoassay result is based on the sum of various levels of
antibody immunoreactivities in the sample matrix tested. The overall reactivity (as
expressed in apparent THC-COOH concentration or calibrator-equivalent unit) can be
affected by various factors. Among the pivotal factors is the design of the chemical
structures for both the drug derivatives for reagent conjugation and the immunogens
used for antibody generation.
3.3. Immunogen Strategies for Antibody Generation
The overall analytical sensitivity and specificity of an immunoassay is, to a significant
extent, related to the characteristics of the antibody used in the assay. Because
drugs such as cannabinoids are small molecular weight haptens, a carrier protein is
needed to produce an effective Immunogen. The site of linkage on the drug molecule
to the protein carrier can determine the reactivity of the resulting antibodies. The specificity
of an antibody is usually directed toward those structures on the hapten that are
distal to the linkage group. Thus, the linkage site allows haptens to be coupled to the
carrier in such a way that characteristic functional groups are exposed for antibody
generation (20,21,87–89).
Figure 3 shows the published linkage sites for coupling cannabinoid haptens to a
carrier protein. These linker groups include those out of the C1-position, the C2-position,
the C9-position, and the C5’-position of the THC-COOH compound or a very
closely related compound. Various immunogen design structures were described in
the National Institute on Drug Abuse Research Monographs 7 and 42 (20,21). Most of
these antibodies were used for the development of RIAs with the exceptions of immunogen
structures depicted for developing EMIT assay with the enzyme “pig heart malate
dehydrogenase.” There are a few major families of US/European/World patents for
cannabinoid immunoassays along with claims for the structures of drug derivatives
and/or immunogens. The patent families include those for Abbott’s FPIA and those
for Roche’s RIA, enzyme immunoassay, FPIA, and KIMS cannabinoid assays (88,89).
Salamone et al. (87) comprehensively reviewed the selectivity of different immunogen
structures and also described an approach to generate antibodies with a broader
spectrum of cross-reactivities towards THC metabolites by “sequential immunization”
and by designing a noncannabinoid, benzpyran core, immunogen. Taken together, the
antibody generation approaches can be summarized as follows:
1. In general, antibodies generated from immunogens with the linkage position out of
the C1-, C2-, or C5’-positions are more selective for the cyclohexyl ring, hence they
usually display high selectivity for the unconjugated form of THC-COOH. The crossreactivities
for the 8-, 9-, and 11-substituted metabolites is lower because of the high
recognition of the antibodies for this part of the molecule. Likewise, the cross-reactivities
with the glucuronidated compounds are lower because the ether bond forms between
156 Tsai
glucuronic acid and the hydroxyl moiety at C-11 for 11-OH-THC, and the ester bond
forms between the glucuronide and the carboxyl moiety at C-11 for THC-COOH.
2. On the other hand, antibodies generated by immunogens with the C-9 position linkage
are less selective for the cyclohexyl ring. Nevertheless, these antibodies typically show
better binding to the 8-, 9-, and 11-substituted metabolites, as well as improved binding
to their corresponding glucuronides. The antibodies also exhibit some selectivity
for the cannabinoid nucleus in this region. These types of antibodies can be selected
for high cross-reactivities for some, but not all, of the 8-, 9-, and 11-hydroxylated
metabolites.
3. To increase the spectrum and degree of cross-reactivities for THC metabolites, a
noncannabinoid immunogen was designed not to hold the antigenic determinants of
the cyclohexyl ring, and hence the resulting antibodies will be indifferent to the
cyclohexyl portion of the cannabinoid nucleus. Such a bicyclic immunogen contained
only the structure of the benzpyran core. By eliminating the portion of the molecule
that undergoes extensive metabolism from the immunogen and by preserving the core
structure, antibodies with higher cross-reactive values with positive clinical samples
can be generated. The resulting antibodies from the benzpyran core immunogens all
showed broader cross-reactivities towards the 8-, 9-, and 11-hydroxylated metabolites.
Fig. 3. Immunogen strategies for the generation of anticannabinoid antibodies:
common sites of linkage of cannabinoid haptens to a carrier protein. (From refs.
4,19,20,83–85.)
Immunoassays to Detect Cannabis Abuse 157
The broad-spectrum antibodies can be utilized beyond the development of
immunoassays. Feng et al. (80) immobilized THC antibody that was generated from
the benzpyran core immunogen to prepare immunoaffinity chromatography for developing
a simpler extraction procedure for Δ9-THC and its metabolites from various
biological specimens. Good recovery was achieved by simultaneous extraction of Δ9-
THC and its major metabolites, including THC-COOH, 11-OH-THC, and 8-β,11-diOH-
Δ9-THC, from plasma or urine after enzyme hydrolysis. A similar approach was also
used for meconium analysis and confirmed that 11-OH-THC (80) is indeed an important
metabolite in meconium.
The evolution of assay specificity can also be observed from the review of three
decades of publications regarding cannabinoid immunoassays. In the earlier stages of
drug immunoassay development, immunogens were used to produce polyclonal antibodies
from selected animals. Naturally, polyclonal antibodies have broader crossreactivities
that are collectively contributed by a range of antibody affinity, avidity,
and binding characteristics. The overall cross-reactivity manifestation can vary a bit
from animal to animal and may change slightly over different time periods. Thus, it is
not unusual for large pools of polyclonal antibodies to be validated and sequestered.
Most current DAT immunoassays use monoclonal antibodies that are much more
selective and specific and possess consistent quality. High specificity toward the target
THC-COOH may increase overall immunoassay specificity at the expense of sensitivity.
Thus, high antibody specificity may have the disadvantage of lower detection
rate for clinical samples that contain THC-COOH near the screen cutoff concentration.
Broad-spectrum monoclonal antibodies can possess the advantages of both monoclonal
antibody consistency and the broader cross-reactivity profile. Nevertheless, the
increased immunoassay sensitivity resulting from the higher values of THC-COOH
equivalents might have the disadvantage of producing unconfirmed positives and might
need a lower GC/MS cutoff (87).
Bearing in mind the variations in the relative percentages and forms of Δ9-THC
metabolites present in the testing samples, both the detection and confirmation rates
can have trade-offs, especially for near-cutoff samples. The ultimate goal for a cannabinoid
immunoassay design is to balance the assay sensitivity and specificity for its
comparative performance to the GC/MS analysis according to their respective cutoff
guidelines and regulations.
3.4. Regulations and Guidelines
Globally, various guidelines for substance abuse management have been developed
by government agencies, forensic societies, and clinical organizations. Some of
the guidelines include more detailed technical and procedural recommendations for
specimen collection and processing, initial drug screening, confirmation analysis, quality
control and assurance, and documentation and result-reporting requirements.
In the United States, the federally regulated drug-testing programs are implemented
and administered by the Substance Abuse and Mental Health Services Administration
(SAMHSA, formerly National Institute of Drug Abuse) and Department of
Health and Human Services. The 1994 SAMHSA Mandatory Guidelines for Federal
Workplace Drug Testing Programs (90) define initial test or screening test as “an
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immunoassay test to eliminate negative urine specimens from further consideration
and to identify the presumptively positive specimens that require confirmation or further
testing.” The guidelines mandate that the initial test “shall use an immunoassay
which meets the requirements of the Food and Drug Administration (FDA) for commercial
distribution.” The guidelines also permit multiple initial tests (or rescreening)
to be performed utilizing different immunoassays for the same drug or drug class
under the stipulation that “all tests meet all Guideline cutoffs and quality control
requirements.”
The regulated approach to initial screening “permits rapid identification of presumptive
positives within a framework of extensive quality control and offers a defined
reference if the next step confirmation is required.” This allows a process with a set
“administrative cutoff” for uniform comparison across different assay principles and
various volumes of screening. The specified cutoff levels for cannabinoids testing were
set at 100 ng/mL for immunoassays and 15 ng/mL for GC/MS in the first Mandatory
Guidelines (53 FR 11970, 1988). The cutoff for immunoassay was lowered to 50 ng/mL
in the subsequent version of the federal guidelines (91). In case a retest is required for
a specimen or for the testing of Bottle B of a split specimen, the federal guidelines state
that the retest quantification is not subject to a cutoff requirement. However, the retest
“must provide data sufficient to confirm the presence of the drug or metabolite” (90).
The proposed revisions for the next version of the Mandatory Guidelines (91,92)
will include regulations on specimen validity testing, POCT, and alternative specimen
testing. Additionally, the new guidelines will expand the authorized confirmation
method from only GC/MS to allow the use of additional confirmation technologies
such as LC/MS. However, the new guidelines draft does not change the cutoff requirements
for cannabinoid testing. Other civilian drug-testing programs, such as the College
of American Pathologists Forensic Urine Drug Testing laboratory accreditation
program, allow the cutoff determinations be made according to the need of the laboratory
or to the intent of its clients’ drug-testing programs. Generally speaking, even in
nonregulated sectors, many drug-testing programs follow the cutoff defined by the federal
guidelines and require reporting positive results if both the initial immunoassay
results and the GC/MS analysis are at or above their respective cutoff concentration.
The provisions of the rules that affect US corporations may be imposed on their
global employees. In contrast, countries in the European Union, Asia, and Australia
differ in their concerns and strategies in relation to substance abuse problems. Surveys
of DAT in European Union laboratories in the late 1990s indicated that a high percentage
of laboratories did not use or report cutoff (93–95). A few work groups in Europe
have proposed consensus or country-specific guidelines and cutoffs, including drugtesting
application-specific cutoffs, for DAT (see, e.g., refs. 96–98). The European
Laboratory Guidelines for Legally Defensible Workplace Drug Testing were developed
by the European Workplace Drug Testing Society with an aim to “establish best
practice” for laboratories within Europe “whilst allowing individual countries to operate
within the requirements of national customs and legislation” (98). For urine drug
testing, the maximum cutoff for screening test and the confirmation cutoff recommended
by the European Workplace Drug Testing Society for cannabis metabolites
are the same as those mandated by the current SAMHSA guidelines.
Immunoassays to Detect Cannabis Abuse 159
3.5. Comparative Evaluation of Cannabinoid Immunoassays
3.5.1. General Evaluations
Immunoassays for commercial applications have to be developed and manufactured
in compliance with a number of regulations and quality-management requirements.
Currently, all projects for immunoassay research, development, and
commercialization are required to follow the FDA Design Controls and Quality System
Regulations. The overall assay performance characteristics have to meet an array
of predefined specifications with robust assurances at each of the design control milestone
reviews in order to receive approval for proceeding to the next milestone. The
manufacturers then submit data and statistical analyses in support of claimed performance
parameters for the assay/device/instrument application to FDA for 510K review
and approval for premarket clearance. Likewise, the manufacturers have to declare
conformity and submit required data and documentations to the European In Vitro
Diagnostic Directive for the immunoassays to be registered for the “CE mark.” There
are also country-specific processes for registration and approval for commercialization
in countries such as Japan and Canada. Additionally, many companies require
external clinical trials during product development to simulate the performance in the
field as well as to anticipate any potential findings or cross-reactivity issues not observed
during the in-house development. To date, the majority of published evaluations
of different immunoassay products have involved authentic clinical samples from
either controlled drug-administration study or specimens collected for routine laboratory
drug testing (see, e.g., refs. 14, 15, 18, 35, 36, and 99–105).
3.5.2. Cutoff Concentrations and Immunoassay Evaluations
Because a cutoff is the concentration of drug below which all specimens are
considered to be negative, the cutoff decision has a direct impact on the detection time
window and the positive rate. The most commonly used method for immunoassay
performance comparisons is to evaluate the so-called true-positive (TP), true-negative
(TN), false-positive (FP), and false-negative (FN) of the assay. These results can then
be used to calculate the specificity [TN / (TN + FP)] × 100%, sensitivity [TP / (TP +
FN)] × 100%, efficiency [(TP + TN) / (TN + FP + TP + FN)] × 100%, or positive or
negative predictive values of the assay. Because the criteria for either true or false are
based on the comparison of immunoassay and GC/MS interpretation at their respective
screening and confirmation cutoff levels, the goals and strategies for balancing
the relative performance around the selected cutoff concentrations are among the important
considerations for designing an immunoassay for cannabinoid testing.
Traditionally, the cutoff decision can be made by considering the assay limit of
detection or a predefined, higher concentration. Although not generally inferred in the
context of drug testing, cutoff sometimes is used to refer to the analyte concentration
at which repeated tests on the same sample yield positive results 50% of the time and
negative results for the other 50%. In a near-cutoff zone as concentrations close to the
cutoff value, some results may be positive or negative for different analytical methodologies
or for repeated testings using the same method. For most drug-testing programs,
the “administrative cutoffs” were chosen with the consideration that the cutoff
160 Tsai
is sufficiently above the assay limit of detection, yet low enough to allow the detection
of drug use within a reasonable time frame (90,91). One of the earlier concerns in
setting the immunoassay cutoff for cannabinoids was the risk of falsely identifying
urine samples as positive for individuals exposed to passive marijuana smoke. Nonetheless,
further studies on passive inhalation have led to the conclusion that the levels
of cannabinoids in the body from passive inhalation would not be enough to cause
urine specimens from a non-marijuana user to test positive using a screen cutoff concentration
of 50 ng/mL (72,106,107).
Several studies have since demonstrated that higher positive rates for marijuana
detection were achieved by lowering the initial testing cutoff in urine (100–105). The
sensitivity vs specificity tradeoff also reflects the fact that the target analyte specificity
is related to the detection rate of cannabinoid immunoassays, especially for samples
that contain THC-COOH concentrations between the mandated GC/MS cutoff and the
mandated (or chosen) immunoassay cutoff levels (100–105,108–110).
Luzzi et al. (111) investigated analytical performance of drug detection below
the SAMHSA cutoffs and showed that the accuracy of urine drug-screening results
between the SAMHSA-specified cutoffs and the precision-based cutoffs was less than
the accuracy for specimens above the SAMHSA cutoffs. The use of the precisionbased
cutoff for clinical drug testing increased both the number of screen-positive
specimens and the detection of specimens that yielded positive results on confirmatory
testing. However, the confirmatory rates for subcutoff-positive specimens were
lower than for specimens screened positive at cutoff. When choosing 35 ng/mL as the
subcutoff for EMIT screening, 90% of the subcutoff-positive THC specimens contained
THC-COOH by GC/MS analysis. Similarly, Hattab et al. (112) stated that the
immunoassay cutoff could be further lowered for detecting maternal and neonatal drug
exposure. Using the lower thresholds, drugs were detected in 4–5% of the subjects
that had screened negative at the conventional threshold concentrations. GC/MS analysis
confirmed the presence of cannabinoids in 74% of urine specimens that rescreened
positive at a lower cutoff.
The target ranges of cutoff concentrations for alternative specimen testing are
significantly lower than those for urine drug testing. The application of alternative
specimens for drug testing is still an evolving field, and there have been ongoing discussions
and studies over recent years (23,27–29,42,45,113–122). In a prevalence study
that compared positivity rates of oral fluid test results with urine test results for different
drugs, the screening and confirmation cutoff concentrations selected for oral fluid
cannabinoids testing were 3 and 1.5 ng/mL, respectively (27). The overall confirmedpositive
prevalence rate for oral fluid testing at these cutoff concentrations was 3.2%.
In comparison, the confirmed-positive prevalence rates for urine testing using 50 and
15 ng/mL as the respective screening and confirmation cutoffs were 1.7% for federally
mandated urine testing and 3.2% for private sector workplace testing.
With the low cutoff concentrations for oral fluid cannabinoid screening and confirmation,
oral fluid testing also has the potential to produce positive results from
passive cannabis smoke exposure. In a controlled dosing study, Niedbala et al. reported
that two individuals who were passively exposed to the smoke from 10 cannabis cigarettes
produced positive screening results, which failed to test positive by GC/MS/MS
Immunoassays to Detect Cannabis Abuse 161
(27). In a subsequent study with five cannabis smokers and four passive subjects, the
authors observed a biphasic pattern of decline for THC in oral fluid specimens collected
from active smokers, whereas the pattern of THC decline was linear in specimens
collected from passive subjects (28). The authors concluded that the risk of
positive oral fluid tests from passive inhalation is limited to a period of approx 30
minutes following smoke exposure.
In the latest version of the Proposed SAMHSA Guidelines (91), the following
cutoff concentrations are recommended for detecting cannabis abuse:
1. Initial tests:
a. 1 pg marijuana metabolite/mg hair sample.
b. 4 ng marijuana metabolite/sweat patch.
c. 4 ng “THC parent drug and metabolites”/mL oral fluid specimen.
d. 50 ng “THC metabolites”/mL urine specimen.
2. Confirmation:
a. 0.05 pg THC-COOH/mg hair sample.
b. 1 ng THC parent drug/sweat patch.
c. 2 ng THC parent drug/mL oral fluid specimen.
d. 15 ng THC-COOH/ mL urine specimen.
3.5.3. Correlation of Results From Cannabinoid Immunoassay
and GC/MS Analysis
A number of studies have been conducted to investigate how well results from
cannabinoid immunoassays can correlate to GC/MS analysis and/or to select an
appropriate cutoff value for each of the initial test methods (99–105). In all cases the
general correlations exist, yet the data points could be rather scattered. Generally speaking,
the correlation coefficients are more sensitive to the change of sample groups, in
which the distributions in the relative concentrations of THC-COOH and other crossreacting
compounds varies.
The relative concentrations of THC metabolites in plasma and urine have been
studied to determine if a temporal relationship could be estimated between marijuana
use and metabolite excretion (65,69). With the addition of the β-glucuronidase
hydrolysis step in the extraction protocol, the presence of significant quantities of
THC and 11-OH-THC in urine could be demonstrated (69). The relative concentrations
of THC-COOH and 11-OH-THC can be shown in a scatter plot when all data for
urinary THC-COOH and 11-OH-THC concentrations published in the article by Manno
et al. (69) were used to create the plot shown in Fig. 4. For samples with THC-COOH
levels closely surrounding the 15 ng/mL cutoff, the relative cross-reactivities of an
immunoassay with 11-OH-THC, THC-COOH, and their relative abundance may contribute
to the immunoassay outcome by rendering the results false positive or false
negative when compared to a fixed GC/MS value of THC-COOH.
In addition to the interindividual metabolism and metabolite variability, the correlation
of immunoassay and GC/MS results can also be influenced by the total performance
characteristics of not only the screening but also confirming techniques used
(123–127). Because all analytical techniques have an acceptable range of imprecision,
it is essential to note that a value generated from immunoassay or GC/MS analysis is
162 Tsai
162
Fig. 4. Relative concentrations of THC-CODH and 11-OH-TCH in cannabinoids containing urine samples.
(Adapted from data from ref. 65.)
Immunoassays to Detect Cannabis Abuse 163
not an absolutely fixed number. These analytical techniques all have to be validated
and meet a host of quality-control and quality-assurance requirements. Similar to the
requirements for proper utilization of immunoassays, knowledge of the advantages
and potential pitfalls of different GC/MS systems as well as ionization and detection
modes would facilitate proper optimization for the accuracy of compound quantification
and identification (124).
Because GC/MS involves multiple steps of extraction, derivatization, and quantitative
analysis, the laboratory has to determine the acceptable criteria for replicate
analysis. Generally, the repeatability and reproducibility of GC/MS in a certified laboratory
are excellent, even though there are interlaboratory variabilities among the certified
laboratories. For years, the College of American Pathologists and American
Association for Clinical Chemistry have been conducting quarterly surveys and yearend
critiques for all certified laboratories. The survey results of THC-COOH analysis
for year-end 2002 and the first quarter of 2003 are listed in Table 1. The results are
fairly consistent over the years, and the interlaboratory coefficient of variation has
been approx 10–15%. Statistically, the variations may not significantly affect the confirmation
of presumptive positives, even though the confirmation rate for near-cutoff
samples can be more readily affected.
A semi-quantitative immunoassay produces a numerical concentration that
approximates the total amount of THC-COOH along with associated metabolites in
the specimen, namely, a value for apparent THC-COOH equivalent. The results of
unknown clinical samples are calculated by the automatic analyzers based on a calibration
curve. The calibration curve is calculated from prevalidated equations for the
best-fit curve. The claimed concentrations of calibrators must be established by repeated
Table 1
Examples of the AACC/CAP Forensic Urine Drug Testing (Confirmatory)
Survey Results
Mean Coefficient of Low value High value
Survey No. labs (ng/mL) variation (%) (ng/mL) (ng/mL)
UDC-1, 2003 128 514.61 16.9 247.3 718.8
112 77.18 10.9 53.9 101.0
111 10.6 12.1 7.4 14.3
UDC, 2002 113 91 13.7
(year-end 127 591 15.0
critique) 118 97 12.4
122 95 11.2
109 36 12.7
126 14 12.7
145 13 13.8
Data were obtained with permission from American Association for Clinical Chemistry/
College of American Pathologists (AACC/CAP) forensic urine drug testing (confirmatory)
Survey UDC-A of 2003 and Survey 2002 year-end critique for Δ9-THC-COOH.
164 Tsai
GC/MS analysis to ensure that the THC-COOH concentration in the calibrators stays
within the acceptable range of GC/MS values for the entire duration of its shelf life.
Table 2 shows a collection of analytical recovery data or imprecision data from
various package inserts of commercial immunoassays. The nominal THC-COOH concentration
is the amount of THC-COOH compound spiked into urine for running the
immunoassays, and the numerical value of apparent THC-COOH concentration is the
average of replicate results obtained from the immunoassays.
In general, the results of semi-quantitative immunoassays provide an indication
of the levels of THC metabolites to assist in making dilutions for GC/MS analysis.
How closely a semi-quantitative immunoassay result can match the nominal value is
affected by a number of factors, including the quantitative accuracy of calibrators, the
quantitative accuracy of the spiked samples for evaluation, the constituents of the
specimens, the assay precision for the lot of reagents used, and the assay dynamic
range. The results may no longer be semi-quantitative in that the absorbance changes
of the immunoassay flatten out or reach the plateau (128). Commonly used commercial
immunoassays offer applications for multiple cutoff choices to meet the requirement
of different drug-testing programs. Depending on the drug-testing program goals
and preferences, the more frequently used cutoff concentrations for urinary cannabinoid
immunoassays are 20, 25, 50, and 100 ng/mL.
In a study designed to understand the relationship of THC concentrations in oral
fluid and plasma after controlled administration of smoked cannabis, Heustis and Cone
observed that results from an RIA selective for THC were higher than those obtained
from GC/MS. The mean ± standard deviation ratio of RIA to GC/MS concentration
was 3.35 ± 2.16, with a range of 1.1–8.8 (23). The higher estimated THC concentrations
in oral fluid by the RIA screen method were attributed to cross-reactivities of the
THC RIA antibody to other cannabis constituents. In this study, THC RIA concentrations
at 0.2 hour were generally 20-fold or more than those measured at 0.27 hour.
With a 1.0 ng/mL screening cutoff concentration, the mean detection times by RIA for
the 1.75% and 3.55% doses were 5.7± 0.8 and 8.8 ± 8.3 hours, respectively. The authors
also compared the excretion rates in three biological specimens from the same
subject by GC/MS analysis of THC (for oral fluid and plasma) and THC-COOH (for
urine) and reported half-life estimates of 0.8 hour for oral fluid, 0.9 hour for plasma,
and 16.9 hours for urinary specimens.
3.5.4. Stability of Cannabinoids in Biological Matrices
Different stability studies have been conducted to investigate the stability of THCCOOH
in urine or the stability of THC and THC-COOH in blood (84,85,129–134).
The hydrophobic nature of cannabinoid molecules may lead to the loss of drugs in the
specimen caused by surface adsorption to the specimen-handling and storage devices
and containers. The loss of analyte from calibrator solutions can lead to inaccuracy of
the analytical system (129). The stability of cannabinoids in immunoassay calibrator
solutions and in urine samples has been extensively evaluated in various container
materials at different temperatures (129–134). In addition to potential analyte loss to
surface adsorption, the temperature and storage conditions can affect the stability of
cannabinoids in specimens. Drug partition into strata when frozen in urine was observed
and postulated to be due to the thermodynamics of the freezing process (131).
Immunoassays to Detect Cannabis Abuse 165
165
Table 2
Analytical Recovery of Semi-quantitative Cannbinoid Immunoassays at Different Cutoff Concentrationsa
Nominal THC-COOH (ng/mL) vs average “apparent THC-COOH concentration” (ng/mL) at different cutoff levels
Assay cutoffb 15 18 20 22 25 30 37.5 40 45 50 55 62.5 60 75 80 90 100 125 135 150 180
EMIT-100c 12 36 36 41 62 74 95 110 153 192
EMIT-50c 30 33 39 42 42 45 48 65 130 163 179
EMIT-20c 16 18 20 21 24 51
FPIAd 21 34 45 54 78 98 135
KIMS II-
100/50/20e 16 20 23 39 49 69 79 96 140
aAverage THC-COOH concentration reported in the packiage inserts for either “accuracy by recovery” or “impression studies” of the immunoassay
products. The “nominal THC-COOH concentration” is the amount of THC-COOH compound spiked for running the immunoassays and the “apparent THCCOOH
concentration” is the average result obtained from the immunoassays.
bThe products are indicated the “immunoassay technology-cutoff level;” the information is not shown on CEDIA package inserts.
cPackage inserts of Emit II Plus Cannabinoids assay, Dade Behring, Inc., June 2001. Three cutoff levels: 100, 50, and 20 ng/mL.
dPackage inserts of AxSYM Cannabinoids assay, Abbott Laboratories, 1997.
ePackage inserts on ONLINE DAT Cannabinoids II assay, Roche Diagnositcs, 2003. The assays were run at three concentrations for each of the three
cutoff levels: 100, 50, and 20 ng/mL.
166 Tsai
Recently, Skopp and colleagues (84,85) published several studies investigating
the stability of free and glucuronidated THC metabolites in plasma and authentic urine
specimens. Formation of free THC-COOH increased with increasing storage temperature
in both plasma and urine. In urine samples, THC-COOH exists primarily as the
glucuronide, and free THC-COOH is present in minute amounts. During storage, THCCOOH
was liberated from its glucuronide in a time- and temperature-dependent manner
(84). The authors reported that the dynamic change in the breakdown of the
glucuronide is of considerable importance for the broad and highly variable changes
observed during storage of authentic samples. The authors also investigated the stability
of cannabinoids in hair samples exposed to sunlight (135). The stability of THC in
oral fluid is also an issue of concern, although commercially available collection devices
generally contain preservative chemicals. In the near future, it is expected that more
studies will be carried out to investigate the stability of cannabinoids in various alternative
specimens.
3.5.5. Hemp Seed/Oil Products, Synthetic THC Medication,
and Drug Testing
The question of whether the consumption of cannabinoid-containing foodstuffs
or cannabinoid-based therapeutics could be used to justify the presence of urinary
THC-COOH has been extensively investigated and reported in the literature
(70,110,136–144). A number of studies in 1997 clearly showed that ingestion of what
were commercially available hemp seed oils could produce positive cannabinoid
immunoassay results for several days (137–140). These screen-positive specimens
were shown to contain THC-COOH by GC/MS in most of the studies (137–139).
Later studies indicated that there has been a significant reduction in the THC concentration
of hemp food products. These studies observed only occasional screen-positive
samples and showed decreased levels of urinary THC-COOH with shortened
detection time (141,142). In addition, the Drug Enforcement Agency (DEA) and Justice
Department added an interpretive rule to 21 CFR Part 1308. DEA interprets the
Controlled Substances Act and DEA regulations to declare any product that contains
any amount of THC to be a schedule I controlled substance, even if such product is
made from portions of the Cannabis plant that are excluded from the Controlled Substances
Act definition of ”marihuana’’ (145). However, a number of sources still exist
globally that may provide hemp oils with considerable THC concentration.
Oral ingestion of prescribed synthetic THC medication (dronabinol [Marinol®])
can also produce positive results for cannabinoid testing. Immunoassays alone cannot
determine if a positive result could be solely a result of the use of synthetic THC.
Importantly, ElSohly et al. (140,141) demonstrated that Δ9-tetrahydrocannabivarin
(THCV), the C3 homolog of Δ9-THC, is a marker for the ingestion of marijuana or a
related product. THCV is a natural product that exists only in Cannabis plants with
THC. Thus, the detection of THCV-COOH in plasma and urine specimens would
indicate the use or ingestion of cannabis-related products and would not support claims
of the sole use of Marinol (143,144).
Recently, Gustafson et al. (70) studied urinary pharmacokinetics of THC-COOH
after controlled clinical study of multiple-dose oral THC administration. Varying THC
Immunoassays to Detect Cannabis Abuse 167
doses were administered through gelatin capsule and liquid hemp oil, along with THC
in sesame oil, to examine effects of dose, vehicle type, and form. The maximum THCCOOH
concentration ranges in urine samples were 7.3–38.2, 5.4–31, 26–436, and 19–
264 ng/mL for THC daily doses of 0.39, 0.47, 7.5, and 14.8 mg, respectively. Following
the administration of these daily THC doses, the mean urinary terminal elimination
half-lives averaged 50.3 ± 17.4, 44.2 ± 19.4, 64.0 ± 22.5, and 52.1 ± 21.8 hours,
respectively.
3.5.6. Cannabinoid-to-Creatinine Ratio Studies
Regardless of the cutoff levels chosen for cannabinoids testing, substantial variabilities
have been observed between subjects and between doses in the excretion
profiles of THC-COOH. Huestis et al. (67) demonstrated that mean detection times in
urine following smoking varied considerably between individuals even in highly controlled
smoking studies. It has been documented that consecutive urine specimens
may fluctuate below and above the cutoff during the terminal elimination phase when
THC-COOH concentrations approach the cutoff (67,71). The normalization of drug
excretion to urine creatinine concentration has been well documented not only to predict
new drug use but also to reduce the variability of drug measurements attributable
to urine dilution (146–150). Gustafson et al. (70) observed an up to fourfold intrasubject
variation across doses and a sixfold intersubject variation for a single dose in terminal
elimination half-lives. However, the authors found no significant effect of creatinine
normalization on pharmacokinetic parameters, half-life, maximum excretion rate, and
time to maximum excretion rate following oral THC administration. The authors also
showed that the apparent urinary elimination half-life of THC-COOH prior to reaching
15 ng/mL concentration was significantly shorter than the terminal urinary elimination
half-life.
3.5.7. Specimen Validity Testing
The normalization of THC metabolite concentration to urine creatinine concentration
has been proven to help address the issue of fluctuating THC-COOH concentration
as a result of specimen donor hydration status. In addition to physiological
fluctuation, intentional dilution of urine specimens in vivo or in vitro may lower the
levels of drug below the threshold for a positive screen result and thus avoid further
testing (151–154). Moreover, attempts to conceal drug abuse by water dilution are
most likely to play a substantial role when concentrations are at or near the detection
threshold, such as the terminal stages of drug eliminations (151–153).
Frazer et al. (151) showed that cannabinoids were among the most often confirmed
drug classes in diluted specimens. The authors recommended the reduction of
the FN rate for DAT by incorporating lower screening and confirmation cutoff levels
for diluted specimens that screened negative using the SAMHSA mandated cutoff
concentrations. Nevertheless, the more direct approach is to test the samples for signs
of dilution or substitution. Cook et al. (154) extensively reviewed the published scientific
literature for the characterization of human urine for specimen validity determination
in workplace drug testing. The authors developed criteria for classifying
submitted urine as substituted, and the criteria were then validated by controlled dehydration
study (154,155).
168 Tsai
Deliberate invalidation of the specimen by chemical adulteration has also been
applied to mask urine screening (156–160). Among the drugs of abuse assays, cannabinoid
testing is the most sensitive to chemical additives, especially to oxidizing
agents, as adulterants that may negatively affect the target analyte for drug testing.
Tsai et al. (158) investigated the interaction of various oxidizing agents with the THC
metabolites under a number of sample matrix conditions and observed a spectrum of
manifestations with regard to their effects on immunoassays and GC/MS analysis.
Paul and Jacobs (160) evaluated different oxidizing adulterants. Several oxidizing
adulterants that are difficult to test by conventional urine adulterant testing methods
showed considerable effects on the destruction of THC-COOH. The time and temperature
for these effects were similar to those used by most laboratories to collect and
test specimens, and the loss of THC-COOH was significant (>94%) in several cases.
In response to the specimen validity issues, SAMHSA and the Department of
Transportation initiated the process to develop standards for testing and reporting of
sample adulteration, substitution, and dilution (66 FR 43876). The revised mandatory
Guidelines for specimen validity testing were published in 2004 (92). Many immunoassay
manufacturers also offer products or utility channels for specimen validity
testing. Alternative matrices are generally perceived as less vulnerable to adulteration
if the sample collection procedures are directly observed. However, there are environmental
contamination and bias concerns for some of the matrices. The scenarios of
passive exposure to marijuana smoking are also being investigated for hair, sweat, and
oral fluid testing. The World Wide Web distributors of adulteration products for urine
testing have been offering an array of adulteration products for hair and saliva /oral
fluid testing. The proposed SAMHSA Guidelines provide specific information and
requirements on conducting specimen validity testing for all alternative specimens
submitted for mandatory drug testing programs (91).
4. CONCLUSIONS
The application of cannabinoid immunoassays as the initial test remains the most
economic and efficient screening tool “to eliminate negative specimens from further
consideration” and “to identify the class of drugs that requires confirmatory test” (90,91).
The regulated cutoff levels provide a uniform approach for the mandated drug-testing
programs. On the other hand, the availability of multiple cutoff choices from the immunoassay
kits provides alternative means for certain drug-testing programs that require
the use of cutoff levels different from regulated workplace drug testing.
Although results from urine drug testing alone are not sufficient to answer many
demanding forensic and clinical questions, the detection and quantification of urinary
cannabinoids have not only provided insights on cannabinoid metabolism but also played
a pivotal role in overall drug-testing programs. A number of immunoassays have been
developed or adapted for detecting cannabis abuse using various biological fluids and
forensic matrices. The technical challenges for detecting cannabinoids in other biological
matrices are higher as compared to urinalysis, and more research and development
are currently ongoing in diverse fields relating to alternative specimen testing.
Regardless of the specimen type tested, it is highly recommended that presumptive
positive results be confirmed to rule out issues of cross-reactivity with
Immunoassays to Detect Cannabis Abuse 169
noncannabinoid compounds. The complexity of cannabinoid chemistry and pharmacokinetics
has challenged the development of immunoassays to meet the diverse goals
of detecting or deterring cannabis abuse. However, various strategies have been
extensively explored for manipulating the antibody selectivity and immunoassay sensitivity
and specificity. Naturally, the results for testing one specimen with different
immunoassay technologies or platforms can vary to some extent because of the different
antibodies and reagent systems used.
Because of the interindividual differences in metabolism, specimens that show
the same apparent THC-COOH concentration as determined by an immunoassay can
produce different THC-COOH concentrations as determined by GC/MS analysis. This
is generally not a real issue for routine drug testing when the majority are either truly
“drug-free” negative specimens (e.g., workplace testing) or high drug concentration
positive specimens (e.g., criminal justice testing). For detecting clinical samples that
contain cannabinoid immunoassay results between the screen cutoff and confirmation
cutoff, a more specific assay may not have adequate sensitivity, whereas a more sensitive
immunoassay may have a higher percentage of unconfirmed positives. A higher
confirmation rate does confer efficiency and economical advantage for the process
that involves large volume drug screening.
Although immunoassays lack the defined specificity of GC/MS, they remain the
only practical means of conducting large-volume screening programs. For routine
workplace drug testing, immunoassays work well in terms of eliminating the bulk of
drug-free samples from further testing. Immunoassays are relatively easy to perform
and do not require sample pretreatment for urinalysis. The values and utilities of these
immunoassays have been supported by the hundreds of millions of samples tested
over the past decades. In addition to qualitative screening, the assays can be run in
semi-quantitative mode to provide an approximate correlation with GC/MS value and
to aid in the estimation of dilution factor needed for conducting GC/MS confirmation.
In conclusion, the key factors that impact the design and performance of cannabinoids
immunoassays may include (1) the chemical characteristics and pharmacokinetics
of cannabinoids, (2) the analytical performance characteristics of the initial and
confirmation testing for the sample matrix of interest, (3) the regulatory requirements
and cutoff choices for both initial screening and confirmatory tests, (4) the analyte
stability and validity of the testing specimen, (5) potential interference from structurally
related compounds, and (6) the goals of drug-testing programs or the relevance to
clinical decisions. The understanding of these factors, together with knowledge of the
analytical screening and confirmation techniques for drug testing, are imperative for
the appropriate interpretation of the drug-testing results.
REFERENCES
1. National Survey on Drug Use and Health, NSDUH. [formerly called the National Household
Survey on Drug Abuse, NHSDA]. (2003) (http://www.oas.samhsa.gov/
nhsda.htm#NHSDAinfo).
2. Martin, B. R. and Hall, W. (1997) The health effects of cannabis: key issues of policy
relevance. United Nations Office on Drugs and Crime. (1997) UNODC Bulletin on Narcotics
- 1997 Issue 1 - 005. (http://www.unodc.org/unodc/fr/bulletin/bulletin_1997-01-
01_1_page005.html).
170 Tsai
3. United Nations International Drug Control Programme. (1997) Cannabis as an illicit narcotic
crop: a review of the global situation of cannabis consumption, trafficking and production.
UNDCP Research Section, 1997 Issue 1. (http://www.unodc.org/unodc/bulletin/
bulletin_1997-01-01_1_page004.html).
4. Rowley, G. L., Armstrong, T. A., Crowl, C. P., et al. (1976) Determination of THC and
its metabolites by EMIT homogeneous enzyme immunoassay: a summary report. NIDA
Res. Monogr. 7, 28–32.
5. Rodgers, R., Crowl, C. P., Eimstad, W. M., et al. (1978) Homogeneous enzyme immunoassay
for cannabinoids in urine. Clin. Chem. 24, 95–100.
6. Abercrombie, M. L. and Jewell, J. S. (1986) Evaluation of EMIT and RIA high volume
test procedures for THC metabolites in urine utilizing GC/MS confirmation. J. Anal.
Toxicol. 10, 178–180.
7. Jolley, M. E., Stroupe, S. D., Schwenzer, K. S., et al. (1981) Fluorescence polarization
immunoassay. iii. an automated system for therapeutic drug determination. Clin. Chem.
27, 1575–1579.
8. Karlsson, L. and Strom, M. (1988) Laboratory evaluation of the TDx assay for detection
of cannabinoids in urine from prison inmates. J. Anal. Toxicol. 12, 319–321.
9. Palmer, S. M., Kaufman, R. A., Salamone, S. J., et al. (1995) Cobas Integra: clinical
laboratory instrument with continuous and random-access abilities. Clin. Chem. 41, 1751–
1760.
10. Smith, J. and Osikowicz, G. (1993) Abbott AxSYM random and continuous access immunoassay
system for improved workflow in the clinical laboratory. Clin. Chem. 39,
2063–2069.
11. Ross, R., Horwitz, C. A., Hager, H., Usategui, M., Burke, M. D., and Ward, P. C. (1975)
Preliminary evaluation of a latex agglutination-inhibition tube test for morphine. Clin.
Chem. 21, 139–143
12. Deom, A. (1984) Evaluation of a new latex agglutination inhibition test, Agglutex, for
the demonstration of opiates in urine. Ann. Biol. Clin. (Paris), 42, 317–319.
13. Armbruster, D. A. and Krolak, J. M. (1992) Screening for drugs of abuse with the Roche
ONTRAK assays. J. Anal. Toxicol. 16, 172–175.
14. Armbruster, D. A., Schwarzhoff, R. H., Hubster, E. C., and Liserio, M. K. (1993) Enzyme
immunoassay, kinetic microparticle immunoassay, radioimmunoassay, and fluorescence
polarization immunoassay compared for drugs-of-abuse screening. Clin. Chem.
39, 2137–2146.
15. Armbruster, D. A., Schwarzhoff, R. H., Pierce, B. L., and Hubster, E. C. (1993) Method
comparison of EMIT II and ONLINE with RIA for drug screening. J. Forensic Sci. 38,
1326–1341.
16. Engel, W. D. and Khanna, P. L. (1992) CEDIA in vitro diagnostics with a novel homogeneous
immunoassay technique. Current status and future prospects. J. Immunol. Methods
150, 99–102.
17. Feldman, M., Kuntz, D., Botelho, K., et al. (2004) Evaluation of Roche Diagnostics
ONLINE DAT II, a new generation of assays for the detection of drugs of abuse.
J.Anal.Toxicol. 28, 593–598.
18. Armbruster, D. A., Hubster, E. C., Kaufman, M. S., and Ramon, M. K. (1995) Cloned
enzyme donor immunoassay (CEDIA) for drugs-of-abuse screening. Clin. Chem. 41, 92–
98.
19. Cleeland, R., Christenson J., Usategui-Gomez M., Heveran J., Davis R., and Grunberg E.
(1976) Detection of drugs of abuse by radioimmunoassay: a summary of published data
and some new information. Clin. Chem. 22, 712–725.
20. Willette, R. E., ed. (1976) Cannabinoid assays in humans. NIDA Res. Monogr. 7. NIDA,
Rockville, MD.
Immunoassays to Detect Cannabis Abuse 171
21. Hawks, R. L., ed. (1982) The analysis of cannabinoids in biological fluids. NIDA Res.
Monogr. 42. NIDA, Rockville, MD.
22. Baselt, R. C. (1984) Urine drug screening by immunoassay: interpretation of results, in
Advances in Analytical Toxicology, Vol. 1 (Baselt, R. C., ed.), Biomedical Publications,
Foster City, CA, pp. 81–123.
23. Huestis, M. A. and Cone, E. J. (2004) Relationship of delta 9-tetrahydrocannabinol concentrations
in oral fluid and plasma after controlled administration of smoked cannabis.
J.Anal.Toxicol. 28, 394–399.
24. Tobin, T., Watt, D. S., Kwiatkowski, S., et al. (1988) Non-isotopic immunoassay drug
tests in racing horses: a review of their application to pre- and post-race testing, drug
quantitation, and human drug testing. Res. Commun. Chem. Pathol. Pharmacol. 62, 371–
395.
25. Moore, K. A., Werner, C., Zannelli, R. M., Levine, B., and Smith, M. L. (1999) Screening
postmortem blood and tissues for nine classes [correction of cases] of drugs of abuse
using automated microplate immunoassay. Forensic Sci. Int. 106, 93–102.
26. Kerrigan, S. and Phillips Jr, W. H. (2001) Comparison of ELISAs for opiates, methamphetamine,
cocaine metabolite, benzodiazepines, phencyclidine, and cannabinoids in
whole blood and urine. Clin. Chem. 47, 540–547.
27. Niedbala, R. S., Kardos, K. W., Fritch, D. F., et al. (2001) Detection of marijuana use by
oral fluid and urine analysis following single-dose administration of smoked and oral
marijuana. J. Anal. Toxicol. 25, 289–303.
28. Cone, E. J., Presley, L., Lehrer, M., et al. (2002) Oral fluid testing for drugs of abuse:
positive prevalence rates by Intercept immunoassay screening and GC-MS-MS confirmation
and suggested cutoff concentrations. J. Anal. Toxicol. 26, 541–546.
29. Niedbala, S., Kardos, K., Salamone, S., Fritch, D., Bronsgeest, M., and Cone, E. J. (2004)
Passive cannabis smoke exposure and oral fluid testing. J.Anal.Toxicol. 28, 546–552.
30. Sharma, J. D., Aherne, G. W., and Marks, V. (1989) Enhanced chemiluminescent enzyme
immunoassay for cannabinoids in urine. Analyst 114, 1279–1282.
31. Willette, R. E. (1986) Choosing a laboratory. NIDA Res. Monogra. 73, 13–19.
32. Finkle, B. S., Blanke, R. V., and Walsh, J. M., eds. (1990) NIDA Technical, Scientific
and Procedural Issues of Employee Drug Testing consensus Report.
33. Transcript On-Site Drug Testing Workgroup Meeting, 1999. (http://
workplace.samhsa.gov/ResourceCenter/r382.htm).
34. An Evaluation of Non-Instrumented Drug Test Devices, Substance Abuse and Mental
Health Services Administration, Center for Substance Abuse Prevention, Division of
Workplace Programs, 1999 (http://workplace.samhsa.gov/ResourceCenter/r409.htm).
35. Department of Transplantation, National Highway Traffic Safety Administration,
NHTSA. (2000). Field test of on-site drug detection devices, DOT HS 809 192. (http://
www.nhtsa.dot.gov/people/injury/research/pub/onsitedetection/Drug_index.htm).
36. Roadside Testing Assessment, ROSITA. (1999). Work package 2, Deliverable D2, Inventory
of state-of-the-art road side drug testing equipment. (www.rosita.org).
37. Jenkins, A. J. and Goldberger, B. A., eds. (2002) On-Site Drug Testing, Humana Press,
Totowa, NJ.
38. Buechler, K. F., Moi, S., Noar, B., et al. (1992) Simultaneous detection of seven drugs of
abuse by the Triage panel for drugs of abuse. Clin. Chem. 38, 1678–1684.
39. Towt, J., Tsai, S. C. J., Hernandez, M. R., et al. (1995) ONTRAK TESTCUP: a novel, onsite,
multi-analyte screen for the detection of abused drugs. J. Anal. Toxicol. 19, 504–
510.
40. Wennig, R., Moeller, M. R., Haguenoer, J. M., et al. (1998) Development and evaluation
of immunochromatographic rapid tests for screening of cannabinoids, cocaine, and opiates
in urine. J. Anal. Toxicol. 22, 148–155.
172 Tsai
41. Yang, J. M. and Lewandrowski, K. B. (2001) Urine drugs of abuse testing at the point-ofcare:
clinical interpretation and programmatic considerations with specific reference to
the Syva Rapid Test (SRT). Clin. Chim. Acta 307, 27–32
42. Jehanli, A., Brannan, S., Moore, L., and Spiehler, V. R. (2001) Blind trials of an onsite
saliva drug test for marijuana and opiates. Forensic Sci. Int. 46, 1214–1220.
43. Gronholm, M. and Lillsunde, P., (2001) A comparison between on-site immunoassay
drug-testing devices and laboratory results. Forensic Sci. Int. 121, 37–46.
44. Peace, M. R., Poklis, J. L., Tarnai, L. D., and Poklis, A. (2002) An evaluation of the
OnTrak Testcup-er on-site urine drug-testing device for drugs commonly encountered
from emergency departments. J. Anal. Toxicol. 26, 500–503.
45. Walsh, J. M., Flegel, R., Crouch, D. J., Cangianelli, L., and Baudys, J. (2003) An evaluation
of rapid point-of-collection oral fluid drug-testing devices. J. Anal. Toxicol. 27,
429–439.
46. Weiss, A. (1999) Concurrent engineering for lateral-flow diagnostics. IVD Technology 5, 48–57.
47. Klimov, A.D., Tsai, S-C. J., Towt, J., and Salamone, S. J. (1995) Improved immunochromatographic
format for competitive-type assays. Clin. Chem. 41, 1360.
48. Niedbala, R. S., Feindt, H., Kardos, K., et al. (2001) Detection of analytes by immunoassay
using up-converting phosphor technology. Anal. Biochem. 293, 22.
49. Reynolds, L. A. (2001). What you should know about on-site saliva drug and alcohol
testing. Occup. Health Saf. 70, 188–190.
50. Tsai, J.S.C., Deng, D., Diebold, E., Smith, A., Wentzel, C. and Franzke, S. (2002) The
latest development in biosensor immunoassay technology for drug assays. LABOLife 4/
02, 17–20.
51. Emergency Department Trends From DAWN: Final Estimates 1995–2002. http://
dawninfo.samhsa.gov/pubs_94_02/edpubs/2002final/The DAWN Report, Major drugs of
abuse in ED visits, 2002 update. http://dawninfo.samhsa.gov/pubs_94_02/shortreports/
files/DAWN_tdr_MDA.pdf.
52. Quest Diagnostics’ Drug Testing Index. http://www.questdiagnostics.com/
employersolutions/dti_archives.html.
53. Turner, C. E., Elsohly, M. A., and Boeren, E. G. (1980) Constituents of Cannabis sativa
L. XVII. A review of the natural constituents. J. Nat Prod. 43, 169–234.
54. Razdan, R. K. (1987) Structure-activity relationship in cannabinoids: an overview. NIDA
Res. Monogr. 79, 3–14.
55. Adams, I. B. and Martin, B. R. (1996) Cannabis: pharmacology and toxicology in animals
and humans. Addiction 91, 1585–1614
56. Mechoulam, R. and Hanus, L. (2000) A historical overview of chemical research on cannabinoids.
Chem Phys Lipids 108, 1–13.
57. Martin, B. R. (2002) Identification of the endogenous cannabinoid system through integrative
pharmacological approaches. J. Pharmacol Exp Ther. 301, 790–796.
58. Martin, B. R. (1986) Cellular effects of cannabinoids. Pharmacol Rev. 38, 45–74.
59. ElSohly, M. A., Ross, S. A., Mehmedic, Z., Arafat, R., Yi, B., and Banahan, B. F., 3rd
(2000) Potency trends of delta9-THC and other cannabinoids in confiscated marijuana
from 1980-1997. J. Forensic Sci. 45, 24–30.
60. Ross, S. A., Mehmedic, Z., Murphy, T. P., and Elsohly, M. A. (2000) GC-MS analysis of
the total delta9-THC content of both drug- and fiber-type cannabis seeds. J. Anal. Toxicol.
24, 715–717.
61. Perez-Reyes, M., Di Guiseppi, S., Davis, K. H., Schindler, V. H., and Cook, C. E. (1982)
Comparison of effects of marihuana cigarettes to three different potencies. Clin.
Pharmacol Ther. 31, 617–624
62. Chiang, C. N. and Rapaka, R. S. (1987) Pharmacokinetics and disposition of cannabinoids.
NIDA Res. Monogr. 79, 173–188.
Immunoassays to Detect Cannabis Abuse 173
63. Perez-Reyes, M. (1990) Marijuana smoking: factors that influence the bioavailability of
tetrahydrocannabinol. NIDA Res. Monogr. 99, 42–62.
64. Huestis, M. A., Henningfield, J. E., and Cone, E. J. (1992) Blood cannabinoids. I. Absorption
of THC and formation of 11-OH-THC and THCCOOH during and after smoking
marijuana. J. Anal. Toxicol. 16, 276–282.
65. Huestis, M. A., Henningfield, J. E., and Cone, E. J. (1992) Blood cannabinoids. II. Models
for the prediction of time of marijuana exposure from plasma concentrations of delta
9-tetrahydrocannabinol (THC) and 11-nor-9-carboxy-delta 9-tetrahydrocannabinol
(THCCOOH). J. Anal. Toxicol. 16, 283–290
66. Cone, E. J., and Huestis, M. A. (1993) Relating blood concentrations of tetrahydrocannabinol
and metabolites to pharmacologic effects and time of marijuana usage. Ther.
Drug Monit. 15, 527–532.
67. Huestis, M. A., Mitchell, J. M., and Cone, E. J. (1996) Urinary excretion profiles of 11-
nor-9-carboxy-delta 9-tetrahydrocannabinol in humans after single smoked doses of marijuana.
J. Anal. Toxicol. 20, 441–452.
68. Huestis, M. A. and Cone, E. J. (1998). Urinary excretion half-life of 11-nor-9-carboxydelta9-
tetrahydrocannabinol in humans. Ther. Drug Monit. 20, 570–576.
69. Manno, J. E., Manno, B. R., Kemp, P. M., et al. (2001) Temporal indication of marijuana
use can be estimated from plasma and urine concentrations of delta9-tetrahydrocannabinol,
11-hydroxy-delta9-tetrahydrocannabinol, and 11-nor-delta9-tetrahydrocannabinol-
9-carboxylic acid. J. Anal. Toxicol. 25, 538–549.
70. Gustafson, R. A., Kim, I., Stout, P. R., et al. (2004) Urinary pharmacokinetics of 11-nor-
9-carboxy-delta9-tetrahydrocannabinol after controlled oral delta9-tetrahydrocannabinol
administration. J. Anal. Toxicol. 28, 160–167.
71. Smith-Kielland, A., Skuterud, B., and Morland, J. (1999) Urinary excretion of 11-nor-9-
carboxy-delta9-tetrahydrocannabinol and cannabinoids in frequent and infrequent drug
users. J. Anal. Toxicol. 23, 323–332
72. ElSohly, M. A. (2003) Practical challenges to positive drug tests for marijuana. Clin.
Chem. 49, 1037–1038.
73. Harvey, D. J. and Brown, N. K. (1991) Comparative in vitro metabolism of the cannabinoids.
Pharmacol Biochem Behav. 40, 533–540.
74. Yamamoto, I., Watanabe, K., Narimatsu, S., and Yoshimura, H. (1995) Recent advances
in the metabolism of cannabinoids. Int J. Biochem Cell Biol. 27, 741–746.
75. Matsunaga, T., Tanaka, H., Higuchi, S., et al. (2001) Oxidation mechanism of 7-hydroxydelta
8-tetrahydrocannabinol and 8-hydroxy-delta 9-tetrahydrocannabinol to the corresponding
ketones by CYP3A11. Drug Metab Dispos. 29, 1485–1491.
76. Watanabe, K., Matsunaga, T., Yamamoto, I., Funae, Y., and Yoshimura, H. (1995) Involvement
of CYP2C in the metabolism of cannabinoids by human hepatic microsomes
from an old woman. Biol Pharm Bull. 18, 1138–1141.
77. Watanabe, K., Narimatsu, S., Yamamoto, I., and Yoshimura, H. (1991) Oxygenation
mechanism in conversion of aldehyde to carboxylic acid catalyzed by a cytochrome P-
450 isozyme. J. Biol Chem. 266, 2709–2711.
78. Alburges, M. E. and Peat, M. A. (1986) Profiles of delta 9-tetrahydrocannabinol metabolites
in urine of marijuana users: preliminary observations by high performance liquid
chromatography-radioimmunoassay. J. Forensic Sci. 31, 695–706.
79. ElSohly, M. A. and Feng, S. (1998) Delta 9-THC metabolites in meconium: identification
of 11-OH-delta 9-THC, 8 beta,11-diOH-delta 9-THC, and 11-nor-delta 9-THC-9-
COOH as major metabolites of delta 9-THC. J. Anal. Toxicol. 22, 329–335.
80. Feng, S., ElSohly, M. A., Salamone, S., and Salem, M. Y. (2000) Simultaneous analysis
of delta9-THC and its major metabolites in urine, plasma, and meconium by GC-MS
using an immunoaffinity extraction procedure. J. Anal. Toxicol. 24, 395–402.
174 Tsai
81. Gustafson, R. A., Moolchan, E. T., Barnes, A., Levine, B., and Huestis, M. A. (2003)
Validated method for the simultaneous determination of Delta 9-tetrahydrocannabinol
(THC), 11-hydroxy-THC and 11-nor-9-carboxy-THC in human plasma using solid phase
extraction and gas chromatography-mass spectrometry with positive chemical ionization.
J. Chromatogr B Analyt Technol Biomed Life Sci. 798, 145–154.
82. Kemp, P. M., Abukhalaf, I. K., Manno, J. E., Manno, B. R., Alford, D. D., and Abusada,
G. A. (1995) Cannabinoids in humans. I. Analysis of delta 9-tetrahydrocannabinol and
six metabolites in plasma and urine using GC-MS. J. Anal. Toxicol. 19, 285–291.
83. Kemp, P. M., Abukhalaf, I. K., Manno, J. E., et al. (1995) Cannabinoids in humans. II.
The influence of three methods of hydrolysis on the concentration of THC and two metabolites
in urine. J. Anal. Toxicol. 19, 292–298.
84. Skopp, G., Potsch, L., Mauden, M., and Richter, B. (2002) Partition coefficient, blood to
plasma ratio, protein binding and short-term stability of 11-nor-delta(9)-carboxy tetrahydrocannabinol
glucuronide. Forensic Sci. Int. 126, 17–23.
85. Skopp, G. and Potsch, L. (2004) An investigation of the stability of free and
glucuronidated 11-nor-delta9-tetrahydrocannabinol-9-carboxylic acid in authentic urine
samples. J. Anal. Toxicol. 28, 35–40
86. Weinmann, W., Vogt, S., Goerke, R., Muller, C., and Bromberger, A. (2000) Simultaneous
determination of THC-COOH and THC-COOH-glucuronide in urine samples by
LC/MS/MS. Forensic Sci. Int. 113, 381–387.
87. Salamone, S. J., Bender, E., Hui, R. A., and Rosen, S. (1998) A non-cannabinoid immunogen
used to elicit antibodies with broad cross-reactivity to cannabinoid metabolites. J.
Forensic Sci. 43, 821–826.
88. Patent families for cannabinoids immunoassays (Abbott Laboratories). Representative
US patents for each of the patent families include: US 5,144,030 (1992); US 5,264,373
(1993); US 5,463,027 (1995).
89. Patent families for cannabinoids immunoassays (Hoffman La Roche / Roche Diagnostics).
Representative US patents for each of the patent families include: US 4,438,207
(1984); US 4,833,073 (1989); US 5,219,747 (1993); US 5,315,015 (1994); US 5,817766
(1998).
90. Mandatory guidelines for federal workplace drug testing programs (1994) Fed. Reg. 59,
29908 (http://www.health.org/workplace/GDLNS-94.htm) or (http://workplace.samhsa.
gov/fedprograms/MandatoryGuidelines/HHS09011994.pdf).
91. Proposed Revisions to Mandatory Guidelines for Federal Workplace Drug Testing Programs
(2004) Fed. Reg. 69, 19673–19732.(http://a257.g.akamaitech.net/7/257/2422/
14mar20010800/edocket.access.gpo.gov/2004/pdf/04-7984.pdf).
92. Revised Mandatory Guidelines for Federal Workplace Drug Testing Programs, Specimen
Validity Testing (2004) Fed. Reg. 69, 19644–19673.http://a257.g.akamaitech.net/7/
257/2422/14mar20010800/edocket.access.gpo.gov/2004/pdf/04-7985.pdf.
93. Badia, R., Segura, J., Artola, A., and de la Torre, R. (1998) Survey on drugs-of-abuse
testing in the European Union. J. Anal. Toxicol. 22, 117–126.
94. Corcione, S., Pichini, S., Badia, R., Segura, J., and de la Torre, R. (1999) Quantitative
aspects of drugs of abuse in urine samples: intercollaborative studies conducted in the
European Union. Ther. Drug Monit. 21, 653–660.
95. Wilson, J. F. and Smith, B. L. (1999) Evaluation of detection techniques and laboratory
proficiency in testing for drugs of abuse in urine: an external quality assessment scheme
using clinically realistic urine samples. Steering Committee for the United Kingdom National
External Quality Assessment Scheme for Drugs of Abuse in Urine. Ann Clin.
Biochem. 36, 592–600.
96. AGSA Swiss Working Group for Drugs of Abuse Testing Guidelines. (2003)(http://
www.consilia-sa.ch/agsa/E/AGSA%20Guidelines_E_rev3.pdf).
Immunoassays to Detect Cannabis Abuse 175
97. Verstraete, A. G. and Pierce, A. (2001) Workplace drug testing in Europe. Forensic Sci.
Int. 121, 2–6.
98. EWDTS (European Workplace Drug Testing Society) Laboratory Guidelines. (2002)
http://www.ewdts.org/guidelines.html.
99. Ferrara, S. D., Tedeschi, L., Frison, G., et al. (1994) Drugs-of-abuse testing in urine:
statistical approach and experimental comparison of immunochemical and chromatographic
techniques. J. Anal. Toxicol. 18, 278–291.
100. Rowland, B. J., Irving, J., and Keith, E. S. (1994) Increased detection of marijuana use
with a 50 micrograms/L urine screening cutoff. Clin. Chem. 40, 2114–2115.
101. Huestis, M. A., Mitchell, J. M., and Cone, E. J. (1994) Lowering the federally mandated
cannabinoid immunoassay cutoff increases true-positive results. Clin. Chem. 40, 729–
733.
102. Wingert, W. E. (1997) Lowering cutoffs for initial and confirmation testing for cocaine
and marijuana: large-scale study of effects on the rates of drug-positive results. Clin.
Chem. 43, 100–103.
103. Weaver, M. L., Gan, B. K., Allen, E., et al. (1991) Correlations on radioimmunoassay,
fluorescence polarization immunoassay, and enzyme immunoassay of cannabis metabolites
with gas chromatography/mass spectrometry analysis of 11-nor-delta 9-tetrahydrocannabinol-
9-carboxylic acid in urine specimens. Forensic Sci. Int. 49, 43–56.
104. Liu, R. H., Edwards, C., Baugh, L. D., Weng, J. L., Fyfe, M. J., and Walia, A. S. (1994)
Selection of an appropriate initial test cutoff concentration for workplace drug urinalysis—
Cannabis example. J. Anal. Toxicol. 18, 65–70.
105. Brendler, J. and Liu, R. H. (1997) Initial test cutoff selection based on regression analysis
of initial test apparent analyte result vs GC/MS test analyte result—evaluation of
two radioimmunoassay kits’ test data. Clin. Chem. 43, 688–690.
106. Cone, E. J, Johnson, R. E., Darwin, W. D., et al. (1987) Passive inhalation of marijuana
smoke: urinalysis and room air levels of delta-9-tetrahydrocannabinol. J. Anal. Toxicol.
11, 89–96.
107. Cone, E. J. (1990) Marijuana effects and urinalysis after passive inhalation and oral ingestion.
NIDA Res. Monogr. 99, 88–96.
108. ElSohly, M. A. and Jones, A. B. (1995) Drug testing in the workplace: could a positive
test for one of the mandated drugs be for reasons other than illicit use of the drug? J. Anal.
Toxicol. 19, 450–458.
109. Lyons, T. P., Okano, C. K., Kuhnle, J. A., et al. (2001) A comparison of Roche Kinetic
Interaction of Microparticles in Solution (KIMS) assay for cannabinoids and GC-MS analysis
for 11-nor-9-carboxy-delta9-tetrahydrocannabinol. J. Anal. Toxicol. 25, 559–564.
110. Gustafson, R. A., Levine, B., Stout, P. R., et al. (2003) Urinary cannabinoid detection
times after controlled oral administration of delta9-tetrahydrocannabinol to humans. Clin.
Chem. 49, 1114–1124
111. Luzzi, V. I., Saunders, A. N., Koenig, J. W., et al. (2004) Analytic performance of immunoassays
for drugs of abuse below established cutoff values. Clin. Chem. 50, 717–722.
112. Hattab, E. M., Goldberger, B. A., Johannsen, L. M., et al. (2000) Modification of screening
immunoassays to detect sub-threshold concentrations of cocaine, cannabinoids, and
opiates in urine: use for detecting maternal and neonatal drug exposure. Ann. Clin. Lab.
Sci. 30, 85–91
113. Kintz, P., Cirimele, V., and Ludes, B. (2000) Detection of cannabis in oral fluid (saliva)
and forehead wipes (sweat) from impaired drivers. J. Anal. Toxicol. 24, 557–561.
114. Samyn, N., De Boeck, G., and Verstraete, A. G. (2002) The use of oral fluid and sweat
wipes for the detection of drugs of abuse in drivers. Forensic Sci. Int. 47, 1380–1387.
115. Moore, C. and Lewis, D. (2003) Comment on oral fluid testing for drugs of abuse: positive
prevalence rates by Intercept immunoassay screening and GC-MS-MS confirmation
176 Tsai
and suggested cutoff concentrations. J. Anal. Toxicol. 27, 169 (author reply, J. Anal.
Toxicol. 27, 170–172).
116. Spiehler, V. (2004) Comment on “An evaluation of rapid point-of-collection oral fluid
drug-testing devices.” J. Anal. Toxicol. 28, 75–76 (author reply, J. Anal. Toxicol. 28, 76).
117. Sachs, H. (1997) Quality control by the Society of Hair Testing. Forensic Sci. Int. 84,
145–150.
118. Jurado, C. and Sachs, H. (2003) Proficiency test for the analysis of hair for drugs of
abuse, organized by the Society of Hair Testing. Forensic Sci. Int. 133, 175–178.
119. Thorspecken, J., Skopp, G., and Potsch, L. (2004) In vitro contamination of hair by marijuana
smoke. Clin. Chem. 50, 596–602.
120. Wolff, K., Farrell, M., Marsden, J., et al. (1999) A review of biological indicators of
illicit drug use, practical considerations and clinical usefulness. Addiction 94, 1279–1298.
121. Cone, E. J. (2001) Legal, workplace, and treatment drug testing with alternative biological
matrices on a global scale. Forensic Sci. Int. 121, 7–15.
122. lan, Y. H. and Goldberger, B. A. (2001) Alternative specimens for workplace drug testing.
J. Anal. Toxicol. 25, 396–399
123. Armbruster, D. A., Tillman, M. D., and Hubbs, L. M. (1994) Limit of detection (LQD)/
limit of quantitation (LOQ): comparison of the empirical and the statistical methods exemplified
with GC-MS assays of abused drugs. Clin. Chem. 40, 1233–1238.
124. Goldberger, B. A. and Cone, E. J. (1994) Confirmatory tests for drugs in the workplace
by gas chromatography-mass spectrometry. J. Chromatogr. A 674, 73–86.
125. Wu, A. H. (1995) Mechanism of interferences for gas chromatography/mass spectrometry
analysis of urine for drugs of abuse. Ann Clin. Lab Sci. 25, 319–329.
126. Underwood, P. J., Kananen, G. E., and Armitage, E. K. (1997) A practical approach to
determination of laboratory GC-MS limits of detection. J. Anal. Toxicol. 21, 12–16.
127. Lehrer, M. (1998) The role of gas chromatography/mass spectrometry. Instrumental techniques
in forensic urine drug testing. Clin. Lab Med. 184, 631–649.
128. Haver, V. M., Romson, J. L., and Sadrzadeh, S. M. (1991) Semiquantitation of cannabinoid
immunoassays? A reexamination of the EMIT 20-ng/mL assay. J. Anal. Toxicol. 15, 98–100.
129. Blanc, J. A., Manneh, V. A., Ernst, R., et al. (1993) Adsorption losses from urine-based
cannabinoid calibrators during routine use. Clin. Chem. 39, 1705–1712.
130. Paul, B. D., McKinley, R. M., Walsh, J. K. Jr, Jamir, T. S., and Past, M. R. (1993) Effect
of freezing on the concentration of drugs of abuse in urine. J. Anal. Toxicol. 17, 378–380.
131. Romberg, R. W. and Past, M. R. (1994) Reanalysis of forensic urine specimens containing
benzoylecgonine and THC-COOH. J. Forensic Sci. 39, 479–485.
132. Dugan, S., Bogema, S., Schwartz, R. W., and Lappas, N. T. (1994) Stability of drugs of
abuse in urine samples stored at -20 degrees C. J. Anal. Toxicol. 18, 391–396.
133. Roth, K. D., Siegel, N. A., Johnson, R. W., Jr., et al. (1996) Investigation of the effects of
solution composition and container material type on the loss of 11-nor-delta 9-THC-9-
carboxylic acid. J. Anal. Toxicol. 20, 291–300.
134. Moody, D. E., Monti, K. M., and Spanbauer, A. C. (1999) Long-term stability of abused
drugs and antiabuse chemotherapeutical agents stored at -20 degrees C. J. Anal. Toxicol.
23, 535–540.
135. Skopp, G., Potsch, L., and Mauden, M. (2000) Stability of cannabinoids in hair samples
exposed to sunlight. Clin. Chem. 46, 1846–1848.
136. Cone, E. J., Johnson, R. E., Paul, B. D., Mell, L. D., and Mitchell, J. (1988) Marijuanalaced
brownies: behavior effects, physiologic effects, and urinalysis in humans following
ingestion. J. Anal. Toxicol. 12, 169–175.
137. Costantino, A., Schwartz, R. H., and Kaplan, P. (1997) Hemp oil ingestion causes positive
urine tests for delta 9-tetrahydrocannabinol carboxylic acid. J. Anal. Toxicol. 21,
482–485.
Immunoassays to Detect Cannabis Abuse 177
138. Struempler, R. E., Nelson, G., and Urry, F. M. (1997) A positive cannabinoids workplace
drug test following the ingestion of commercially available hemp seed oil. J. Anal.
Toxicol. 21, 283–285.
139. Lehmann, T., Sager, F., and Brenneisen, R. (1997) Excretion of cannabinoids in urine
after ingestion of cannabis seed oil. J. Anal. Toxicol. 21, 373–375.
140. Fortner, N., Fogerson, R., Lindman, D., Iversen, T., and Armbruster, D. (1997) A marijuana-
positive urine test results from consumption of hemp seeds in food products. J.
Anal. Toxicol. 21, 476–481.
141. Bosy, T. Z. and Cole, K. A. (2000) Consumption and quantitation of delta9-tetrahydrocannabinol
in commercially available hemp seed oil products. J. Anal. Toxicol. 24, 562–
566.
142. Leson, G., Pless, P., Grotenhermen, F., Kalant, H., and ElSohly, M. A. (2001) Evaluating
the impact of hemp food consumption on workplace drug tests. J. Anal. Toxicol. 25, 691–
698.
143. ElSohly, M. A., deWit, H., Wachtel, S. R., Feng, S., and Murphy, T. P. (2001) Delta9-
tetrahydrocannabivarin as a marker for the ingestion of marijuana versus Marinol: results
of a clinical study. J. Anal. Toxicol. 25, 565–571.
144. ElSohly, M. A., Feng, S., Murphy, T. P., et al. (2001) Identification and quantitation of
11-nor-delta9-tetrahydrocannabivarin-9-carboxylic acid, a major metabolite of delta9-
tetrahydrocannabivarin. J. Anal. Toxicol. 25, 476–480.
145. Interpretation and clarification of listing of “tetrahydrocannabinols” in Schedule I; exemption
from control of certain industrial products and materials derived from the Cannabis
plant; final rules and proposed rulInterpretive rule (2001) Fed. Reg. 66,
51529–51544.
146. Huestis, M. A. and Cone, E. J. (1998) Differentiating new marijuana use from residual
drug excretion in occasional marijuana users. J. Anal. Toxicol. 22, 445–454.
147. Lafolie, P., Beck, O., Blennow, G., et al. (1991) Importance of creatinine analyses of
urine when screening for abused drugs. Clin. Chem. 37, 1927–1931.
148. Fraser, A. D. and Worth, D. (1999) Urinary excretion profiles of 11-nor-9-carboxy-delta9-
tetrahydrocannabinol: a delta9-THCCOOH to creatinine ratio study. J. Anal. Toxicol. 23,
531–534
149. Fraser, A. D. and Worth, D. (2002) Monitoring urinary excretion of cannabinoids by
fluorescence-polarization immunoassay: a cannabinoid-to-creatinine ratio study. Ther
Drug Monit. 24, 746–750.
150. Fraser, A. D. and Worth, D. (2003) Urinary excretion profiles of 11-nor-9-carboxy-delta9-
tetrahydrocannabinol: a delta9-THC-COOH to creatinine ratio study #2. Forensic Sci.
Int. 133, 26–31.
151. Fraser, A. D. and Zamecnik, J. (2003) Impact of lowering the screening and confirmation
cutoff values for urine drug testing based on dilution factors. Ther. Drug Monit. 25, 723–
727.
152. Cone, E. J., Lange, R., and Darwin, W. D. (1998) In vivo adulteration: excess fluid ingestion
causes false-negative marijuana and cocaine urine test results. J. Anal. Toxicol. 22,
460–473.
153. Coleman, D. E. and Baselt, R. C. (1997) Efficacy of two commercial products for altering
urine drug test results. J. Toxicol. Clin. Toxicol. 35, 637–642.
154. Cook, J. D., lan, Y. H., LoDico, C. P., and Bush, D. M. (2000). The characterization of
human urine for specimen validity determination in workplace drug testing: a review. J.
Anal. Toxicol. 24, 579–588.
155. Edgell, K., lan, Y. H., Glass, L. R., and Cook, J. D. (2002) The defined HHS/DOT substituted
urine criteria validated through a controlled hydration study. J. Anal. Toxicol. 26,
419–423.
178 Tsai
156. Wong, R. (2002) The effect of adulterants on urine screen for drugs of abuse: detection
by an on-site dipstick device. Am. Clin. Lab. 21, 37–39.
157. Pearson, S. D., Ash, K. O, and Urry, F. M. (1989) Mechanism of false-negative urine
cannabinoid immunoassay screens by Visine eyedrops. Clin. Chem. 35, 636–638.
158. Tsai, J. S., ElSohly, M. A., Tsai, S. F., Murphy, T. P., Twarowska, B., and Salamone, S.
J. (2000) Investigation of nitrite adulteration on the immunoassay and GC-MS analysis
of cannabinoids in urine specimens. J. Anal. Toxicol. 24, 708–714.
159. Cody, J. T. and Valtier, S. (2001) Effects of stealth adulterant on immunoassay testing for
drugs of abuse. J. Anal. Toxicol. 25, 466–470.
160. Paul, B. D. and Jacobs, A. (2004) Effects of oxidizing adulterants on detection of 11-nordelta9-
THC-9-carboxylic acid in urine. J. Anal. Toxicol. 26, 460–463.
MS for Detection of Cannabinoids 179
From: Forensic Science and Medicine: Marijuana and the Cannabinoids
Edited by: M. A. ElSohly © Humana Press Inc., Totowa, New Jersey
179
Chapter 8
Mass Spectrometric Methods
for Determination of Cannabinoids
in Physiological Specimens
Rodger L. Foltz
1. INTRODUCTION
This chapter describes the published mass spectrometric (MS) methods that have
proven most effective for quantitative measurement of Δ9-tetrahydrocannabinol (THC)
and its major metabolites in physiological specimens. Because determination of 11-
nor-9-carboxy- Δ9-tetrahydrocannabinol (THCA) in urine continues to be the most frequently
used indicator of marijuana use, the first portion of the chapter will discuss
methods for measurement of THCA in urine. However, the major portion of the chapter
is devoted to the most recent developments for measuring THC and its metabolites
in other biological specimens including blood, plasma, meconium, oral fluids, hair,
and other tissues. Tables 1–7 are designed to facilitate location of references describing
analytical methods involving key components for analysis of cannabinoids in various
matrices.
Analysis of THC and its metabolites in biological specimens has been reviewed
by Lindgren (1), Foltz (2), Bronner and Xu (3), Goldberger and Cone (4), Cody and
Foltz (5), and Staub (6).
The selection of internal standards is an important factor in the development of
quantitative assays involving MS. Because of the demand for effective internal standards
for MS analysis of THC and its major metabolites, a variety of deuterium-labeled
analogs have become commercially available. THC-d3, THCA-d3, and trideuterated
11-hydroxy-Δ9-tetrahydrocannabinol (HO-THC-d3) have often been used as internal
180 Foltz
standards. However, cannabinoid analogs with more than three deuteriums (THC-d6,
THC-d9, THCA-d6, THCA-d9, THCA-d10, and HO-THC-d6) are reported to be even
more effective as internal standards (7–10).
2. DETERMINATION OF THCA IN URINE
THCA is primarily excreted in urine as the ester-linked glucuronide conjugate.
Consequently, the urine is most often subjected to mild alkaline hydrolysis to release
the THCA (11,12). Enzymatic hydrolysis using β-glucuronidase can also free the THCA
from the conjugate, but the procedure takes considerably longer than alkaline hydrolysis
(13,14). After hydrolysis the urine is acidified and extracted by either liquid/liquid or
solid-phase extraction (SPE). A solvent mixture of hexane and ethyl acetate, typically
7:1 (v/v), has been used most often for extraction of free THCA in urine (11). A wide
variety of solid-phase systems are also available for extraction of THCA in urine (10,15–
24), and two research groups have selectively extracted THCA from urine by means
of immobilized antibodies (8,25).
THCA has two polar functional groups that must be derivatized prior to gas chromatography
(GC)/MS analysis. The carboxyl group and the phenolic group can both
be derivatized by trimethylsilylation or by methylation. Trimethylsilylation is most
often performed by adding bis-(trimethylsilyl)-trifluoroacetamide (BSTFA) with 1%
trimethylchlorosilane (TMCS) to the dried extract and heating at approx 70°C for 20
minutes, followed by direct injection into the GC/MS system (17,18). Methylation is
generally performed by addition of methyl iodide in the presence of tetramethylammonium
hydroxide (TMAH) in dimethyl sulfoxide (16,26). Some investigators have
used propyl iodide when interference problems were encountered after derivatizing
with methyl iodide (27); others have used a perfluorinated anhydride and a
perfluorinated alcohol (10,24,28,29). The latter protocol can provide increased sensitivity,
particularly when the derivatives are detected by negative ion chemical ionization
mass spectrometry (GC/NCI-MS; ref. 28). However, it is important to remove the
perfluorinated anhydride reagent by evaporation prior to reconstitution and injection
into the GC/MS because the anhydride tends to degrade the chromatographic column.
Szirmai and co-workers compared five different methods for derivatization of
THCA and two other acidic metabolites of THC in urine (9). Two of the methods
involved esterification of the carboxylic acid group with diazomethane followed by
trimethylsilyation or trifluoroacetylation of the phenolic group; the other three methods
employed (1) BSTFA alone, (2) methyl iodide-TMAH, or (3) pentafluoropropionic
anhydride (PFPA) and trifluoroethanol.
Nearly all GC/MS assays for determination of THCA in urine employ fused silica
capillary columns with methyl silicone or 5% phenylmethylsilicone stationary phases.
Electron ionization (EI) continues to be the dominant method for ionizing derivatized
THCA. With EI-MS, each of the reported THCA derivatives yields at least three ions
with high relative intensities, an important benefit in forensic analyses.
The first published liquid chromatography (LC)/MS assay for determination of
THCA in urine employed positive ion electrospray ionization (ESI; ref. 30). Under
selected ion monitoring the protonated molecule ion (M + H)+ at m/z 345 was dominant
and could be detected down to 2.5 ng/mL. Up-front collision-induced dissociaMS
for Detection of Cannabinoids 181
tion generated qualifying ions at m/z 327 and 299, but their ion intensities were relatively
low and thereby increased the lower limit of detection to 15 ng/mL. Significantly
better sensitivity has been achieved by monitoring the (M – H)– ions for THCA
(m/z 343) and THCA-d3 (m/z 346) formed by ESI (23).
Weinmann and co-investigators (21) developed a very rapid LC/MS/MS assay
for THCA in urine using negative ion atmospheric pressure chemical ionization (APCI)
in combination with selected-reaction monitoring. When subjected to collision-induced
dissociation, the (M – H)– ion at m/z 343 fragmented to abundant ions at m/z 325, 299,
and 245. The runtime took 6 minutes, and the lower limit of quantitation was 5 ng/mL.
Investigators in the same laboratory reported using positive-ion turboionspray to
determine THCA and THCA glucuronide in urine by LC/MS/MS (31).
Skopp and Potsch used LC/MS/MS to study the stability of THCA and THCAglucuronide
in urine and plasma stored at temperatures of –20, 4, 20, and 40°C (32).
The analytes and their deuterated internal standards were ionized by turboionspray,
and the protonated molecule ions collisionally dissociated to abundant product ions.
Unfortunately, THCA and other cannabinoids are not as efficiently ionized by
either ESI or APCI as most other drugs. Nevertheless, the advantage of not having to
derivatize an analyte prior to analysis is an inducement to utilize LC/MS rather than
GC/MS.
Potential problems that can occur in determination of THCA in urine include
interferences (27,33), adsorptive losses during storage and extraction (12,29,34–36),
and degradation of THCA as a result of adulteration of a urine sample (37).
3. DETERMINATION OF OTHER CANNABINOIDS IN URINE
Although detection of THCA in urine continues to be the primary method for
identifying recent use of marijuana, Manno and Manno and their co-investigators have
shown that THC and other metabolites of THC are also excreted in urine as glucuronide
conjugates that are not, however, as easily hydrolyzed as THCA glucuronide
(38,39). THC and its hydroxylated metabolites are excreted in urine primarily as etherlinked
glucuronide conjugates that do not undergo hydrolysis under alkaline conditions.
Enzymatic hydrolysis using β-glucuronidase from Escherichia coli at a pH of
6.8 is highly effective in cleaving ether-linked glucuronide conjugates. Manno et al.
have used this method for quantitative analysis of cannabidiol, cannabinol, THC, and
six THC metabolites in plasma and urine. After enzymatic hydrolysis, they extracted
the cannabinoids with hexane:ethyl acetate (7:1), derivatized them with BSTFA, and
analyzed the products by electron ionization GC/MS. Analysis of urine samples by
this method proved useful for estimating the time of marijuana use (14).
GC/MS analysis for 11-nor-Δ9-tetrahydrocannabivarin-9-carboxylic acid
(THCVA) has been used to determine whether the presence of THCA in a subject’s
urine indicates the use of marijuana or is solely the result of the use of the prescription
drug Marinol® (synthetic THC; ref. 40). Δ9-Tetrahydrocannabivarin, a homolog of THC,
is present in most marijuana and is metabolized in the body to THCVA (41). Because
THCVA is a homolog of THCA, the two compounds behave very similarly during
extraction and derivatization but have different retention times and form abundant
ions that differ by 28 amu (40).
182 Foltz
4. DETERMINATION OF CANNABINOIDS IN BLOOD OR PLASMA
Cannabinoid concentrations in urine are not very useful for determining impairment
or recent use of marijuana. Therefore, in forensic cases it is important to measure
cannabinoid concentrations in blood or plasma, particularly the concentrations of
THC and HO-THC, the two psychoactive cannabinoids. However, analysis of cannabinoids
in blood or plasma is complicated by the difficulty of separating the cannabinoids
from the abundance of endogenous lipophilic and proteinaceous compounds
in blood that are not generally present in urine. Furthermore, concentrations of THC
and HO-THC in blood decrease rapidly after smoking marijuana or after oral ingestion
of cannabinoids.
Most published methods for determination of cannabinoids in blood or plasma
have not included enzymatic hydrolysis of glucuronide conjugates. However, recent
studies have shown that significant but variable proportions of THC, HO-THC, and
THCA are present in plasma as glucuronide conjugates (42). Hydrolysis of the glucuronide
conjugates is most effectively achieved using β-glucuronidase from E. coli
(14,42).
Liquid/liquid extractions have been used to separate cannabinoids from blood or
plasma (38,43–45). When Chu and Drummer evaluated eight different buffers and ten
different solvents for extracting THC from whole blood, they obtained the best results
by adding 1 mL of 1 M ammonium sulfate to 1 mL of blood and extraction with 7 mL
of hexane (45). However, because SPE is capable of achieving better selectivity, it is
now more widely used for extraction of cannabinoids from blood and plasma.
D’Asaro evaluated an automated SPE system (Zymark RapidTrace™) for determining
THC and THCA in whole blood (46). THC-d3 and THCA-d3 were added
to 1 mL of warm blood followed by addition of 3 mL of acetonitrile containing 10%
acetone. After vortexing and centrifugation the supernatant was separated and concentrated
by evaporation, then acidified with 0.1 M HCl and subjected to SPE. Various
SPE cartridges were evaluated; the C-8 anion exchange copolymer sorbent provided
the best overall recoveries and the cleanest extracts. THC and THCA were eluted at
the same time and then derivatized with BSTFA and analyzed by GC/MS with electron
ionization and selected-ion monitoring. The lower limits of quantitation (LOQs)
were 2.0 ng/mL for THC and 1.0 ng/mL for THCA.
The combination of a liquid/liquid extraction followed by a SPE was employed
by Felgate and Dinan for analysis of THC and THCA in whole blood (47). After
addition of deuterated internal standards to 0.5 mL of blood diluted with 1.0 mL of
water and 1 mL of 1.0 phosphate buffer (pH 4.0), the diluted blood was extracted with
hexane/ethyl acetate (5:1). The extract was evaporated to dryness, reconstituted with
hexane, and further cleaned up by SPE using Varian Bond Elut THC cartridges. THC
was eluted with hexane containing 50% toluene, and the THCA was eluted separately
with hexane containing 40% ethyl acetate. The THC and THCA extracts were analyzed
separately after each was derivatized with pentafluoropropanol and
pentafluoropropionic anhydride. If the derivatized THC and THCA extracts were combined,
sensitivity was reduced due to interferences. The GC/MS analysis, with electron
ionization and selected-ion monitoring, achieved an LOQ of 1 ng/mL for each
analyte.
MS for Detection of Cannabinoids 183
A fully validated GC/MS assay for determination of THC, HO-THC, and THCA
in serum was recently reported by Steinmeyer et al. (48). Deuterated internal standards
for each analyte were added to 1 mL of serum along with 0.2 mL ethanol and
2 mL 0.1 M phosphate buffer (pH 9.0). Samples were extracted on C18 bonded-phase
adsorption cartridges. The analytes were eluted from the cartridges with acetone/methanol
(1:1), and the extracts were evaporated to dryness and derivatized with
tetrabutylammonium hydroxide, dimethylsulfoxide, and iodomethane. The derivatized
extracts were acidified with 0.1 M HCl, extracted into isooctane, and analyzed by EIGC/
MS in the selected-ion monitoring mode. The LOQs in ng/mL were 0.62 (THC),
0.68 (HO-THC), and 3.35 (THCA). The method was cross-validated for analysis of
liver microsomal preparations.
A method for measurement of THC and THCA in plasma was developed at the
Center for Human Toxicology, University of Utah, to analyze specimens from clinical
studies (49). After addition of deuterated internal standards to 1 mL of plasma, 1 mL
of acetonitrile was added and the samples were vortexed and centrifuged. The supernatant
was separated and combined with 4 mL of 0.1 M acetate buffer (pH 7.0) and
poured onto a conditioned CleanScreen ZSTHC020 SPE column. The column was
then washed with 0.1 M acetate buffer and dried under vacuum. THC was eluted with
hexane/ethyl acetate/ammonia hydroxide (93:5:2), and the THCA was eluted separately
with hexane/ethyl acetate (70:30). The eluants containing THC and THCA were
combined, evaporated to dryness, and derivatized with hexafluoroisopropanol (HFIP)
and trifluoroacetic anhydride (TFAA). GC/MS analysis with negative ion chemical
ionization gave abundant molecular anions for the derivatized THC (m/z 410) and
abundant fragment ions (m/z 422) formed by loss of (CF3)2CHOH from the molecular
anion of derivatized THCA. LOQs were 0.5 ng/mL (THC) and 2.5 ng/mL (THCA).
Huestis et al. developed and fully validated a GC/MS assay for simultaneous
determination of THC, HO-THC, and THCA in human plasma (42). Their method
includes enzymatic hydrolysis of glucuronide conjugates, simultaneous SPE of all
three analytes in a single eluant, derivatization with BSTFA, and analysis by positive
ion chemical ionization GC/MS. Ions were monitored for each analyte and internal
standard: THC, m/z 387; THC-d3, m/z 390; HO-THC, m/z 459; HO-THC-d3, m/z 462;
THCA, m/z 489; and THCA-d3, m/z 492. Enzymatic hydrolysis with E. coli β-glucuronidase
resulted in significantly higher concentrations of HO-THC and THCA in the
eluants than could be obtained without the hydrolysis step. Extraction recoveries ranged
from 67.3 to 83.5% for all three analytes. LOQs were 0.5 ng/mL for THC and HOTHC
and 1.0 ng/mL for THCA.
Another method developed for analysis of clinical samples employed gas chromatography/
tandem mass spectrometry (GC/MS/MS; ref. 50). Deuterated internal standards
for THC and HO-THC were added to a 2-mL aliquot of human plasma followed
by 2 mL of acetonitrile and 2 mL of 0.1 M phosphate buffer (pH 6.0). After vortexing
and centrifugation, the supernatant was transferred to a conditioned Bond Elut Certify-
1 extraction column. After several washing steps the THC and HO-THC were
eluted from the column with methylene chloride, derivatized by trimethylsilylation,
and analyzed by GC/MS/MS using positive ion chemical ionization with ammonia as
the reagent gas. The protonated molecule ions for trimethylsilylated THC (m/z 387)
184 Foltz
and HO-THC (m/z 475) were collisionally dissociated to product ions at m/z 293 and
detected by selected-reaction monitoring. LOQs were 50 pg/mL for THC and 100 pg/
mL for HO-THC.
Several preliminary efforts to measure cannabinoids in blood or plasma by LC/
MS have been reported. Hughes et al. compared ESI, APCI, and atmospheric-pressure
photoionization (APPI) for analysis of THC, THCA, and HO-THC in blood. APCI
was more sensitive than ESI. THCA and HO-THC had better sensitivity in the negative
ionization mode, while THC showed better sensitivity in the positive ionization
mode. APPI was three to five times more sensitive for all three cannabinoids (51).
After SPE of THC, HO-THC, and THCA in blood, Mireault analyzed the extracts
using an ion trap LC/MS (Finnigan LCQ) operated in the APCI mode. THC was detected
using MS/MS, but HO-THC and THCA required MS/MS/MS to achieve adequate
selectivity (52).
5. DETERMINATION OF CANNABINOIDS IN ADIPOSE TISSUE
AND OTHER TISSUES
Quantitative determination of cannabinoids in adipose tissue is even more challenging
than analysis of cannabinoids in blood. Johansson et al. developed a lengthy
assay for measurement of THC in human fatty tissue (53). The procedure included
homogenization of the fat samples with hexane:isopropanol (3:2) and sequential SPEs
with Lipidex 5000 gel and a C18 resin. The extracted THC was derivatized with Nmethyl-
N-(t-butyldimethylsilyl)trifluoroacetamide (MTBSTFA), and the derivatized
THC was purified by preparative HPLC using a C18 column. Finally, the purified and
derivatized THC was analyzed by means of GC and high-resolution MS.
Investigators in the Department of Forensic Medicine at Kyushu University, Japan,
developed a relatively simple method for determination of THC in human tissues including
brain, lung, kidney, muscle, liver, spleen, and adipose tissue (54). Tissue
samples (0.1 g of fat or 0.5 g of the other tissues) were homogenized with 3 mL of
acetonitrile. After centrifugation, the supernatant was concentrated by evaporation
and mixed with 2 mL of 0.2 M sodium hydroxide. The aqueous solution was extracted
with 3 mL of hexane:ethyl acetate (9:1); the organic extract was washed with 2 mL of
0.1 M HCl to remove basic compounds and then evaporated to dryness for derivatization
in a solution of iodomethane, tetrabutylammonium hydroxide, and dimethyl-sulfoxide.
Derivatized extracts were analyzed by GC/MS using electron ionization and
selected-ion monitoring. The lower limit of detection for THC in each of the tissues
examined was 1 ng/g.
6. DETERMINATION OF CANNABINOIDS IN MECONIUM
Clinicians are increasingly interested in determining when a newborn infant has
been prenatally exposed to marijuana or other drugs of abuse. Meconium is the preferred
matrix for analysis in these cases because it retains drugs and drug metabolites
for a longer time than does an infant’s blood or urine (55).
GC/MS confirmation of THCA in meconium was first reported by Moore et al.
(56). The meconium was initially screened by fluorescence polarization immunoassay
MS for Detection of Cannabinoids 185
(Abbott Laboratories, Abbott Park, IL). Positives were then analyzed by GC/MS. After
homogenization in methanol, THCA-d3 was added along with 11.8 M potassium
hydroxide, and the mixture was allowed to stand for 15 minutes. After centrifugation
the aqueous supernatant was diluted with deionized water and extracted with
hexane:ethyl acetate (9:1) to remove lipophilic nonacidic compounds; the aqueous
layer was acidified with 0.1 N HCl and extracted with hexane:ethyl acetate (9:1). The
resulting organic layer was evaporated to dryness and derivatized with MTBSTFA.
EI-GC/MS analysis monitored ions at m/z 572, 515, and 413 for THCA and m/z 575,
518, and 416 for THCA-d3. The lower limit of detection (LOD) for THCA was 2 ng/g.
ElSohly and co-investigators extensively investigated methods of measuring THC
and its metabolites in meconium (8,55). They found that HO-THC and 8β,11-diHOTHC
were present in significant quantities in meconium from neonates whose mothers
had used marijuana and that those metabolites were mainly in the form of
glucuronide conjugates. The investigators developed two different GC/MS assays for
determination of cannabinoids in meconium; both included enzyme hydrolysis, but
one employed liquid/liquid extraction (55) and the other an immunoaffinity extraction
procedure (8). The liquid/liquid extraction method included the following procedures:
after addition of THC-d9 and THCA-d6 the meconium was homogenized in methanol
and centrifuged, and the supernatant was evaporated to dryness. The residue was taken
up in saturated monobasic potassium phosphate and extracted with chloroform. The
chloroform extract was evaporated to dryness and the residue dissolved in 0.1 M phosphate
buffer (pH 6.8) containing β-glucuronidase (E. coli, Type IX-A). After 16 hours
at 37°C, the sample was cooled, acidified with 1 N HCl, and extracted with hexane:ethyl
acetate (9:1). Acidic cannabinoids were removed from the organic solution by extraction
into 1 N sodium hydroxide, reacidified, and extracted back into hexane:ethyl acetate
before derivatization with BSTFA. Neutral cannabinoids remaining in the original
hexane:ethyl acetate solution were subjected to further clean-up prior to derivatization
with pyridine and acetic anhydride. The neutral and acidic cannabinoids were analyzed
separately by GC/MS. The LODs for the THC metabolites ranged from 2 to 15 ng/g.
Surprisingly, 8β,11-diOH-THC was found in the acidic fraction, along with THCA.
The second method, employing an immunoaffinity extraction, proved to be much
faster and more selective than the liquid/liquid extraction method. The immunoaffinity
resin was prepared by immobilization of THC antibody (Roche Diagnostic Systems,
Somerville, NJ) onto cyanogen bromide-activated Sepharose 4B, and stored in 1 M
NaCl solution containing 0.05% NaN3. After addition of deuterated internal standards
and 3 mL of methanol, the meconium (0.5 g) was homogenized and centrifuged and
the supernatant was evaporated to dryness. The dried residue was extracted with 2 mL
of isopropanol:water (95:5), and after centrifugation the supernatant was again separated
and evaporated to dryness. The residue was taken up in 2 mL of 0.1 M phosphate
buffer (pH 6.8) and hydrolyzed with β-glucuronidase (E. coli, type IX-A). The
immunoaffinity-resin slurry was added to the hydrolyzed sample and poured into a frit
filter cartridge and the liquid allowed to pass through under a slight vacuum. The resin
was washed once with phosphate saline buffer (pH 7.0) and three times with deionized
water. After the analytes were eluted with acetone and the extract evaporated to
dryness, they were trimethylsilylated using BSTFA and 1% TMCS and analyzed by
186 Foltz
EI-GC/MS with selected ion monitoring. The LODs were 1.0 ng/g for THCA and HOTHC
and 2.5 ng/g for 8β,11-diHO-THC.
Authors of the above immunoaffinity procedure reported that of 24 presumptive
positive meconium samples analyzed, 15 were confirmed positive for THCA and 18
were positive for HO-THC. Only three specimens were positive for 8ß,11-diHO-THC.
7. DETERMINATION OF CANNABINOIDS IN ORAL FLUIDS
Analysis of oral fluids to detect recent use of drugs of abuse is of increasing
interest because sampling is less invasive than collection of urine or blood. However,
unlike most other drugs, THC gets into oral fluids primarily by direct deposition into
the oral mucosa during smoking or oral ingestion, rather than being transferred from
blood to saliva. Consequently, concentrations of metabolites of THC are very low and
difficult to detect in this matrix.
Niedbala et al. compared results from analysis of urine and oral fluids from subjects
that smoked marijuana or ingested marijuana plant material (24). Oral fluid was
collected using a treated absorbent cotton fiber pad affixed to a nylon stick (OraSure
Technologies, Bethlehem, PA). After absorbing fluids in the mouth, the pad was placed
in a preservative solution that was subsequently analyzed for THC. THC-d3 was added
to 200 μL of diluted oral fluid, and the specimen was treated with 2 mL of 0.2 M
sodium hydroxide and extracted with 3 mL of hexane:ethyl acetate (9:1). The organic
layer was washed with 3 mL of 0.1 M HCl to remove basic compounds and the organic
layer was separated and evaporated to dryness. The dried extract was derivatized with
30 μL of BSTFA and 30 μL of ethyl acetate at 70°C for 30 minutes before analysis by
GC/MS/MS using electron ionization and selected-reaction monitoring. The LOQ for
THC in oral fluids was 0.5 ng/mL.
When detection of THC in oral fluids was compared to detecting THCA in urine,
the probability of a positive test in oral fluids was higher in specimens collected over
the first 6 hours following exposure. Subsequently, positivity in urine specimens
increased and generally exceeded that of oral fluid in specimens collected after 16
hours (24).
In an earlier study Menkes et al. collected oral fluids from 13 experienced users
after each of them had smoked one marijuana cigarette. Each saliva sample (20–200 μL)
was added to 200 μL of 8 M urea and extracted with 4 mL of pentane. The organic
extract was evaporated to dryness, derivatized with pentafluoropropionic anhydride
and analyzed by GC/MS using electron ionization and selected-ion monitoring. Concentrations
of THC were compared to measurements of heart rate and intoxication
over a period of 4 hours after smoking. The results indicated that salivary THC levels
can be a sensitive index of recent cannabis smoking, and appear more closely linked
with the effects of intoxication than do either blood or urine cannabinoid levels (57).
Brodbelt and co-investigators used commercially available 30-μm
poly(dimethylsiloxane) solid-phase microextraction fibers to absorb THC, cannabidiol,
and cannabinol from saliva specimens collected after smoking (58). One mL of saliva
was diluted with 1 mL of deionized water and 0.5 mL of acetic acid. THC-d3 was
added, and the solution was transferred to a vial containing the solid-phase
microextraction fibers. The fibers were subsequently transferred to a heated (270°C)
MS for Detection of Cannabinoids 187
injection port, which caused thermal desorption of the cannabinoids into the GC/MS.
The mass spectrometer was operated in full-scan mode between 120 and 350 amu.
The ions used for quantitation were THC (m/z 314, 299, and 231), cannabidiol (m/z
314 and 231), and cannabinol (m/z 310, 295, and 238). The range of quantitation for
each cannabinoid was 5–500 ng/mL.
8. DETERMINATION OF CANNABINOIDS IN HAIR
Determination of drugs in hair has continued to grow in importance; its advantages
over analysis of other matrices are that it is relatively noninvasive, and drugs
can be detected in hair for a much longer time period. However, cannabinoids in blood
are not taken up in hair nearly as efficiently as most other drugs are. As a result,
concentrations of cannabinoids in hair after smoking or ingestion of marijuana are
very low and can only be detected with extremely sensitive analytical methods. Furthermore,
cannabinoid metabolites such as THCA are normally present in hair at even
lower concentrations than parent cannabinoids such as THC, cannabinol, and cannabidiol.
This is a problem in forensic cases because passive exposure to marijuana smoke
can result in external adsorption of cannabinoids to hair follicles. Consequently, a hair
analysis that detects THCA provides more convincing evidence of intentional smoking
or ingestion of marijuana than a hair analysis that detects THC, cannabinol, or
cannabidiol. However, a strong case can be made for intentional marijuana use based
on detection of THC, cannabinol, or cannabidiol if it is shown that the method of
decontamination removes all externally adsorbed cannabinoids from the hair prior to
hair analysis.
Most published reviews on testing for drugs in hair primarily discuss methods
for analysis of basic drugs such as cocaine, opiates, and amphetamines. Authors who
have reviewed analysis of cannabinoids in hair include Staub (6), Sachs and Kintz
(59), and Baptista et al. (60).
Methods for the determination of cannabinoids in hair generally include the following
basic steps: (1) decontamination of hair by washing with a solvent to remove
any cannabinoids adsorbed to external surfaces of the hair; (2) enzymatic or alkaline
hydrolysis of the hair to facilitate extraction of the cannabinoids; (3) extraction of the
digested hair; (4) derivatization of the extracted cannabinoids; and (5) analysis using
GC and MS. The cannabinoids that appear to have the highest concentration in hair
are THC, cannabinol, and cannabidiol. However, some of the published methods are
designed to detect only THCA, for reasons stated above.
Methylene chloride has been most often used for decontaminating hair prior to
digestion (61–64); however, Strano-Rossi and Chiarotti reported that washing with
petroleum ether was more efficient than methylene chloride for then removal of cannabinoids
adsorbed to hair (65). Wilkins et al. compared four different wash solvents
(methylene chloride, methanol, isopropanol, and phosphate buffer) for analysis of THC
in human hair from known cannabis users. The concentrations of THC were significantly
lower when methylene chloride was used (66).
To extract cannabinoids efficiently, the hair is first dissolved by alkaline hydrolysis
or by enzymatic hydrolysis. Alkaline hydrolysis is generally favored because it can be
performed very rapidly. After addition of internal standard(s) the hair is subjected to
188 Foltz
NaOH (1–2 N) at 80–95°C for 10–30 minutes (61–65,67) or maintained at 37°C overnight
(66). If the assay includes determination of drugs that are degraded in the presence
of strong alkali, β-glucuronidase/arylsulfatase can be used to digest the hair prior
to extraction (60).
Early methods for the determination of cannabinoids in hair used liquid/liquid
extraction to remove cannabinoids from the hydrolyzed hair (61–63,66,68); for example,
after acidification, homogenized hair can be extracted with hexane:ethyl acetate (9:1
v/v; ref. 61). A more recently published method employing enzymatic hydrolysis used
a two-step liquid/liquid extraction procedure (60). After adjustment of the pH to 8.5,
the hydrolyzed hair sample was extracted with chloroform:isopropanol (97:3 v/v).
The aqueous layer was separated, acidified with acetic acid, and re-extracted with
hexane:ethyl acetate (9:1 v/v). The two organic extracts were then combined and prepared
for GC/MS analysis.
Sachs and Dressler developed a very sensitive but lengthy assay for the detection
of THCA in hair. The procedure involved initially extracting the hydrolyzed hair in
hexane:ethyl acetate, washing the organic extract with 0.5 M NaOH and then with 0.1 M
HCl, and injecting the concentrated organic extract into a high-performance liquid chromatography
column. The fraction containing THCA was collected, acidified with 0.05
M phosphoric acid, and extracted with hexane:ethyl acetate. This extensive clean-up
permitted detection of derivatized THCA at concentrations as low as 0.3 pg/mL (67).
Other recently published methods have generally used SPE procedures, including
solid-phase microextraction (SPME). Moore et al. used mixed-mode hydrophobic/anion
exchange SPE cartridges to extract THCA from digested hair (64). After conditioning
the SPE cartridge, the hydrolyzed hair sample was added to the cartridge; the column
was washed with deionized water (2 mL) and 0.1 M HCl:acetonitrile (70:30 v/v; 2 mL)
and dried, after which THCA was eluted with 3 mL of hexane:ethyl acetate (75:25 v/v).
Several variations of solid-phase microextractions have recently been used to
extract cannabinoids from hydrolyzed hair samples. Strano-Rossi and Chiarotti developed
a relatively simple and rapid method for detection of THC, cannabinol, and cannabidiol
in hair based on solid-phase microextraction and GC/MS analysis (65). A
commercially available 30-μm polydimethylsiloxane fiber was dipped into the neutralized
hair digest for 15 minutes and then inserted directly into the injection port of
the GC/MS, where the adsorbed nonderivatized cannabinoids were vaporized. The
injection port temperature was 260°C; the 5% phenylmethylsilicone capillary column
was maintained at 100°C for 2 minutes and then temperature-programmed to 270°C.
The LODs for analysis of 50 mg of hair were 0.1 ng/mg for THC and cannabinol and
0.2 ng/mg for cannabidiol.
Musshoff et al. used two variations of a headspace solid-phase microextraction
(HS-SPME) method for determination of cannabinoids in hair. With one method a
100-μm polydimethylsiloxane fiber was inserted for 25 minutes into the headspace of
a heated (90°C) vial containing the digested hair (69). The fiber was then exposed to
the headspace in a second vial containing 25 μL of MSTFA for 8 minutes at 90°C,
resulting in trimethylsilylation of the adsorbed cannabinoids. Finally, the fiber was
inserted into the heated (250°C) injection port of a GC/MS, permitting the derivatized
cannabinoids to be vaporized and analyzed. The reported LODs ranged from 0.05 to
0.14 ng/mg for THC, cannabidiol, and cannabinol. THCA was not detected.
MS for Detection of Cannabinoids 189
189
Table 1
Published Methods for Mass Spectometric Analysis of Cannabinoids in Urine
LOQ LOD
Ref. Analyte Extraction Derivatization Instrumentation Ionization (ng/mL) (ng/mL) Notes
29 THCA Liq/Liq PFPA and PFPOH GC/MS EI — — Discusses surface
adsorption problems
73 THCA Liq/Liq BSTFA GC/MS EI — — Compares extraction and
derivatization
procedures
11 THCA Liq/Liq MTBSTFA GC/MS EI — 0.9 Derivative is more stable
than TMS derivative
74 THCA Liq/Liq Trimethylsilyliodide GC/MS EI 10 1.0 Analyzed urine collected
for doping analysis
17 THCA SPE BSTFA GC/MS EI 2.0 — Reduced solvent volume
for SPE
16 THCA SPE Methyl iodide GC/MS EI 5 — Full-scan detection on an
ion trap MS
26 THCA SPE Methyl iodide GC/MS EI — 2 Extraction uses a strong
anion exchange resin
18 THCA SPE BSTFA GC/MS EI — — Extraction uses 3 M
Empore disk
cartridges
20 THCA SPE MSTFA GC/MS EI 2.5 — Compares 2 SPE and
derivatization
procedures
22 THCA SPE MSTFA GC/MS EI 2.0 2.0 High throughput with
Cerex PolyCrom-THC
SPE
9 THCA and 2 Liq/Liq Five procedures GC/MS EI — — Compared THCA-d3, -d6,
other acidic compared -d9, and -d10 as internal
metabolites standards
(continued)
190 Foltz
Table 1 (continued)
LOQ LOD
Ref. Analyte Extraction Derivatization Instrumentation Ionization (ng/mL) (ng/mL) Notes
28 THCA Liq/Liq PFPA and PFPOH GC/MS NCl — 0.7 Compares El, PCl, and
NCl mass spectra
25 THCA See notes Methyl iodide GC/MS EI — 0.5 Antibody-mediated
extraction
75 THCA See notes Methyl iodide GC/MS EI 20 0.25 Extractive-alkylation
procedure
27 THCA Liq/Liq Propyl iodide GC/MS EI 0.64 0.32 Derivatization with
proply preferred to
methyl
8 THC and See notes BSTFA GC/MS EI — 0.5 to 2.5 Hydrolyzed with
major β-glucuronidase.
metabolites Extracted with an
immunoaffinity resin.
15 THCA See notes MSTFA GC/MS EI — — Compares 2 SPE and 2
Liq/Liq extractions
12 THCA SPE BSTFA GC/MS EI 5 — Automated SPE
procedure
14 THC and Liq/Liq BSTFA GC/MS EI — — Samples hydrolyzed with
THCA β-glucuronidase
10 THCA SPE PFPA and PFPOH GC/MS EI 1.8 0.9 Automated SPE
procedure
24 THCA SPE PFPA and PFPOH GC/MS EI 5.0 — Compared oral fluid
testing to urine testing
71 THCA Liq/Liq BSTFA GC/MS/MS EI 5 — Varian Saturn 2000 ion
trap
19 THCA SPE BSTFA GC/MS/MS EI — — Detailed description of
operating parameters
190
MS for Detection of Cannabinoids 191
30 THCA SPE No derivatization LC/MS Pos.-ESI 2.5 — Also tried negative ion
ESl-MS
23 THCA SPE No derivatization LC/MS Neg.-ESI — — Zorbax Eclipse XDBC18
LC column
21 THCA SPE No derivatization LC/MS/MS Neg.-APCl 5 — Short prep. and analysis
time. Ret. time,
2.4 min
31 THCA and Liq/Liq No derivatization LC/MS/MS Pos.-ESI — 10 30 min. run time
THCA-glucuronide
10 THCA and SPE No derivatization LC/MS/MS Pos.-ESI 6.0 1.4 Assay used to determine
THCA-glucuronide stability of THCA and
THCA-glucuronide in
plasma and in urine
THCA, 11-nor-9-carboxy-Δ9-tetrahydrocannabinol; THC, Δ9-tetrahydrocannabinol;Liq/Liq, liquid/liquid extraction; PFPA, pentafluoropropionic anhydride;
PFPOH, pentafluoropropanol; GC/MS, gas chromatography/mass spectrometry; EI, electron ionization; BSTFA, bis-(trimethylsilyl)-trifluoroacetamide;
MTBSTFA, N-methyl-N-(t-butyldimethylsilyl)-trifluoroacetamide; SPE, solid-phase extraction; MSTFA, N-methyl-N-(trimethylsilyl)-trifluoroacetamide; NCI,
negative ion chemical ionization; PCI, positive ion chemical ionization; ESI, electrospray ionization; APCI, atmospheric pressure chemical ionization;
LOQ, limit of quantitation; LOD, lower limit of detection.
191
192 Foltz
Table 2
Published Methods for Mass Spectrometric Analysis of Cannabinoids in Plasma or Serum
LOQ LOD
Ref. Analyte Extraction Derivatization Instrumentation Ionization (ng/mL) (ng/mL) Notes
38 Multiple analytes Liq/Liq BSTFA GC/MS EI — 0.6 THC, CBD, DBN, and 5
metabolites of THC
76 THC and HO-THC Liq/Liq TFAA GC/MS NCl 0.2/0.5 — THCA analyzed using
different
derivatization
THCA 1. BF3/MeOH 0.2 — Early use of negative ion
2. TFAA chemical ionization
48 THC, HO-THC, SPE Methyl iodide GC/MS EI 0.6/0.7 3.4 — Improved version of an
and THCA earlier assay
82 THC, THCA, and SPE PFBBr GC/MS NCl 0.3/0.3 — Extractive alkylation
HO-THC BSTFA 1.0 using XAD-2 resin
49 THC and THCA SPE TFAA and HFIP GC/MS NCL 0.5/2.5 — Fully validated assay
8 THC and major See notes BSTFA GC/MS EI — 0.5–2.5 Hydrolysis with
metabolites β-glucuronidase;
extraction with an
immunoaffinity resin;
also analyzed
meconium
77 THC, HO-THC, SPE MSTFA GC/MS/MS EI 2/5/8 — Blood diluted 6:1
and THCA prior to extraction
42 THC, HO-THC, SPE BSTFA GC/MS PCl 0.5/0.5 1.0 — Plasma hydrolyzed with
and THCA β-glucuronidase.
Compares
concentrations with
and without
hydrolysis
50 THC and HO-THC SPE Tri-Sil TBTa GC/MS/MS PCl 0.05/0.1 0.01/0.2 Run time, 7 min
LOQ, limit of quantitation; LOD, lower limit of detection; Liq/Liq, liquid/liquid extraction; BSTFA, bis-(trimethylsilyl)-trifluoroacetamide; GC/MS, gas
chromatography/mass spectrometry; EI, electron ionization; THC, Δ9-tetrahydrocannabinol; HO-THC, 11-hydroxy-Δ9-tetrahydrocannabinol; TFAA,
trifluoroacetic anhydride; NCI, negative ion chemical ionization; THCA, 11-nor-9-carboxy-Δ9-tetrahydrocannabinol; SPE, solid-phase extraction; HFIP,
hexafluoroisopropanol; MSTFA, N-methyl-N-(trimethylsilyl)-trifluoroacetamide; PCI, positive ion chemical ionization.
aTri-Sil TBT from Pierce Chemical Co., Rockford, IL.
192
MS for Detection of Cannabinoids 193
Table 3
Published Methods for Mass Spectrometric Analysis of Cannbinoids in Whole Blood
LOQ LOD
Ref. Analyte Extraction Derivatization Instrumentation Ionization (ng/mL) (ng/mL) Notes
78 THC SPE TFAA GC/MS NCl 1.0 — Initial precipitation with
acetonitrile
46 THC and THCA SPE BSTFA GC/MS EI 2.0/1.0 1.6/0.8 Zymark RapidTrace SPE
workstation
43 THC and THCA Liq/Liq Methyl iodide GC/MS EI 1.0/0.5 — Extract 2 mL of blood
with hexane:EtOAc
(9:1)
47 THC and THCA Liq/Liq PFPA and PFPOH GC/MS EI 1.0 — THC and THCA extracts
and SPE analyzed in separate
runs
45 THC Liq/Liq PFPA and PFPOH GC/MS EI 1.0 — Method fully validated;
compared extraction
solvents
79 THC and THCA Liq/Liq BSTFA GC/MS/MS EI — 1.0 Multistep extraction
procedure
44 THC, HO-THC, Liq/Liq BSTFA GC/MS EI — 0.2/0.2 Evaluated several
and THCA different extraction
and derivatization
procedures
LOQ, limit of quantitation; LOD, lower limit of detection; THC, Δ9-tetrahydrocannabinol; SPE, solid-phase extraction; TFAA, trifluoroacetic anhydride;
GC/MS, gas chromatography/mass spectrometry; THCA, 11-nor-9-carboxy-Δ9-tetrahydrocannabinol; PFPA, pentafluoropropionic anhydride; PFPOH,
pentafluoropropanol; Liq/Liq, liquid/liquid extraction; BSTFA, bis-(trimethylsilyl)-trifluoroacetamide; HO-THC, 11-hydroxy-Δ9-tetrahydrocannabinol; NCI,
negative ion chemical ionization; EI, electron ionization.
193
194 Foltz
194
Table 4
Published Method for Mass Spectrometric Analysis of Cannabinoids in Tissues
LOQ LOD
Ref. Analyte Extraction Derivatization Instrumentation Ionization (ng/g) (ng/g) Notes
53 THC Liq/Liq t-Butyldimethyl GC/MS EI 0.4 — Very lengthy procedure;
and SPE silylation uses a high-resolution
mass spectrometer
54 THC Liq/Liq Methylation GC/MS EI — 1.0 Tissue homogenized
with acetonitrile
LOQ, limit of quantitation; LOD, lower limit of detection; THC, Δ9-tetrahydrocannabinol; Liq/Liq, liquid/liquid extraction; SPE, solid-phase
extraction; GC/MS, gas chromatography/mass spectrometry; EI, electron ionization.
MS for Detection of Cannabinoids 195
Table 5
Published Methods for Mass Spectometric Analysis of Cannabinoids in Meconium
LOQ LOD
Ref. Analyte Extraction Derivatization Instrumentation Ionization (ng/g) (ng/g) Notes
56 THCA Liq/Liq MTBSTFA GC/MS EI — 2.0 Analyzed 100 meconium
samples; 16 confirmed
positive
55 THC and major Liq/Liq BSTFA GC/MS EI 2.0–15 Includes enzymatic
metabolites hydrolysis; major
cannabinoids in
meconium are HOTHC
and 8β, 11-diHO-THC
8 THC and major See notes BSTFA GC/MS EI — 1.0–2.5 Hydrolyzed with
metabolites β-glucuronidase;
extracted with an
immunoaffinity
LOQ, limit of quantitation; LOD, lower limit of detection; THCA, 11-nor-9-carboxy-Δ9-tetrahydrocannabinol; Liq/Liq, liquid/liquid extraction;
THC, Δ9-tetrahydrocannabinol; MTBSTFA, N-methyl-N-(t-butyldimethylsilyl)-trifluoroacetamide; GC/MS, gas chromatography/mass spectrometry;
EI, electron ionization; THC, Δ9-tetrahydrocannabinol; BSTFA, bis-(trimethylsilyl)-trifluoroacetamide; HO-THC, 11-hydroxy-Δ9-tetrahydrocannabinol.
195
196 Foltz
Table 6
Published Methods for Mass Spectometric Analysis of Cannabinoids in Oral Fluids
LOQ LOD
Ref. Analyte Extraction Derivatization Instrumentation Ionization (ng/mL) (ng/mL) Notes
58 THC SPME None GC/MS EI 10 1.0 Also analyzed
cannabidiol and
cannabinol
24 THC Liq/Liq BSTFA GC/MS/MS EI 0.5 0.2 Detailed description
of a clinical study
57 THC Liq/Liq PFPA GC/MS EI — — Chewing gum used to
stimulate saliva
LOQ, limit of quantitation; LOD, lower limit of detection; THC, Δ9-tetrahydrocannabinol; SPME, solid-phase microextraction; GC/MS, gas
chromatography/mass spectrometry; EI, electron ionization; Liq/Liq, liquid/liquid extraction; PFPA, pentafluoropropionic anhydride.
196
MS for Detection of Cannabinoids 197
Table 7
Published Methods for Mass Spectometric Analysis of Cannabinoids in Hair
LOQ LOD
Ref. Analyte Extraction Derivatization Instrumentation Ionization (ng/mg) (ng/mg) Notes
67 THCA Liq/Liq PFPA/HFIP GC/MS NCl 0.001 0.0003 HPLC cleanup to
improve sensitivity
80 THCA SPE PFPA/HFIP GC/MS/MS NCl — — MS/MS more sensitivity
than GC/MS
61 THC and THCA Liq/Liq PFPA/PFPOH GC/MS EI — 0.1 Analyzed hair from 43
fatal heroin overdose
cases
68 THC and THCA Liq/Liq HFBA/HFIP GC/MS EI 0.05 0.01 Hair hydrolyzed with
11.8 N KOH at RT for
10 min
72 THC and THCA — HFBA/HFIP GC/MS/MS NCl 0.00005 0.00002 Samples analyzed by
Psychemedics Corp.;
extraction method not
disclosed
65 THC, CBD, SPME No derivatization GC/MS EI 0.1 Petroleum ether used to
and CBN decontaminate hair
prior to digestion
69 THC, CBD, HS-SPME MSTFA GC/MS EI 0.3 0.05 Analyzed hair from 25
and CBN marijuana users; THC
concentration 0.3–2.2
ng/mg
70 THC, CBD, HS-SPDE MSTFA GC/MS EI 0.4 0.1 Relatively rapid
and CBN procedure using
HS-SPDE
(continued)
197
198 Foltz
Table 7 (continued)
LOQ LOD
Ref. Analyte Extraction Derivatization Instrumentation Ionization (pg/mg) (pg/mg) Notes
60 THC, CBD, Liq/Liq No derivatization GC/MS EI 0.1 0.02 Ketamine and
and CBN Ketoprofen used as
THCA PFPA/PFPOH NCl 0.01 0.005 internal stds; hair
hydrolyzed with β-
glucuronidase/
arylsulfatase
62 THCA Liq/Liq PFPA/PFPOH GC/MS NCl 0.01 0.005 Monitored ions at m/z
622, 602, 605, and
474
64 THCA SPE TFAA/HFIP GC/MS NCl 0.0005 — High-volume injector
gave improved
sensitivity
66 THC, HO-THC, Liq/Liq TFAA GC/MS NCl 0.050/ 0.010/ THCA extracted
and THCA (see notes) 0.500/ 0.250/ separately from THC
0.050 0.010 and HO-THC and
derivatized by
methylation followed
by TFAA
63 THC, CBD, Liq/Liq No derivatization GC/MS EI — 0.1/ Alkaline digest extracted
and CBN 0.02/ with hexane:ethyl
0.0 acetate (9:1)
71 THCA Liq/Liq BSTFA GC/MS/MS EI 5.0 — Used an ion trap mass
spectrometer
81 THC, CBD, Supercritial No derivatization GC/MS EI — — Primarily
and CBN fluid concerned with
extraction analysis of cocaine
and opiates in hair
LOQ, limit of quantitation; LOD, lower limit of detection; THCA, 11-nor-9-carboxy-Δ9-tetrahydrocannabinol; Liq/Liq, liquid/liquid extraction; PFPA,
pentafluoropropionic anhydride; HFIP, hexafluoroisopropanol; GC/MS, gas chromatography/mass spectrometry; NCI, negative ion chemical ionization; HPLC,
high-performance liquid chromatography; SPE, solid-phase extraction; THC, Δ9-tetrahydrocannabinol; PFPOH, pentafluoropropanol; EI, electron ionization; HFBA,
heptafluorobutyric anhydride; CBD, cannabidiol; CBN, cannabinol; HS-SPME,headspace solid-phase microextraction; MSTFA, N-methyl-N-(trimethylsilyl)-
trifluoroacetamide; HS-SPDE, headspace solid-phase dynamic extraction; TFAA, trifluoroacetic anhydride; BSTFA, bis-(trimethylsilyl)-trifluoroacetamide.
198
MS for Detection of Cannabinoids 199
The second method (70), headspace solid-phase dynamic extraction (HS-SPDE),
used a gas-tight syringe attached to a needle internally coated with a 50-μm film of
polydimethylsiloxane containing 10% of activated carbon (commercially available
from Chromtech, Idstein, Germany). Hydrolysis of the hair (10 mg) took place in a
10-mL headspace vial containing 1 mL of 1 M NaOH, 0.5 g of sodium carbonate, and
the THC-d3 internal standard. The sample solution was heated at 90°C for 5 minutes
and stirred by a magnetic mixer bar. The SPDE needle was inserted into the sample
vial through a septum and the syringe plunger was moved up and down slowly 30
times aspirating and dispensing a vapor volume of 1 mL to extract the analytes from
the headspace dynamically. In the same manner as the HS-SPME method, the needle
was removed and inserted into a second vial containing the derivatizing reagent.
Exposure to the derivatizing reagent vapor occurred by moving the syringe plunger up
and down six times over a 4-minute period. The syringe was then removed from the
vial, the needle inserted into the hot injection port of the GC/MS, and the plunger
slowly moved down, thereby flushing the analytes into the GC column.
The HS-SPME and HS-SPDE methods gave very similar results in terms of lower
limits of detection and quantitation, precision and accuracy, and extraction recoveries.
However, the SPDE needle with the internal coating is far more robust than the SPMEcoated
fiber, has greater capacity, and is usable for more than 350 samplings (70).
Some of the published assays for determination of cannabinoids in hair do not
derivatize prior to GC/MS analysis (61,63,65). Trimethylsilylation with BSTFA or
MSTFA has been used for analysis of cannabinoids in hair (65,70,71) but so far has
not provided the sensitivity required to detect THCA in hair from cannabis users. The
best sensitivities have been achieved by derivatization with a combination of a
perfluorinated anhydride (TFAA, PFPA, or HFBA) and a perfluorinated alkyl alcohol
(HFIP or PFPOH). Derivatization with these reagents increases the molecular weights
of the cannabinoid analytes, often resulting in improved chromatography and selectivity.
An even greater benefit is the fact that perfluorinated derivatives are much
more efficiently ionized by NCI than by electron ionization, often resulting in dramatically
improved sensitivity (60,62,64,67,72).
REFERENCES
1. Lindgren, J.-E. (1983) Quantification of Δ1-tetrahydrocannabinol in tissues and body fluids.
Arch. Toxicol. 6 (Suppl.), 74–80.
2. Foltz, R. L. (1984) Analysis of cannabinoids in physiological specimens by gas chromatography/
mass spectrometry, in Advances in Analytical Toxicology (Baselt, R. C., ed.),
Biomedical Publ., Davis, CA, pp. 125–157.
3. Bronner, W. E. and Xu, A. S. (1992) GC/MS methods of analysis for detection of 11-nor-Δ9-
tetrahydrocannabinol-9-carboxylic acid in biological matrices. J. Chromatogr. 580, 63–75.
4. Goldberger, B. A. and Cone, E. J. (1994) Confirmatory tests for drugs in the workplace by
GC/MS. J. Chromatogr. A 674, 73–86.
5. Cody, J. T. and Foltz, R. L. (1995) GC/MS analysis of body fluids for drugs of
abuse, in Forensic Applications of Mass Spectrometry ( Yinon, J., ed.), CRC Press, Boca
Raton, FL, pp. 1–59.
6. Staub, C. (1999) Chromatographic procedures for determination of cannabinoids in biological
samples, with special attention to blood and alternative matrices like hair, saliva,
sweat and meconium. J. Chromatogr., Biomed. Appl. 733, 119–126.
200 Foltz
7. ElSohly, M. A., Little, T. L., and Stanford, D. F. (1992) Hexadeutero-11-nor- Δ9-tetrahydrocannabinol-
9-carboxylic acid: A superior internal standard for the GC/MS analysis of Δ9-
THC acid metabolite in biological specimens. J. Anal. Toxicol. 16, 188–191.
8. Feng, S., ElSohly, M. A., Salamone, S., and Salem, M. Y. (2000) Simultaneous analysis of
Δ9-THC and its major metabolites in urine, plasma, and meconium by GC/MS using an
immunoaffinity extraction procedure. J. Anal. Toxicol. 24, 395–402.
9. Szirmai, M., Beck, O., Stephansson, N., and Halidin, M. M. (1996) A GC/MS study of
three major acidic metabolites of Δ9-tetrahydrocannabinol. J. Anal. Toxicol. 20, 573–578.
10. Stout, P. R., Horn, C. K., and Klette, K. L. (2001) Solid-phase extraction and GC/MS
analysis of THC-COOH method optimization for a high-throughput forensic drug-testing
laboratory. J. Anal. Toxicol. 25, 550–554.
11. Clouette, R., Jacob, M., Koteel, P., and Spain, M. (1993) Confirmation of 11-nor-Δ9-tetrahydrocannabinol
in urine as its t-butyldimethylsilyl derivative using GC/MS. J. Anal.
Toxicol. 17, 1–4.
12. Langen, M. C. J., de Bijl, G. A., and Egberts, A. C. G. (2000) Automated extraction of 11-
nor-Δ9-tetrahydrocannabinol carboxylic acid from urine samples using the ASPE-XL
solid-phase extraction system. J. Anal. Toxicol. 24, 433–437.
13. McBurney, L. J., Bobbie, B. A., and Sepp, L. A. (1986) GC/MS and EMIT analysis for Δ9-
tetrahydrocannabinol metabolites in plasma and urine of human subjects. J. Anal. Toxicol.
10, 56–64.
14. Manno, J. E., Manno, B. R., Kemp, P. M., et al. (2001) Temporal indication of marijuana
use can be estimated from plasma and urine concentrations of Δ9-tetrahydrocannabinol,
11-hydroxy-Δ9-tetrahydrocannabinol, and 11-nor-Δ9-tetrahydrocannabinol-9-carboxylic
acid. J. Anal. Toxicol. 75, 538–549.
15. Congost, M., De la Torre, R., and Segura, J. (1988) Optimization of the quantitative analysis
of the major cannabis metabolite in urine by GC/MS. Biomed. Environ. Mass Spectrom.
16, 367–372.
16. Wimbish, G. H. and Johnson, K. G. (1990) Full spectral GC/MS identification of Δ9-
carboxy-tetrahydrocannabinol in urine with the Finnigan ITS40. J. Anal. Toxicol. 14, 292–
295.
17. O’Dell, L., Rymut, K., Chaney, G., Darpino, T., and Telepchak, M. (1997) Evaluation of
reduced solvent volume solid-phase extraction columns with analysis by GC/MS for determination
of 11-nor-9-carboxy-Δ9-THC in urine. J. Anal. Toxicol. 21, 433–437.
18. Singh, J. and Johnson, L. (1997) Solid-phase extraction of THC metabolite from urine using
the Empore disk cartridge prior to analysis by GC-MS. J. Anal. Toxicol. 21, 384–387.
19. Phinney, C. S. and Welch, M. J. (1995) Analysis by a combination of gas chromatography
and tandem mass spectrometry: Development of quantitative tandem-in-time ion trap mass
spectrometry: Isotope dilution quantification of 11-nor-Δ9-tetrahydrocannabinol-9-carboxylic
acid. Rapid Commun. Mass Spectrom. 9, 1056–1060.
20. Wu, A. H. B., Liu, N., Cho, Y.-J., Johnson, K. G., and Wong, S. S. (1993) Extraction and
simultaneous elution and derivatization of 11-nor-9-carboxy-Δ9-tetrahydrocannabinol using
Toxi-Lab SPEC prior to GC/MS analysis of urine. J. Anal. Toxicol. 17, 215–217.
21. Weinmann, W., Goerner, M., Vogt, S., Goerke, R., and Pollak, S. (2001) Fast confirmation
of 11-nor-9-carboxy-Δ9-tetrahydrocannabinol in urine by LC/MS/MS using negative atmospheric
pressure chemical ionization. Forensic Sci. Int. 121, 103–107.
22. Crockett, D. K., Nelson, G., Dimson, P., and Urry, F. M. (2000) Solid-phase extraction of
11-nor-Δ9-tetrahydrocannabinol-9-carboxylic acid from urine drug-testing specimens with
the Cerex PolyCrom-THC column. J. Anal. Toxicol. 24, 245–249.
23. Tai, S. S.-C. and Welch, M. J. (2000) Determination of 11-nor-Δ9-tetrahydrocannabinol-
9-carboxylic acid in urine-based standard reference material by isotope-dilution LC/MS
with electrospray ionization. J. Anal. Toxicol. 24, 385–389.
MS for Detection of Cannabinoids 201
24. Niedbala, R. S., Kardos, K. W., Fritch, D. F., et al. (2001) Detection of marijuana use by
oral fluid and urine analysis following single-dose administration of smoked and oral marijuana.
J. Anal. Toxicol. 25, 289–303.
25. Lemm, U., Tenczer, J., and Baudisch, H. (1985) Antibody-mediated extraction of the main
tetrahydrocannabinol metabolite from human urine and its identification by GC/MS in the
sub-nanogram range. J. Chromatogr. 342, 393–398.
26. Paul, B. D., Mell, L. D., Jr., Mitchell, J. M., and McKinley, R. M. (1987) Detection and
quantitation of urinary 11-nor-Δ9-tetrahydrocannabinol-9-carboxylic acid, a metabolite of
tetrahydrocannabinol, by capillary gas chromatography and electron impact mass
fragmentography. J. Anal. Toxicol. 11, 1–5.
27. Joern, W. A. (1992) GC/MS assay of the marijuana carboxy metabolite: Urine interference
with the dimethyl derivative. J. Anal. Toxicol. 16, 207.
28. Karlsson, L., Jonsson, J., Aberg, K., and Roos, C. (1983) Determination of Δ9-tetrahydrocannabinol-
11-oic acid in urine as its pentafluoropropyl-pentafluoropropionyl derivative by GC/
MS utilizing negative ion chemical ionization. J. Anal. Toxicol. 7, 198–202.
29. Joern, W. A. (1987) Detection of past and recurrent marijuana use by a modified GC/MS
procedure. J. Anal. Toxicol. 11, 49–52.
30. Breindahl, T. and Andreasen, K. (1999) Determination of 11-nor-Δ(9)-tetrahydrocannabinol-
9-carboxylic acid in urine using high-performance liquid chromatography and
electrospray ionization mass spectrometry. J. Chromatogr. B 732, 155–164.
31. Weinmann, W., Vogt, S., Goerke, R., Muller, C., and Bromberger, A. (2000) Simultaneous
determination of THC-COOH and THC-COOH-glucuronide in urine samples by LC/MS/
MS. Forensic Sci. Int. 113, 381–387.
32. Skopp, G. and Potsch, L. (2002) Stability of 11-nor-Δ-9-carboxy-tetrahydrocannabinol glucuronide
in plasma and urine assessed by liquid chromatography-tandem mass spectrometry.
Clin. Chem. 48, 301–306.
33. Brunk, S. D. (1988) False negative GC/MS assay for carboxy THC due to ibuprofen interference.
J. Anal. Toxicol. 12, 290–291.
34. Stout, P. R., Horn, C. K., and Lesser, D. R. (2000) Loss of THCCOOH from urine specimens
stored in polypropylene and polyethylene containers at different temperatures. J.
Anal. Toxicol. 24, 567–571.
35. Blanc, J. A., Manneh, V. A., Ernst, R., et al. (1993) Adsorption losses from urine-based
cannabinoid calibrators during routine use. Clin. Chem. 39, 1705–1712.
36. Joern, W .A. (1992) Surface adsorption of the urinary marijuana carboxy metabolite: The
problem and a partial solution. J. Anal. Toxicol. 16, 401.
37. Tsai, J. S. C., ElSohly, M. A., Tsai, S. F., Murphy, T. P., Twarowska, B., and Salamone, S.
J. (2000) Investigation of nitrite adulteration on the immunoassay and GC-MS analysis of
cannabinoids in urine specimens. J. Anal. Toxicol. 24, 708–714.
38. Kemp, P. M., Abukhalaf, I. K., Manno, J. E., Manno, B. R., Alford, D. D., and Abusada, G.
A. (1995) Cannabinoids in humans. I. Analysis of Δ9-tetrahydrocannabinol and six metabolites
in plasma and urine using GC/MS. J. Anal. Toxicol. 19, 285–291.
39. Kemp, P. M., Abukhalaf, I. K., Manno, J. E., et al. (1995) Cannabinoids in humans. II. The
influence of three methods of hydrolysis on the concentration of THC and two metabolites
in urine. J. Anal. Toxicol. 19, 292–298.
40. ElSohly, M. A., Feng, S., Murphy, T. P., Ross, S. A., Nimrod, A., Mehmedic, Z., and
Fortner, N. (1999) Δ9-Tetrahydrocannabivarin (Δ9-THCV) as a marker for the ingestion
of cannabis versus Marinol®. J. Anal. Toxicol. 23, 222–224.
41. ElSohly, M. A., Feng, S., Murphy, T. P., et al. (2001) Identification and quantitation of 11-
nor-Δ9-tetrahydrocannabivarin-9-carboxylic acid, a major metabolite of Δ9-
tetrahydrocannabivarin. J. Anal. Toxicol. 25, 476–480.
202 Foltz
42. Gustafson, R. A., Moolchan, E. T., Barnes, A., Levine, B., and Huestis, M. A. (2003)
Validated method for the simultaneous determination of Δ9-tetrahydrocannabinol (THC),
11-hydroxy-THC and 11-nor-9-carboxy-THC in human plasma using solid phase extraction
and gas chromatography-mass spectrometry with positive chemical ionization. J.
Chromatogr. B 798, 145–154.
43. Kintz, P. and Cirimele, V. (1997) Testing human blood for cannabis by GC-MS. Biomed.
Chromatogr. 11, 371–373.
44. Goodall, C. R. and Basteyns, B. J. (1995) A reliable method for the detection, confirmation,
and quantitation of cannabinoids in blood. J. Anal. Toxicol. 19, 419–426.
45. Chu, M. H. C. and Drummer, O. H. (2002) Determination of Δ9-THC in whole blood using
gas chromatography-mass spectrometry. J. Anal. Toxicol. 26, 575–581.
46. D’Asaro, J. A. (2000) An automated and simultaneous solid-phase extraction of Δ9-tetrahydrocannabinol
and 11-nor-9-carboxy- Δ9-tetrahydrocannabinol from whole blood using
the Zymakr RapidTrace with confirmation and quantitation by GC-EI-MS. J. Anal.
Toxicol. 24, 289–295.
47. Felgate, P. D. and Dinan, A. C. (2000) The determination of Δ9-tetrahydrocannabinol and
11-nor-9-carboxy-Δ9-tetrahydrocannabinol in whole blood using solvent extraction combined
with polar solid-phase extraction. J. Anal. Toxicol. 24, 127–132.
48. Steinmeyer, S., Bregel, D., Warth, S., Kraemer, T., and Moeller, M. R. (2002) Improved
and validated method for the determination of Δ9-tetrahydrocannabinol (THC), 11-hydroxy-
THC and 11-nor-9-carboxy-THC in serum, and in human liver microsomal preparations
using gas chromatography-mass spectrometry. J. Chromatogr. B 772, 239–248.
49. Huang, W., Moody, D. E., Andrenyak, D. M., et al. (2001) Simultaneous determination of
Δ9-tetrahydrocannabinol and 11-nor-9-carboxy- Δ9-tetrahydrocannabinol in human plasma
by solid-phase extraction and gas chromatography-negative ion chemical ionization mass
spectrometry. J. Anal. Toxicol. 25, 531–537.
50. Nelson, C. C., Fraser, M. D., Wilfahrt, J. K., and Foltz, R. L. (1993) Gas chromatography
tandem mass spectrometry measurement of Δ(9)-tetrahydrocannabinol, naltrexone, and
their active metabolites in plasma. Ther. Drug Monit. 15, 557–562.
51. Hughes, J. M., Andrenyak, D. M., Crouch, D. J., and Slawson, M. (2003) Comparison of LC/
MS ionization techniques for cannabinoids in blood (Abstract). J. Anal. Toxicol. 27, 191.
52. Mireault, P. (1998) Analysis of Δ9-THC and its two metabolites by APCI-LC/MS. ASMS
Conference, Orlando, CA, (Abstract).
53. Johansson, E., Noren, K., Sjoevall, J., and Halldin, M.M. (1989) Determination of Δ1-
tetrahydrocannabinol in human fat biopsies from marijuana users by GC/MS. Biomed.
Chromatogr. 3, 35–38.
54. Kudo, K., Nagata, T., Kimura, K., Imamura, T., and Jitsufuchi, N. (1995) Sensitive determination
of Δ9-tetrahydrocannabinol in human tissue by GC/MS. J. Anal. Toxicol. 19, 87–90.
55. ElSohly, M. A. and Feng, S. (1998) Δ9-THC metabolites in meconium: Identification of
11-OH-Δ9-THC, 8β,11-diOH- Δ9-THC, and 11-nor-Δ9-THC-9-COOH as major metabolites
of Δ9-THC. J. Anal. Toxicol. 22, 329–335.
56. Moore, C., Lewis, D., Becker, J., and Leikin, J. (1996) The determination of 11 nor-Δ9-
tetrahydrocannabinol-9-carboxylic acid in meconium. J. Anal. Toxicol. 20, 50–54.
57. Menkes, D. B., Howard, R. C., Spears, G. F. S., and Cairns, E. R. (1991) Salivary THC
following cannabis smoking correlates with subjective intoxication and heart rate. Psychopharmacology
103, 277–279.
58. Hall, B. J., Satterfield-Dover, M., Parikh, A. R., and Brodbelt, J. S. (1998) Determination
of cannabinoids in water and human saliva by solid-phase microextraction and quadrupole
ion trap GC/MS. Anal. Chem. 70, 1788–1796.
59. Sachs, H. and Kintz, P. (1998) Testing for drugs in hair—critical review of chromatographic
procedures since 1992—review. J. Chromatogr. B 713, 147–161.
MS for Detection of Cannabinoids 203
60. Baptista, M. J., Monsanto, P. V., Pinho Marques, E. G., et al. (2002) Hair analysis for Δ9-
THC, Δ9-THC-COOH, CBN and CBD, by GC/EI-MS Comparison with GC/MS-NCI for
Δ9-THC-COOH. Forensic Sci. Int. 128, 66–78.
61. Cirimele, V., Kintz, P., and Mangin, P. (1995) Testing of human hair for cannabis. Forensic
Sci. Int. 70, 175–182.
62. Kintz, P., Cirimele, V., and Mangin, P. (1995) Testing human hair for cannabis. II. Identification
of THC-COOH by GC/NCI-MS as a unique proof. J. Forensic Sci. 40, 619–622.
63. Cirimele, V., Sachs, H., Kintz, P., and Mangin, P. (1996) Testing human hair for cannabis.
III. Rapid screening procedure for the simultaneous identification of Δ9-tetrahydrocannabinol,
cannabinol, and cannabidiol. J. Anal. Toxicol. 20, 13–16.
64. Moore, C., Guzaldo, F., and Donahue, T. (2001) The determination of 11-nor- Δ9-tetrahydrocannabinol-
9-carboxylic acid (THC-COOH) in hair using negative ion GC/MS and
high-volume injection. J. Anal. Toxicol. 25, 555–558.
65. Strano-Rossi, S. and Chiarotti, M. (1999) Solid-phase microextraction for cannabinoids
analysis in hair and its possible application to other drugs. J. Anal. Toxicol. 23, 7–10.
66. Wilkins, D. G., Haughey, H., Cone, E. J., Huestis, M. A., Foltz, R. L., and Rollins, D. E.
(1995) Quantitative analysis of THC, 11-OH-THC, and THCCOOH in human hair by negative
ion chemical ionization mass spectrometry. J. Anal. Toxicol. 19, 483–491.
67. Sachs, H. and Dressler, U. (2000) Detection of THC-COOH in hair by MSD-NCI after
HPLC clean-up. Forensic Sci. Int. 107, 239–247.
68. Jurado, C., Gimenez, M. P., Menendez, M., and Repetto, M. (1995) Simultaneous quantification
of opiates, cocaine and cannabinoids in hair. Forensic Sci. Int. 70, 165–174.
69. Musshoff, F., Junker, H. P., Lachenmeier, D. W., Kroener, L., and Madea, B. (2002) Fully
automated determination of cannabinoids in hair samples using headspace solid-phase
microextraction and gas chromatography-mass spectrometry. J. Anal. Toxicol. 26, 554–560.
70. Musshoff, F., Lachenmeier, D. W., Kroener, L., and Madea, B. (2003) Automated
headspace solid-phase dynamic extraction for the determination of cannabinoids in hair
samples. Forensic Sci. Int. 133, 32–38.
71. Chiarotti, M. and Costamagna, L. (2000) Analysis of 11-nor-9-carboxy-Δ9-tetrahydrocannabinol
in biological samples by GC/MS/MS. Forensic Sci. Int. 114, 1–6.
72. Mieczkowski, T. (1995) A research note: The outcome of GC/MS/MS confirmation of hair
assays on 93 cannabinoid-positive cases. Forensic Sci. Int. 70, 83–91.
73. Baker, T. S., Harry, J. V., Russell, J. W., and Myers, R .L. (1984) Rapid method for the GC/MS
confirmation of 11-nor-9-carboxy-Δ9-tetrahydrocannabinol in urine. J. Anal. Toxicol. 8, 255–259.
74. De Cock, K. J. S., Delbeke, F. T., De Boer, D., Van Eenoo, P., and Roels, K. (2003)
Quantitation of 11-nor-Δ9-tetrahydrocannabinol-9-carboxylic acid with GC/MS in urine
collected for doping analysis. J. Anal. Toxicol. 27, 106–109.
75. Lisi, A. M., Kazlauskas, R., and Trout, G. J. (1993) Gas chromatographic-mass spectrometric
quantitation of urinary 11-nor-Δ9-tetrahydrocannabinol-9-carboxylic acid after
derivatization by extractive alkylation. J. Chromatogr. 617, 265–270.
76. Foltz, R. L., McGinnis, K. M., and Chinn, D. M. (1983) Quantitative measurement of Δ9-
tetrahydrocannabinol and two major metabolites in physiological specimens using capillary
column gas chromatography/negative ion chemical ionization mass spectrometry.
Biomed. Mass Spectrom. 10, 316–323.
77. Weller, J.-P., Wolf, M., and Szidat, S. (2000) Enhanced sensitivity in the determination of
Δ9-tetrahydrocannabinol and two major metabolites in serum using ion-trap GC/MS/MS.
J. Anal. Toxicol. 24, 359–364.
78. Stonebraker, W. E., Lamoreaux, T. C., Bebault, M., Rasmussen, S. A., Jepson, B. R., and
Beck, B. K. (1998) Robotic solid-phase extraction and GC/MS analysis of THC in blood.
Am. Clin. Lab. 17, 18–19.
204 Foltz
79. Collins, M., Easson, J., Hansen, G., Hodda, A., and Lewis, K. (1997) GC/MS/MS confirmation
of unusually high Δ9-tetrahydrocannabinol levels in two postmortem blood
samples. J. Anal. Toxicol. 21, 538–542.
80. Uhl, M. (1997) Determination of drugs in hair using GC/MS/MS. Forensic Sci. Int. 84,
281–294.
81. Cirimele, V., Kintz, P., Majdalani, R., and Mangin, P. (1995) Supercritical fluid extraction
of drugs in drug addict hair. J. Chromatogr. B Biomed. Appl. 673, 173–181.
82. Rosenfeld, J. M., McLeod, R. A., and Foltz, R. L. (1986) Solid-supported reagents in the
determination of cannabinoids in plasma. Anal. Chem. 58, 716–721.
Human Cannabinoid Pharmacokinetics 205
From: Forensic Science and Medicine: Marijuana and the Cannabinoids
Edited by: M. A. ElSohly © Humana Press Inc., Totowa, New Jersey
205
Chapter 9
Human Cannabinoid
Pharmacokinetics and Interpretation
of Cannabinoid Concentrations
in Biological Fluids and Tissues
Marilyn A. Huestis and Michael L. Smith
1. INTRODUCTION
Pharmacokinetics is the study of the absorption, distribution, metabolism, and
elimination of a drug in the body and how these processes change with time. Following
controlled drug administration, scientists monitor the drug and its metabolites in
bodily fluids and tissues to develop a pharmacokinetic profile for the animal or human
being studied. After years of research, scientists have learned some important general
principles about pharmacokinetic profiles. One is that, in general, pharmacokinetic
profiles are similar for most animals and humans, but specific elements of the disposition
of a drug in the body can differ greatly between species and between subjects
within a species. Another principle is that helpful models can be developed that characterize
a drug’s pharmacokinetics and define parameters to describe processes such
as time to peak and maximum concentrations, half-lives, volumes of distribution, and
so on. Measuring these pharmacokinetic parameters facilitates comparison between
and within human subjects who are examined at different times following administration
of a drug. As specific examples in this chapter will convey, it is important to
conduct carefully controlled studies and astutely note inter- and intrasubject similarities
and differences in pharmacokinetic parameters to build databases that can be used
to answer real life questions. The third principle that we will consider is that pharmacokinetic
profiles change with the route of drug administration.
206 Huestis and Smith
In this chapter, we describe what is currently known about the pharmacokinetics
of Δ9-tetrahydrocannabinol (THC), the principal psychoactive component of cannabis
(1,2). Our focus is THC because the majority of scientific studies have targeted this
drug and its metabolites, although 64 different cannabinoids have been identified in
the Cannabis plant (3–9). Routes of administration and comparisons of pharmacokinetic
parameters between human subjects have been published and are examined to
develop a relationship to a drug’s pharmacodynamic effects. In the Interpretation of
Body Fluid and Hair Concentrations section of this chapter, we discuss how one uses
the relationship between the pharmacokinetics of THC and its pharmacodynamic effects
to interpret concentrations of cannabinoids in biological fluids and tissues with the
ultimate goal of answering important social and scientific questions. Some typical
questions might involve the following areas:
1. Social scenarios: If a man is arrested for driving erratically and triers of fact in a court
of law subsequently hear testimony that his plasma concentration of THC is 2 ng/mL,
can they infer that the marijuana he previously smoked contributed to his impaired
driving? Should the laboratory that analyzed the plasma specimen have measured
metabolites of THC to better answer this question? Could the same information be
obtained by analyzing oral fluid, a specimen that can be obtained less invasively?
Would analysis of the man’s hair for THC help the jurors determine if he was a chronic
cannabis user? These questions indicate some typical problems encountered by individuals
who must evaluate human performance. Similar questions arise in workplace
drug testing and death investigations.
2. Scientific scenarios: Scientists investigating cannabinoid mechanisms of action are
also interested in their pharmacokinetics (2). Sites of action are often within the brain
or peripheral nerve tissues, and it is important to understand the processes and time
frames for the drugs to reach and leave these sites (10,11). Imaging technology measuring
physiological functions such as cerebral blood flow (CBF) or other blood oxygen
level-dependent function has allowed more sophisticated studies of drug uptake
and distribution to cannabinoid receptor sites. It is important to relate these physiological
functions to a drug’s pharmacokinetic profile in plasma and other fluids
(12,13). Questions from these scientists might be: Do the concentrations of THC in
plasma correlate with changes in CBF following cannabis use? Can measurement of
THC concentrations help us to understand individual variations in CBF and effects of
cannabis?
A representative clinical investigator might ask, can we use plasma cannabinoid
concentrations to manage patients prescribed a cannabis preparation to treat neuropathic
pain, appetite loss with AIDS wasting disease, nausea and vomiting following
chemotherapy, or symptoms of multiple sclerosis? Research scientists and medical
practitioners have begun to use cannabinoids to treat these and similar illnesses (14–
17). As with any therapeutic drug, understanding its pharmacokinetics is important in
managing patients to maximize clinical effectiveness and reduce toxicity. It is also
important in determining the abuse liability of a drug preparation. These and additional
questions will be addressed in this chapter.
Human Cannabinoid Pharmacokinetics 207
2. CANNABIS POTENCY
Dose, chemical structure of precursors, binding of THC to macromolecules in
cannabis plant material, and route of administration affect the amount of THC absorbed.
The concentrations of THC in different cannabis products have been determined (18,19).
The most comprehensive report, by ElSohly et al., examined marijuana, hashish, and
hashish oil samples seized across the United States by the Drug Enforcement Administration
over an 18-year period (20). THC content increased from an average of 1.5%
in 1980 to 4.2% in 1997. Interestingly, THC content in hashish and hashish oil averaging
12.9% and 17.4%, respectively, did not show an increase over time. Government
laboratories in the United States have confirmed this trend toward higher-potency marijuana
(21).
The chemical structure of cannabinoids in marijuana is also important. About
95% of THC present in marijuana plant material is in the form of two carboxylic acids
that are converted to THC during smoking (3,22). Scientists originally believed that if
a person orally ingested marijuana without heating, very little THC would be absorbed.
They had evidence that if one heated marijuana before ingestion, as occurs with marijuana
brownies, significant quantities of THC were absorbed. Later studies demonstrated
that an individual can also absorb THC from marijuana plants that were dried
in the sun, because variable amounts of THC released by decarboxylation. Hashish
and hashish oil retain much of the parent THC in a form that can be more easily
absorbed, whether smoked or ingested orally.
3. ABSORPTION
Smoking, the principal route of cannabis administration in the United States,
provides a rapid and highly efficient method of drug delivery. Approximately 30% of
THC in marijuana or hashish cigarettes is destroyed by pyrolysis during smoking
(23,24). Smoked drugs are highly abused in part because of the efficiency and speed
of delivery of the drug from the lungs to the brain. Intensely pleasurable and strongly
reinforcing effects may be produced because of the almost immediate drug exposure
to the central nervous system. Drug delivery during cannabis smoking is characterized
by rapid absorption of THC, with slightly lower peak concentrations than those found
after intravenous administration (25). Bioavailability of smoked THC is reported to
be 18–50% partly as a result of the intra- and intersubject variability in smoking
dynamics that contribute to uncertainty in dose delivery (26). The number, duration,
and spacing of puffs, hold time, and inhalation volume greatly influence the degree of
drug exposure (27–29). THC can be measured in the plasma within seconds after
inhalation of the first puff of marijuana smoke (see Fig. 1; ref. 30). Mean ± SD THC
concentrations of 7.0 ± 8.1 and 18.1 ± 12.0 ng/mL were observed following the first
inhalation of a low- (1.75% THC, approx 16 mg) or high-dose (3.55% THC, approx
30 mg) cigarette, respectively (30). Concentrations increased rapidly and peaked at
9.0 minutes, berfore initiation of the last puff sequence at 9.8 minutes. Figure 2 dis208
Huestis and Smith
Fig. 1. Mean (N = 6) plasma concentrations of Δ9-tetrahydrocannabinol (THC), 11-
hydroxy-Δ9-THC (11-OH-THC), and 11-nor-9-carboxy-Δ9-THC (THCCOOH) by gas
chromatography/mass spectrometry during smoking of a single 3.55% THC cigarette.
Each arrow represents one inhalation or puff on the cannabis cigarette. (From ref. 1
with permission.)
Fig. 2. Mean (N = 6) plasma concentrations of Δ9-tetrahydrocannabinol (THC), 11-
hydroxy-Δ9-THC (11-OH-THC), and 11-nor-9-carboxy-Δ9-THC (THCCOOH) by gas
chromatography/mass spectrometry following smoking of a single 3.55% THC
cigarette. (From ref. 30 with permission.)
Human Cannabinoid Pharmacokinetics 209
plays mean data for a group of six subjects after paced smoking of a single 3.55%
THC cigarette. The number of puffs, length of inhalation and hold time, time between
puffs, and potency of the cigarette were controlled. Figure 3 shows individual THC
concentration time profiles for six subjects and demonstrates the large intersubject
variability of the smoked route of drug administration. Many individuals prefer the
smoked route, not only for its rapid drug delivery, but also for the ability to titrate
their dose.
In some studies THC was measured in blood, and expected values were found to
be about half those of plasma (31). Albumin and other proteins that bind THC and the
poor penetration of THC into red blood cells contribute to these higher plasma concentrations.
Postmortem blood is a common example where blood concentrations are
routinely reported because of difficulty obtaining acceptable plasma samples. Significant
differences in THC concentrations between the two fluids make it important to
always be informed about which is being reported.
If cannabis is ingested orally, absorption is slower and peak plasma THC concentrations
are lower (25,32–34). Wall et al. found peak THC concentrations approx
4–6 hours after ingestion of 15–20 mg of THC in sesame oil (34). Peak THC concentrations
ranging from 4.4 to 11 ng/mL were observed 1–5 hours following ingestion of
20 mg of THC in a chocolate cookie (25). Oral bioavailability has been reported to be
4–20% (25,34), in part as a result of degradation of drug in the stomach (35). Also,
there is significant first-pass metabolism to active 11-hydroxy-Δ9-tetrahydrocannabinol
(11-OH-THC) and inactive metabolites. Plasma 11-OH-THC concentrations range
from 50 to 100% of THC concentrations following the oral route of cannabis adminis-
Fig. 3. Individual plasma Δ9-tetrahydrocannabinol (THC) time course by gas chromatography/
mass spectrometry for six subjects following smoking of a single 3.55%
THC cigarette. (From ref. 30 with permission)
210 Huestis and Smith
tration compared to only about 10% after smoking (34). 11-OH-THC is equipotent to
THC, explaining the fact that pharmacodynamic effects after oral cannabis administration
appear to be greater than those after smoking THC at the same concentrations
(25).
4. DISTRIBUTION
THC has a large volume of distribution, 10 L/kg, and is 97–99% protein bound
in plasma, primarily to lipoproteins (36,37). Highly perfused organs, including the
brain, are rapidly exposed to drug. Less highly perfused tissues accumulate drug more
slowly because THC redistributes from the vascular compartment to tissue (38). THC’s
high lipid solubility concentrates and prolongs retention of the drug in fat (39,40).
Slow release of the drug from fat and significant enterohepatic circulation contribute
to THC’s long terminal elimination half-life in plasma, reported as greater than 4.1
days in chronic marijuana users (41). Isotopically labeled THC and sensitive analytical
procedures were used to obtain this estimate of drug half-life. Use of less sensitive
assays and a shorter monitoring time yield much lower estimates of terminal elimination
half-life.
5. METABOLISM
Hydroxylation of THC by the hepatic cytochrome P450 enzyme system leads to
production of the active metabolite 11-OH-THC (42,43), believed by early investigators
to be the true active analyte (44). When marijuana is smoked as opposed to taken
orally, concentrations of 11-OH-THC are much lower (approx 10% of the THC concentration;
ref. 30). Other tissues, including brain, intestine, and lung, may contribute
to the metabolism of THC, and, in these tissues, alternate hydroxylation pathways
may be more prominent (45–49). Further metabolism to di- and tri-hydroxy compounds,
ketones, aldehydes, and carboxylic acids has been documented (38,50). Oxidation of
active 11-OH-THC produces the inactive metabolite, 11-nor-9-carboxy-Δ9-tetrahydrocannabinol
(THCCOOH) (44,51). In a study of the pharmacokinetics of a single oral
10-mg dose of Marinol®, the concentration of inactive THCCOOH metabolite predominated
from as early as 1 hour after dosing, with much lower THC and 11-OHTHC
concentrations (52). The inactive THCCOOH metabolite and its glucuronide
conjugate have been identified as the major end products of biotransformation in most
species, including humans (50,53). Renal clearance of these polar metabolites is low
as a result of extensive protein binding (36). Plasma THCCOOH concentrations gradually
increase and are greater than THC concentrations shortly after smoking (Fig. 2),
whereas THC concentrations decrease rapidly after smoking cessation (30). The time
course of detection of THCCOOH in plasma is much longer than that of THC or 11-
OH-THC.
6. ELIMINATION
After the initial distribution phase, the rate-limiting step in the elimination of
THC is its redistribution from lipid depots to blood (54). Early studies showed that
Human Cannabinoid Pharmacokinetics 211
15–20% of a smoked THC dose was eliminated as acidic urinary metabolites, whereas
25–30% were excreted in the feces as 11-OH-THC and THC-COOH following intravenous
administration and 48–53% following oral administration (34,38). Approximately
80% of the acidic urinary metabolites are estimated to be conjugated and
nonconjugated THC-COOH. There appears to be no significant difference in metabolism
between men and women (34). A total of 80–90% of the drug is excreted within
5 days, mostly as hydroxylated and carboxylated metabolites (38). Halldin et al. identified
18 acidic metabolites of THC in urine, most of which are hydroxylated or β-
oxidized analogs of THC (53). Many of these metabolites are conjugated with
glucuronic acid, increasing the compounds’ water solubility. The primary urinary
metabolite is the acid-linked THCCOOH glucuronide conjugate (55), whereas 11-
OH-THC predominates in the feces (38). Mean peak urinary concentrations of THCCOOH
were 89.8 ± 31.9 ng/mL and 153.4 ± 49.2 ng/mL approx 8 and 14 hours after
smoking a single 1.75 or 3.55% THC cigarette (see Fig. 4; refs. 56 and 57). THCCOOH
was detected in urine at a concentration greater than or equal to 15 ng/mL for
33.7 ± 9.2 hours and 88.6 ± 9.5 hours after these doses (15 ng/mL was selected for
evaluation because federal drug testing programs administratively designate specimens
with THCCOOH concentrations below this level as negative). When sensitive
analytical procedures and sufficient sampling periods are employed, the terminal urinary
excretion half-life of THCCOOH in humans has been estimated to be 3–4 days
(58). When THC is ingested orally, the excretion profile is similar to that following
smoking (32,59). Gustafson et al. studied seven subjects who received oral doses of 0,
0.39, 0.47, 7.5 (Marinol), and 14.8 mg THC per day in a double-blind, placebo-con-
Fig. 4. Urinary excretion profile of 11-nor-9-carboxy-Δ9-THC (THCCOOH) as measured
by gas chromatography/mass spectrometry (GC/MS) in one subject following
smoking of a single 3.55% THC cigarette. The horizontal line at 15 ng/mL represents
the current GC/MS cutoff used in most testing programs. The urinary THC-COOH
concentrations (ng/mL) normalized to urine creatinine concentrations (mg/mL) are
illustrated with closed triangles. (From ref. 89 with permission.)
212 Huestis and Smith
trolled, randomized study (60). THC in hemp oil or Marinol was administered in three
divided daily doses at meals for 5 days. All urine specimens were collected over the
10-week study period and analyzed by several immunoassays and gas chromatography/
mass spectrometry (GC/MS). Maximum THC-COOH concentrations were 5.4–
38.2 ng/mL and 19.0–436 ng/mL for the two lower and two higher doses, respectively.
An important analytical study was published by Kemp et al. showing that significantly
higher concentrations of THC and 11-OH-THC in urine were found when
Escherichia coli β-glucuronidase was employed in the hydrolysis method compared
with either of the common hydrolysis methods using Helix pomatia glucuronidase or
base (61). Mean THC concentration in urine specimens from seven subjects collected
after each had smoked a single 3.58% marijuana cigarette was 22 ng/mL using the E.
coli glucuronidase hydrolysis method, whereas THC concentrations using either H.
pomatia glucuronidase or base hydrolysis methods were near zero. Similar differences
were found for 11-OH-THC with a mean concentration of 72 ng/mL from the E.
coli method and concentrations less than 10 ng/mL from the other methods. It is hoped
that the finding of THC in urine may provide a reliable marker of recent cannabis use;
however, adequate data from controlled drug administration studies are not yet available.
7. INTERPRETATION OF BODY FLUID AND HAIR CONCENTRATIONS
Interpreting body fluid concentrations by necessity depends on the nature of the
questions that require a science-based answer; however, the most common social questions
generally can be summarized as: Is the concentration of the drug in an individual’s
body fluid sufficiently high to indicate impairment or place them in violation of a
governing policy?
Research scientists who are conducting studies to determine cannabinoid mechanisms
of action or examine how cannabinoids may be used in clinical treatment also
have an interest in interpreting cannabinoid concentrations in body fluids and tissues.
The generic question they might ask would be: How do fluid or tissue concentrations
in humans correlate with brain concentrations or with treatment outcome? To provide
answers to these important social and scientific questions, we must examine more
closely the kinetics of the drug in bodily fluids and tissues and how these relate to
effects on the individual.
7.1. Plasma
Let us consider the specific example of a man who is stopped by a police officer
for erratic driving. The driver fails a field sobriety test indicating that he is impaired,
and subsequent laboratory testing determines that his plasma THC concentration is
2 ng/mL. Did the THC contribute to his impaired driving?
Plasma concentrations of drug are frequently measured in an attempt to answer
this question because, in general, plasma concentrations of most drugs correlate with
drug effects better than concentrations in other bodily fluids. Mason and McBay
reported in 1985 that one could not predict the effects of cannabis from plasma THC
concentrations (62). They quoted their own study of 600 drivers killed in single-vehicle
Human Cannabinoid Pharmacokinetics 213
crashes that found alcohol to be the only drug with significant adverse effects on driving
(31). Moskowitz, reporting during the same time frame, did not specifically address
plasma concentrations of THC, but cited many studies that found a relationship between
cannabis dose and performance impairment including impaired coordination, tracking,
perception, and vigilance in driving simulators and on-the-road tests (63). More
recent studies with carefully controlled variables and newer performance measures
documented that smoking cannabis at doses of 300 μg THC/kg, or about 20 mg for the
70-kg man in our example, impaired perceptual motor speed, accuracy, and multitasking,
all important requirements for safe driving (64–66). The impairing effects of
the 300 μg/kg dose of THC were similar to those of individuals with blood alcohol
concentrations of 0.05 g/dL or greater, the legal driving limit in most European countries.
When combined with alcohol, the impairing effects of THC were even greater
(66–68). However, most of these studies did not attempt to correlate plasma or blood
THC concentrations with observed effects but demonstrated that impairment depended
on the time after use, with most subjects showing no impairment 24 hours postdose.
Huestis et al. performed controlled administration studies that measured plasma THC
concentrations in six individuals who had smoked 15.8- and 33-mg doses of THC in
marijuana (69). Concentrations for plasma collected after marijuana smoking were
used to construct models for predicting the time of last THC use within 95% confidence
intervals (see Fig. 5; refs. 30, 70, and 71). Both Model I, which used plasma
THC concentrations, and Model II, which used the ratio of THCCOOH/THC concentrations,
were found to predict the time of last use in about 90% of cases from all
previously published plasma concentration data, whether analysis was by radioimmuno-
Fig. 5. Predictive mathematical models for estimating the elapsed time in hours of last
cannabis use based on plasma Δ9-tetrahydrocannabinol (THC) and 11-nor-9-carboxy-
Δ9-THC (THCCOOH) concentrations by GC/MS. (From ref. 70 with permission.)
214 Huestis and Smith
assay (RIA), GC, or GC/MS. These mathematical models were further evaluated in
another controlled drug administration study of 38 subjects, each smoking a 2.64%
THC cigarette. Of these subjects, 29 smoked a second cigarette 4 hours later (72). Plasma
was collected immediately after the first cigarette and up to 6 hours after smoking for
analysis of THC and THC-COOH concentrations (N = 717). Accuracy, when applying
the combination of Model I and Model II’s 95% confidence intervals, following the first
cigarette was 99.5% (413 of 415 specimens had a THC concentration or THC-COOH/
THC ratio that predicted the correct time of use within this interval) with no underestimations
of time of use and maximum overestimation of 4 minutes. Accuracy when
applying the combined models’ 95% confidence intervals following the second cigarette
was 98.6% (285 of 289 specimens) with no underestimations and the same maximum
overestimation. When plasma concentrations of THC were between 0.5 and 2 ng/
mL, Model I alone was 80.5% accurate, and Model II alone was 77.6% accurate. However,
Model I had no underestimations, and Model II had time of use for 17 of 76 specimens
underestimated with maximum errors up to 1.5 hours, indicating that Model II
alone is less reliable when THC concentrations are between 0.5 and 2 ng/mL. If the
models were used in combination, predicted times of use were accurate for all cases.
Both models are used frequently in courts of law in many countries to estimate
elapsed time since last cannabis use in accident and criminal investigations. They
allow decision makers to answer a corollary question: How accurately can you estimate
the time of last use of cannabis? Officials can use this information to corroborate
or discount the accused person’s story. After estimating the time of last use, the time
course of performance-impairment data reported in the literature is referenced to support
a conclusion of possible impairment or lack of impairment. There are many laboratory,
simulator, and on-the-road studies that have shown impairment in tasks required
for safe driving when individuals have been under the influence of cannabis (66,68),
especially when cannabis is combined with ethanol (73).
The onset of impairing effects of THC lags behind the increase in plasma concentration
during absorption; then effects remain relatively constant as the concentration
decreases dramatically because of THC distribution and metabolism (1). This
concentration–effect relationship, displayed in Fig. 6, is described as a counterclockwise
hysteresis. As an example, one can observe two different intensities of effects for
tachycardia and the visual analog scale for “feel drug” at 50 ng/mL depending on
whether the individual is in the absorption or distribution phase. Plasma THC concentrations
appear to be linearly related to the intensity of effects during absorption and
elimination, but there is no relationship between concentration and effects during distribution.
In the case of drivers, it would be rare for authorities to collect a plasma
specimen prior to the initial distribution phase of THC. After smoking cannabis,
absorption and distribution are complete in 45–60 minutes. It typically takes longer
than this to stop the driver, perform a field sobriety test, and transport the driver to a
site for drawing blood. In the scenario we are considering, it would be important to
determine the time sequence of events from driving through blood collection to ensure
that the driver was in the elimination phase. For instructive purposes, we will consider
that the police officer testified that the time of blood collection was more than 1 hour
after the driver was stopped and that the driver was under observation during this
period, precluding further drug use.
Human Cannabinoid Pharmacokinetics 215
Early epidemiological approaches relating cannabinoid plasma concentrations
to accident risk yielded inconsistent results and were criticized for not including an
adequate control group of drivers who were on the same roads at similar times and
who did not have driving accidents (1). An improved approach, responsibility analysis,
independently assigns culpability for the accident and then statistically compares
the odds ratio or risk that an accident could occur for individuals who had cannabinoids
in their system and for those that did not. Culpability analysis proved effective
for demonstrating performance impairment with alcohol, but was less successful for
cannabinoids for several important reasons. In many cases blood was not drawn for
cannabinoid analysis until many hours after an accident or impaired driving incident.
During this time the concentration of THC in the plasma decreased rapidly, often
falling below the limits of quantification (LOQs) of the methods used for analysis. In
many cases, the only analyte identified in plasma was THCCOOH, the inactive
metabolite with a much wider window of drug detection than parent THC. Some of
the early studies only reported whether cannabinoids were present in blood or urine,
not specifying whether measurable THC was found. They used analytical methods
with high LOQs, i.e., small windows of detection, and were underpowered to identify
increased risk because of insufficient sample size. Drummer et al. successfully
employed the empirical approach of culpability analysis and found that the group of
drivers who had THC present in blood were three to seven times more likely to be
responsible for their accident than drivers whose blood specimens were negative for
THC (65,74). Those with THC blood concentrations of 5 ng/mL had the higher probability
of causing the accident, with a mean odds ratio of 6.8.
With this body of scientific information, we now can answer the question of
whether or not marijuana contributed to the driving impairment of the individual in
Fig. 6. Visual analog scale for “How strongly do you feel the drug now?” and heart
rate (BPM, beats per minute) measures for a subject after smoking a 3.55% THC
cigarette demonstrating a counterclockwise hysteresis for the concentration–effect
curves.
216 Huestis and Smith
our example. This individual failed the field sobriety test and had 2 ng/mL of THC in
his plasma more than an hour after being stopped by the police. In this case, marijuana
most likely contributed to the performance impairment. The issue of whether or not a
biological test result alone can be used to document impairment is much more controversial.
In many states and countries, per se laws have been established that state that
an individual is assumed to be under the influence of cannabis if THC or, in some
cases, THCCOOH is found in blood, plasma, or, sometimes, urine. The problem of
drugged driving is a serious public health issue requiring additional research to link
drug concentrations to ongoing impairment, to determine the best analyte and best
biological fluid to monitor, and to decide whether administrative cutoff concentrations
are needed.
What if the accused driver claimed that he might have unknowingly ingested
food that contained cannabis? If this were true, he might be less culpable and receive
less punishment. As mentioned, the ratios of 11-OH-THC to THC concentrations differ
following the smoked and oral routes of administration; peak concentrations of 11-
OH-THC after smoking are about 10% that of THC and approximately equal after oral
administration (1). If 11-OH-THC also was measured in the plasma from the driver in
our example and its ratio with THC was approx 1:1, this would provide some evidence
to support his story.
If we now change venues from the courtroom to the research center, we can
examine how scientists use plasma concentrations to help understand the mechanisms
by which cannabinoids affect brain function. Advances in brain imaging using positron
emission tomography and magnetic resonance imaging have allowed investigators to
observe changes in CBF as a result of THC administration (12,75–77). A question
relevant to this area of research might be: How do plasma concentrations of THC
following administration of cannabis correlate with changes observed in the brain using
imaging techniques? Mathew et al., who studied 47 subjects who received two different
intravenous doses of THC or placebo, found that THC had significant effects on
global and regional CBF (13). Also, feeling intoxicated accounted for changes in
regional CBF better than plasma levels of THC. This finding is not surprising in that
the effects on the brain would be expected to have a more contemporaneous relationship
with related physiological processes in the brain. However, plasma concentrations
provide information about individual differences in processing the same dose of
cannabis and offer additional information about the metabolites of THC, such as 11-
OH-THC, which is physiologically active. It would also be interesting to examine
arterial blood because it has been reported that arterial drug concentrations may be
more closely related to brain function than venous concentrations (78). Combining
pharmacokinetic measures with brain imaging following controlled administration of
cannabis is a new area of research that promises to provide interesting scientific information
by examining the process of drug action from ingestion through direct physiological
changes in regions of the brain.
A related question may be: What information can plasma THC concentrations
give us about receptor function? Recently, cannabinoid receptors, CB1 and CB2, and
endogenous cannabinoid neurotransmitters have been characterized, primarily from
in vitro and animal studies (79–82). In this line of research, cannabinoids with potenHuman
Cannabinoid Pharmacokinetics 217
tial as pharmacotherapies are often evaluated by first studying their interactions with
cannabinoid receptors in animals or in vitro, and then examined in human trials.
SR141716 (named rimonabant), the first CB1-selective cannabinoid receptor antagonist,
was shown to block many of the effects of THC in animals (83,84). In a controlled
clinical study of THC’s cardiovascular and subjective effects in humans, Huestis
et al. found that a single 90-mg oral dose of rimonabant antagonized increases in heart
rate and subjective effects following smoked cannabis (85). It was important to determine
whether the observed reductions in effects were a result of a receptor-mediated
pharmacodynamic change or simply a pharmacokinetic interaction reducing the available
THC. The investigators found that there were no statistically significant differences
between peak and area-under-the-curve plasma concentrations of THC in the
placebo and active rimonabant groups. Therefore, blockade of tachycardia and subjective
effects by rimonabant following smoked marijuana was not a result of an alteration
in THC pharmacokinetics. In addition to its role as a pharmacological tool to
investigate the endogenous cannabinoid system, the antagonist appears to have potential
efficacy in humans for smoking cessation (86) and weight loss (87); phase III
trials are ongoing for these medical indications. Other potential therapeutic roles for
this antagonist are being actively investigated as well.
Clinical trials are evaluating the efficacy of THC, cannabidiol, and other cannabinoids
in the treatment of nausea after cancer chemotherapy, appetite loss, multiple
sclerosis, and neuropathic pain (16). A common clinical question might be: How will
monitoring plasma cannabinoid concentrations aid clinical management of these
patients? As with any new pharmaceutical preparation, it is necessary to study the
drug’s pharmacokinetics to more clearly understand required doses, frequency of dosing,
contributions of metabolites to effects or toxicity, elimination profiles, and metabolism
and excretion in different populations, including newborns, children, ethnic groups,
diseased individuals, and the elderly. For example, one must determine the median
effective dose, ED50, for these populations to assist clinicians who must prescribe doses
that will be efficacious but avoid toxicity.
Another concern of clinicians prescribing medications is abuse liability. It has
been shown that the route of administration affects the abuse liability of a drug (88).
As discussed above, inhalation of smoked cannabis, which results in rapid increases
in THC concentrations, can be an effective way for individuals to titrate their THC
dose, but may increase its abuse liability. Most clinical trials are evaluating oral, sublingual,
or inhaler formulations to better control dose and reduce toxic side effects
from smoking. This is expected to reduce the abuse liability as well. Well-designed
clinical trials that include pharmacokinetic analyses in tandem with clinical assessment
of patients are needed to establish the efficacy and pharmacokinetics of these
new preparations and new delivery routes.
7.2. Urine
Many governmental and private organizations in the United States employ drug
testing as part of their drug use-prevention programs. Urine is the biological matrix
most commonly tested to identify individuals who use drugs. In 2003 it was estimated
that more than 20 million urine specimens were collected for drug testing in United
218 Huestis and Smith
States programs. Drug testing is also an important objective outcome measure of drug
treatment, drug research investigating efficacy of new behavioral therapies, criminal
justice, military programs, and emergency, pediatric, and geriatric medicine. A common
example is judicial programs that routinely collect urine from individuals on
parole. Individuals committing crimes and having a positive urine drug test may be
placed in treatment while on parole if the judge believes that drug use contributed to
the crime. Parolees are ordered to attend a rehabilitation program, are given a short
period of time to eliminate previously self-administered drugs from their bodies, and,
as a condition of continued parole, must discontinue use of prohibited drugs. To ensure
compliance, treatment managers routinely have the parolee donate urine specimens,
and if there is a positive urine test indicating new drug use, the donor may be
sent to prison. This example sets the stage for an important social question. If a parolee
who was a chronic marijuana user had a sequential set of urine tests during his
first week of rehabilitation with decreasing concentrations of THCCOOH from 1000
ng/mL down to 100 ng/mL by the end of the week, and then donated a urine specimen
with a concentration of 150 ng/mL, does this increase in urine concentration indicate
new use in violation of his parole?
Figure 4 shows a typical urinary excretion profile for THCCOOH in an infrequent
marijuana user following smoking of a single marijuana cigarette. As mentioned
previously, there is great inter- and intrasubject variability in the urinary excretion of
cannabinoids. Many investigators have published studies showing that in a sequential
series of urine specimens from individuals who abstained from smoking cannabis,
there can occasionally be urine specimens that have higher concentrations of THCCOOH
than previous samples (89–91). This could be a result of residual excretion of
drug that has been stored in the body following chronic cannabinoid use. Most of
these increases in concentration appear to be related to individuals’ hydration states
that are determined by fluid intake, environmental temperature, levels of activity, disease
states, and a multitude of other variables. Urine may be diluted and drug concentrations
reduced as a result of ordinary variations in daily activity or purposeful attempts
to adulterate the sample by specimen dilution, achieved by simply drinking large quantities
of fluid. In controlled studies of cocaine and cannabinoid administration followed
by consumption of different amounts of liquids, investigators were able to
demonstrate large reductions in urine drug concentrations. In many cases, results fell
below cutoff concentrations for a positive test (92).
Manno et al. first suggested that urinary THCCOOH could be normalized to
urinary creatinine concentration to account for specimen dilution (91). They recommended
a quotient cutoff of
1.5 to identify new drug use. Huestis and Cone addressed
this problem by examining more than 1800 urine specimens collected following controlled
THC administration (89). They found that the greatest accuracy (85.4%) in
predicting new cannabis use occurred when paired specimens collected at least 24
hours apart had a quotient of
0.5 for the [THCCOOH]/[creatinine] in specimen 2
divided by the [THCCOOH]/[creatinine] for specimen 1. If the 1.5 ratio was used, as
proposed by Manno, almost 30% of the cases of new drug exposure would be missed.
Figure 4 shows that normalizing the THCCOOH concentration to creatinine concentrations
makes the excretion pattern more predictable, i.e., it has fewer abrupt changes
in the exponential decrease.
Human Cannabinoid Pharmacokinetics 219
The Huestis and Cone study examined infrequent cannabis users and did not
address excretion patterns that one would expect from chronic use. As mentioned,
chronic users take longer than infrequent users to eliminate marijuana metabolites.
This is a result of the disposition of THC into poorly perfused tissues such as fat. With
chronic cannabis use, THC concentrations in these poorly perfused compartments
increase, forming less accessible depots of THC in the body. Hunt and Jones demonstrated
that the slow return of THC from these depots into the plasma was the ratelimiting
step in the terminal elimination of THC from the body (36). Fraser and Worth
studied a group of 26 chronic marijuana users, testing both the Manno and Huestis
criteria for new use and had a false-negative rate of 7.4% with the Huestis guideline
and 24% with the Manno rule (93). They extended the study to include 37 chronic
marijuana users with at least 48 hours between specimens; with the >0.5 cutoff, new
drug use was identified in 80–85% of cases (94). Of course, the smaller the ratio used,
the greater the potential for false-positive results. The reasons for conducting the urine
test, i.e., treatment or parole, and the impact of the results on the donor guide the
choice of which ratio to apply.
Based on this valuable scientific information, we can answer the question about
whether the individual on parole in our example had smoked marijuana between
donating the specimen containing 100 ng/mL THCCOOH and the specimen with
150 ng/mL THCCOOH. The answer is that we cannot tell if he used cannabis in violation
of his conditions for parole. Additional information is needed to differentiate
between new cannabis use and residual drug excretion. This spike in urine concentration
would not be unusual for an individual who had complied with his treatment
protocol. If the treatment center had collected the specimens at least 24 hours apart
and had measured creatinine concentrations, we would have additional information to
provide a more definitive answer. If the outcome of the evaluation could be used to
place the individual, who was a former chronic cannabis user, in prison for continuing
use after entering his rehabilitation program, the higher ratio of 1.5 might be a better
choice for evaluating his urine tests. This would achieve better specificity, rather than
sensitivity. In addition, more frequent monitoring may be useful if urine specimens
are being collected more than 48 hours apart.
7.3. Oral Fluid
Oral fluid is composed of saliva and secretions from the nasopharyngeal area
and mouth. Mechanisms of drug entry into oral fluid are not fully understood. Scientists
have determined that passive diffusion from blood and tissue depots and direct
entry into oral fluid following smoked, oral, sublingual, or snorted routes of drug
administration are the primary sources. In rare cases (e.g., lithium), active transport
mechanisms also may contribute. Some of the factors affecting how much drug enters
oral fluid from the blood are the lipophilicity of the drug, the degree of plasma protein
binding, the drug’s pKa, and pH differences between blood and oral fluid. In general,
if the drug is not extensively bound to plasma proteins, is lipophilic, and is present in
an unionized state, passive diffusion is the primary mechanism for drug entry into oral
fluid. The lower pH in oral fluid as compared with blood can result in ion trapping of
drugs with a higher pKa (e.g., codeine), which has concentrations three to four times
220 Huestis and Smith
higher in oral fluid (95). In general, detection times for drugs in oral fluid range from
a few hours to 1 or 2 days following use (see Fig. 7).
There are few data on the disposition of cannabinoids in oral fluid following
controlled cannabis administration. Scientists have known that THC is present in oral
fluid since the 1970s (96,97), and in the 1980s Gross et al. found that they could detect
THC in saliva with RIA for 2–5 hours in 35 subjects who smoked one marijuana
cigarette containing 27 mg THC (98). However, the specificity of this assay was low,
with frequent false-positive results. One of the first studies to examine cannabinoid
concentrations in oral fluid after intravenous administration of radiolabeled THC found
no radioactivity in the oral fluid, indicating that THC in oral fluid after smoking was a
result of direct contamination of the oral mucosa and oral fluid in the mouth, and not
from passive diffusion from plasma (99). Another study examined oral fluid following
the smoking of 1.75 and 3.55% marijuana cigarettes by six participants (100).
Specimens were collected by expectoration before and periodically up to 72 hours
after smoking. All specimens were analyzed for cannabinoids using specific RIAs for
THC and THCCOOH, with cutoff concentrations of 1.0 and 2.5 ng/mL, respectively.
THC was detected in oral fluid for up to 24 hours after the higher dose. No specimens
were positive for THCCOOH by RIA. In addition, one participant’s specimen set was
analyzed by GC/MS for THC, 11-OH-THC, and THCCOOH with LOQs of 0.5 ng/
mL. This analysis confirmed that no measurable 11-OH-THC or THCCOOH was
present throughout the time course in any of the oral fluid specimens. Niedbala et al.
studied 18 subjects who were administered single doses of marijuana by smoked (20–
25 mg) or oral (20–25 mg) routes (101). Urine and oral fluid specimens (Intercept
collection device, OraSure Technologies, Inc., Bethlehem, PA) were collected at intervals
up to 72 hours. Oral fluid was screened with a cannabinoid enzyme immunoas-
Fig. 7. General drug effects and detection time ranges in various matrices following
occasional cannabinoid use. (Personal communication from Edward J. Cone, PhD.)
Human Cannabinoid Pharmacokinetics 221
say (Intercept Micro-Plate EIA, OraSure Technologies, Inc.) with a cutoff concentration
of 1.0 ng/mL and confirmed for THC by GC tandem MS, cutoff concentration of
0.5 ng/mL. Urine was screened by cannabinoid immunoassay (Abuscreen Online, Roche
Diagnostics, Inc., Indianapolis, IN) and GC-MS for THC-COOH, cutoff concentrations
of 50 and 15 ng/mL, respectively. Oral fluid specimens tested positive following
marijuana smoked consecutively for average periods of 13 hours. The average time of
the last positive test was 31 hours. There was great individual variation, with one
subject having the last positive specimen at 2 hours and another at 72 hours. The
decrease in oral fluid THC concentrations during the first 2 hours appeared to parallel
those published by others for plasma THC, but no plasma was collected in this study
for direct comparison. Urine specimens were consecutively positive following smoking
for an average of 26 hours. The average time for the last positive reading was 42
hours with ranges up to 72 hours, the last collection. In the oral ingestion study, each
of three subjects ate one brownie that had been cooked with plant material containing
20–25 mg of THC. THC was present in oral fluid following this method of oral ingestion,
but concentrations peaked at 1–2 hours, were low, 3–5 ng/mL, and declined rapidly
to negative, typically at 4 hours.
In recent studies oral fluid has been collected in a wide variety of devices designed
by different manufacturers. Unfortunately, the recovery of cannabinoids from these
devices is frequently unknown, a fact that significantly affects the devices’ sensitivity
in detecting cannabinoid use. Another problem area is the immunoassay reagent used
to screen oral fluid specimens for cannabinoids. Many of the manufacturer’s reagents
target THC-COOH in their antigen-antibody reactions, making the sensitivity of these
tests for cannabinoid exposure unacceptably low. Kintz et al. examined oral fluid
(Salivette), blood, forehead wipes, and urine from 198 injured drivers and found 22
positive by urine testing for THC-COOH (102). Fourteen of these patients were also
positive for THC in oral fluid, with no specimens positive for 11-OH-THC or THCCOOH
at the limits of detection for their method. Samyn et al. collected urine from
drivers who failed field sobriety tests at police roadblocks (103). For drivers who had
a positive urine test, blood specimens were collected and, following informed consent,
oral fluid (Salivette) and sweat specimens were collected. Oral fluid specimens
and plasma were collected from 180 drivers and analyzed by GC-MS with cutoff concentrations
of 5.0 and 1.0 ng/mL, respectively. The predictive value of oral fluid compared
with plasma was 90%. In a different approach, Cone et al. examined 77,218 oral
fluid specimens submitted to a large drug-testing laboratory (104). Using an oral fluid
screening cutoff concentration for cannabinoids of 3 ng/mL and a confirmation THC
cutoff concentration of 1.5 ng/mL, they found a cannabis positive rate of 3.22%, which
was similar to the positive rate of 3.17% for large urine drug-testing laboratories using
federally mandated cutoff concentrations. These studies have shown that measurement
of THC in oral fluid compares favorably with sweat and urine testing for detecting
cannabis use. Others have not found a good correlation between cannabinoid tests
for oral fluid and other body fluids (105–109). Some of this variability in performance
may be related to differences in cutoff concentrations, different screening specificities,
binding of THC by the collection devices, and large intersubject differences of
cannabinoid concentrations in biological fluids. The Substance Abuse Mental Health
222 Huestis and Smith
Services Administration, Department of Health and Human Services (SAMHSA), which
regulates federal workplace drug testing in the United States, is currently proposing a
screening cutoff of 4 ng/mL for cannabinoids and a confirmation cutoff of 2 ng/mL
THC for oral fluid (110).
Menkes et al. reported that the logarithm of salivary THC concentrations correlated
with subjective effects and heart rate (111). Based on all of the available data
and the ease of collection of oral fluid, many states and countries are considering the
use of oral fluid testing for identification of drugged drivers. A large-scale roadside
evaluation of the effectiveness of oral fluid monitoring for identifying drug-impaired
drivers is being conducted currently in Europe and the United States (112,113).
Some organizations are interested in oral fluid testing of employees before beginning
safety-sensitive work, because collection is easy and devices can give a quick
screening result on-site. We will take this setting for a question regarding oral fluid
testing. If a woman reports to a worksite to operate the reactor in a nuclear power
station and her oral fluid screens positive for THC, is the manager justified in assigning
her less sensitive duties until the test can be confirmed by a more specific method?
If the woman had signed a pre-employment agreement not to use impairing drugs
within 24 hours of reporting to work, did she violate her agreement, an act that could
result in termination of her employment? The easy answer is that we cannot prove that
she used cannabis based on a screening test. The result must be confirmed by a second
method based on a different scientific principle of identification; however, it is instructive
to examine the reliability of the result because many organizations would
remove this person from safety-sensitive duties based on a positive screening test. The
suspect employee would be returned to normal duties if the presumptive positive test
was not confirmed by further laboratory testing. If the nuclear power facility had a
drug policy outlining the terms and conditions for drug testing and ramifications of a
positive screening and confirmation test and the woman had been informed of these
regulations, then removal from a safety-sensitive position is a prudent action to take.
Can we determine when the cannabinoid exposure occurred to answer the second part
of the question? As mentioned above, with an oral collection device and screening and
confirmation cutoffs of 1 and 0.5 ng/mL, respectively, Niedbala et al. found typical
detection times of less than 24 hours, but some subjects produced a positive oral fluid
specimen 72 hours after smoking (101). If the confirmatory test is positive and the
cutoff concentrations and methodology are the same as those used in the controlled
clinical study, we may be able to limit the window of drug exposure to within the past
few days. It would be important to know the collection device and the laboratory’s
procedures, in particular the cutoff concentrations used. Unfortunately, data from wellcontrolled
clinical studies to aid our interpretation are limited. Oral fluid collection
devices and testing methodologies differ, and their performance may not have been
evaluated in controlled studies. We cannot state definitively that she violated her agreement
and used cannabis within 24 hours prior to reporting for work.
There is another interesting point to consider in the interpretation of oral fluid
results. Suppose the woman states that she did not use illegal drugs but that she was
passively exposed to marijuana smoke when her boyfriend and two of his friends
smoked cannabis in her small kitchen. Could this explain the positive oral fluid test?
Human Cannabinoid Pharmacokinetics 223
Although there are limited data in the literature, Niedbala et al. reported that two subjects
who did not smoke cannabis but were in the room when others smoked had some
positive screening but no confirmed oral fluid cannabinoid tests (101). Subsequent
studies that are not yet published but were presented at the International Association
of Forensic Toxicologists meeting in 2003 in Melbourne, Australia, and at a conference
for Medical Review Officers (personal communication from S. Niedbala of
OraSure Technologies, Inc.) conveyed the potential for passive exposure to marijuana
smoke resulting in positive screening and confirmation tests. These results occurred
when considerable smoke was present in small spaces, and oral fluid specimens were
negative within 45 minutes of the end of exposure. This situation may be analogous to
research that documented the possibility of a positive urine drug test following extensive
passive exposure to marijuana smoke in a sealed experimental room (114). Although
a positive test was produced in this experimental setting, participants complained
of noxious smoke and irritation to the eyes. Other research conducted under more
realistic passive smoke conditions indicated that production of a positive urine test
with currently mandated federal guideline cutoffs is highly unlikely (115,116). A passive
inhalation defense has rarely been accepted for a positive urine cannabinoid test.
Additional research is needed to characterize the potential for positive oral fluid cannabinoid
test from passive exposure. Perhaps the selection of appropriate oral fluid
screening and confirmation cutoff concentrations can eliminate a positive oral fluid
test from passive exposure. We lack appropriate data to answer the question of passive
exposure of oral fluid at this time and must admit that additional controlled drug administration
and naturalistic studies of drug in oral fluid are needed before we can
definitively address the woman’s claim of passive exposure.
7.4. Sweat
The substance collected for sweat testing is actually a combination of secretions
onto the skin. Cannabinoids and other drugs are transported into sweat by diffusion
from blood and other depots. Sweat from eccrine glands and sebum from apocrine
sweat glands and sebaceous glands are the main constituents. Eccrine glands are located
throughout the body near the surface of the skin, and the sweat they produce is
aqueous, contains salts, is usually in the pH range of 4.0–6.0, and is produced at variable
rates with an average of approx 20 mL per hour. Apocrine sweat glands are
located in the shaft of the hair follicle and excrete a substance that is viscous, cloudy,
and rich in cholesterol, triglycerides, and fatty acids. This secretion mixes with sebum,
a similar viscous liquid rich in triglycerides and long-chain esters, from sebaceous glands
in the hair bulb region. Sweat and sebum mix to form an emulsion on the skin surface.
When sweat is collected for testing, this mixture is the substance absorbed onto patches.
Once drugs diffuse into the glands, it is believed that eccrine sweat transports the drugs
to the surface of the skin within hours, the known time frame for sweat excretion.
Two commercial collection devices are the most commonly used, the PharmChek®
patch (PharmChem Laboratories, Dallas, TX), and Drugwipe® (Securetec, Ottobrunn,
Germany). Some investigators have also used absorbent pads and wiped the forehead
or other regions of the body, and then extracted absorbed substances from the pad.
PharmChek, the only US Food and Drug Administration-approved collection device
224 Huestis and Smith
for drugs of abuse testing, has an absorbent pad covered by a tamper-resistant adhesive
that is porous enough to allow the skin to breathe but protects against external
contamination. Some investigators believe that it is possible to contaminate the sweatcollection
pad through the adhesive cover or by insufficient cleaning of the skin surface
before placement of the patch (117,118). These devices provide a cumulative
record of drug use over the wear time for the patch, usually 7 days, in many instances
increasing the sensitivity of drug detection over other monitoring techniques. The
Drugwipe device, which employs an absorbent material to wipe the skin and an immunochemical
test strip for drug detection, has been evaluated in some studies
(102,107,119).
There are few published reports of cannabinoid concentrations in sweat following
drug use. One issue is that the collection device does not accurately measure the
volume of sweat collected, analogous to the case with oral fluid collection with a
device rather than by expectoration. Therefore, scientists report the amount of drug
collected per patch, not as a concentration of drug in sweat. Another issue is that the
amount of sweat excreted and collected varies based on the amount of exercise and
ambient temperature. There also are insufficient data to evaluate recovery of cannabinoids
from the patch during sample preparation. Kintz et al. collected urine, oral
fluid, and sweat (Drugwipe) samples from injured drivers, and then tested each by
immunoassay and GC/MS. Of 22 patients who had a positive urine test, 16 also had a
positive sweat test (102). The amounts of THC in sweat ranged from 4 to 152 ng per
pad, with no detection of 11-OH-THC or THC-COOH in any specimen at the limit of
detection of the method. Samyn et al. collected blood, urine, oral fluid, and sweat (by
wiping the forehead with a fleece moistened with isopropanol) from 180 drivers who
failed a field sobriety test (103). They reported a positive predictive value compared
to plasma testing of 80% for the cannabinoid sweat test using GC/MS testing at cutoff
concentrations of 5 and 1 ng/mL, respectively. In an earlier study, Samyn and Haeren
found a high number of false-negative and some false-positive cannabinoid sweat testing
results using a Drugwipe device (107). SAMHSA has proposed guidelines for sweat
cannabinoid testing using the PharmChek patch and a wear period of 7 days with a
screening cutoff of 4 ng THC per patch and a confirmation cutoff of 1 ng THC per
patch (110).
One application of sweat testing is monitoring drug use in individuals in drug
rehabilitation programs. A tamper-proof patch is often placed on the upper arm or
back for 7 days, the collection pad is removed, drugs are eluted from the pad, and the
extract is tested for the presence of drugs. Suppose that a sweat patch were applied to
an individual who entered a drug rehabilitation program after providing a negative
urine test and the patch was removed 7 days later for testing. If a THC concentration
of 4 ng/patch was obtained, does this indicate that he had used cannabis after entrance
into the program in violation of his treatment contract?
Based on the published information available, it is most likely that THC detected
in the patch indicates cannabis use after he entered the program, assuming that the
skin was properly cleaned before applying the patch and that handling procedures
avoided contamination during patch removal and storage. However, no published studies
have related urine THC-COOH concentrations to sweat THC patch results, makHuman
Cannabinoid Pharmacokinetics 225
ing it difficult to state with certainty that the results were a result of new cannabis use.
It is expected that if the THC in the sweat patch indicated drug usage just before patch
application, the urine drug test also would have been positive. It might be that drug
depots in the skin of heavy, chronic cannabis users could continue to excrete THC in
sweat after the individual abstains from further drug use, although this hypothesis has
never been tested. It is also possible that cannabinoids could remain in sebum longer
than in urine since sebaceous glands often release sebum when they lyse, a process
that can take up to 2 weeks. Therefore, it is possible that the THC found in the patch
represented drug use before entering the program. Additional controlled drug administration
and naturalistic studies of drug excretion in sweat are needed to improve the
interpretation of cannabinoid sweat tests.
7.5. Hair
Drugs enter hair through several diffusion mechanisms; from the blood into the
highly perfused bulb of the hair shaft, from sebum and sweat along the hair root and
shaft, and from direct contact with drug in the environment (120). More basic drugs
are bound primarily to eumelanin through ionic interactions; little drug binds to
pheomelanin (121). This difference in binding properties is one explanation for higher
concentrations of basic drugs in dark colored hair, which has higher eumelanin content,
than in light-colored hair, which may have primarily pheomelanin or less total
melanin (122,123).
In general, following a single dose, basic drugs that enter hair can be detected by
the most commonly used techniques 3–7 days after drug administration, peak in 1–2
weeks, and decrease thereafter (124–126). Hair grows at a rate of about 1 cm per
month, providing an opportunity to segment hair to determine periods of drug use
over time. Studies relating time of drug use with presence in specific hair segments
have had inconsistent results. Kintz et al. have utilized segmental hair analysis to
indicate the time of drug exposure in drug-facilitated sexual assault (127), and others
have used measurement of antibiotics in hair to monitor hair growth and tie the presence
of these drugs to known times of drug administration (128). Other investigators
administered deuterated cocaine and showed that the presence of this drug was not
restricted to the appropriate hair segments but was found throughout the hair shaft
(124). These data are consistent with the theory that drug in sweat may bathe the hair
shaft and deposit drug along the length of the hair follicle. Many drugs are well protected
by hair and may be detected hundreds of years after the death of an individual
(129,130). Although questions remain about the different mechanisms of drug incorporation,
in general, drug concentrations in hair appear to be somewhat dose related,
even though the correlation is not well defined (131); that is, higher and more frequent
drug use is usually reflected in higher hair concentrations (126,132). However, most
of our knowledge about drug concentrations in hair is derived from studies of basic
drugs such as cocaine, amphetamines, and opiates. There are almost no data from
controlled cannabinoid administration studies to help us in our interpretation of cannabinoid
hair tests. This is especially important because THC is a more neutral compound
and is not thought to bind to hair through the ionic mechanisms that are important
components of incorporation of basic drugs.
226 Huestis and Smith
Furthermore, THC is present in cannabis smoke, and external contamination of
hair through this mechanism is a concern. Thorspecken et al. contaminated hair with
cannabis smoke, and then tried two different wash techniques to remove THC (133).
Their methanol and methylene chloride wash method removed most of the THC from
hair that was a result of contamination. A dodecyl sulfate wash removed external contamination
from all hair samples tested. Scientists have recommended testing for THCCOOH
in hair as another way to address the issue of external contamination with
THC; however, the concentrations of THC-COOH in hair are in the low pg/mg range,
usually requiring tandem MS or special chemical ionization MS analytical techniques
(134). These instruments may not be available to many analytical laboratories because
of the high cost of the equipment, yet the validity of testing only for THC is a highly
contested issue in forensic toxicology. The concern for reducing the possibility of
external contamination has motivated SAMHSA to propose guidelines that set the
cutoff concentrations for cannabinoids in hair at 1 pg/mg of cannabinoids for screening
and 0.05 pg/mg of THC-COOH for confirmation testing. Test results must equal
or exceed these limits before one may report a hair specimen positive when collected
in a workplace program (110).
Another complication in determining a drug’s disposition into hair and expected
values after use is the variability in analytical procedures among laboratories. Different
wash procedures are used to remove external contamination, different digestion
procedures are employed to facilitate extraction of the drug, and different analytical
procedures and instruments are utilized to identify and quantify drugs. Our understanding
of recovery of cannabinoids incorporated into authentic users’ hair is poor.
Scientists can measure the efficiency of extraction methods when cannabinoids are
spiked into hair, but this technique probably does not adequately reflect the extraction
of drug incorporated into hair following cannabis use. Cannabinoid measurements are
further complicated by the very low concentrations of drug in hair. Jurado et al. found
THC and THC-COOH concentrations in hair of cannabis and hashish users that ranged
from 0.06 to 7.63 ng/mg and 0.05 to 3.87 ng/mg, respectively (135). Cirimele et al.
found lower concentrations for THC and THC-COOH of 0.26–2.17 and 0.07–0.33 ng/mg
of hair, respectively, in 43 subjects who had died from fatal heroin overdoses (134,136).
Other investigators have found much lower concentration ranges, often in the pg/mg
range (137). Testing differences and difficulties in analyzing very low concentrations
often result in a wide range of reported concentrations, as documented by Jurado et al.
in a quality control study that had 18 laboratories analyze the same lot of hair samples
and found a 93% coefficient of variation (138).
Let us consider the question regarding the individual accused of using cannabis
before driving that resulted in a plasma THC concentration of 2 ng/mL. Suppose this
man claimed that someone put the cannabis in his food just before driving and that he
had not knowingly used cannabis in the past year. If a hair specimen were submitted
for testing to support his contention and the analysis for cannabinoids were negative,
could the man legitimately use this information to support his claim that he did not
smoke cannabis during the past year? To answer this question, we must first understand
the pharmacokinetics of cannabinoid disposition into hair. How extensive was
the laboratory’s wash procedure, what analytes were targeted, what laboratory proceHuman
Cannabinoid Pharmacokinetics 227
dures were used, and what were the cutoff concentrations? The cutoff concentrations
for the laboratory procedure are critical because for many laboratories cannabinoid
cutoff concentrations are close to the limit of detection. If we find that the laboratory
procedures were valid and cutoff concentrations similar to those recommended by
SAMHSA, we can make some assessments. For example, the driver might not have
been a chronic user of cannabis. However, we cannot say that the negative hair test
supports his assertion that he never used cannabis during the past year except
unknowingly when someone put cannabis in his food the day he was arrested. The low
concentrations of THC and metabolites in hair and the lack of published dose–response
data following controlled administration of cannabis will not allow us to answer the
question. The best answer to the original question is that the negative hair result is
supporting evidence that he is not a chronic cannabis user.
Let us suppose that the test had been positive. Could the prosecution use this
information to support their claim that the man had used cannabis prior to this most
recent incident, indicating a lie that would reflect poorly on his integrity and make his
story about unknowing ingestion less credible? Once again the procedures and cutoff
concentrations are important, but for instructive purposes we will assume they are
reliable and similar to the proposed guidelines. As mentioned, we do not have data
from studies following controlled administration of cannabis to assist in interpreting
the positive hair test result. However, the studies on cocaine, codeine, and other basic
drugs show that drugs or metabolites do not appear for at least 3–7 days when the hair
is cut, not plucked, and usually appear later if the hair testing method has removed
external contamination from sweat. If THC follows similar kinetics, its presence, along
with the presence of other cannabinoids such as cannabinol, cannabidiol, and THCCOOH,
would support the contention that the man had used cannabis, but not specifically
on the day of his arrest. What about the possibility of external contamination?
The presence of THC-COOH makes external contamination less likely because it
indicates that the drug was actually metabolized by the body. There are no data to
indicate that THC-COOH is present in cannabis smoke. Also, if appropriate wash
procedures were used, external THC contamination would be less likely and the evidence
of drug use stronger (133). The answer to the original question would be that
the presence of cannabinoids and specifically THC-COOH in the man’s hair is supporting
evidence that he used cannabis prior to the day he was stopped for driving
erratically; this evidence would not lend support to a case of impairment at the time of
arrest.
8. FINAL THOUGHTS
The information in this chapter demonstrates that the disposition and time course
of cannabinoid analytes into different biological fluids and tissues is critical for interpreting
drug test concentrations and answering related scientific and social questions.
Each matrix has advantages and limitations. Blood or plasma interacts with cells
throughout the body, including the central nervous system; cannabinoid concentrations
in these biofluids more closely relate to drug effects, but the window of drug
detection is usually limited to hours. Urine, a depot for waste, has an analysis time
228 Huestis and Smith
frame of days for detecting drug use and provides important information about drug
metabolism, but concentrations of urine cannabinoids are difficult to relate to effects
of the drug. Oral fluid appears to absorb THC directly from contact with cannabis and
is a convenient fluid for detecting recently smoked cannabis. Concentrations of drugs
in sweat are difficult to determine as a result of problems obtaining an accurate volume
of excreted sweat, but detecting drugs in sweat patches or wipes has important
applications for detecting drug use occurring over 1–2 weeks. Drugs appear to be
more stable in hair and have larger windows of detection, from weeks to years. Analysis
of each of these matrices offers unique scientific information. Knowledge of the
disposition of drugs and metabolites in these fluids and tissues after controlled drug
administration provides a powerful pharmacokinetic database for scientists who are
called upon to give science-based answers to important questions that have a major
impact on our society.
ACKNOWLEDGMENTS
The authors wish to thank Beverly Cepl, Karen Schaeffer, David Darwin, Deborah
Price, and Insook Kim, Ph.D., for providing assistance with the reference material for
the manuscript.
REFERENCES
1. Huestis, M. A. (2002) Cannabis (marijuana)—effects on human behavior and performance,
in The Effects of Drugs on Human Performance and Behavior (Farrell, L. J.,
Logan, B. K., and Dubowski, K. M., eds.), Central Police University Press, Taipei, pp.
15–60.
2. Grotenhermen, F. (2003) Pharmacokinetics and pharmacodynamics of cannabinoids.
Clin. Pharmacokinet. 42, 327–360.
3. Turner, C. E., ElSohly, M. A., and Boeren, E. G. (1980) Constituents of cannabis sativa
L. XVII. a review of the natural constituents. J. Nat. Products 43, 169–234.
4. Turner, C .E., Hadley, K. W., Fetterman, P. S., Doorenbos, N. J., Quimby, M. W., and
Waller, C. (1973) Constituents of Cannabis sativa L. IV: Stability of cannabinoids in
stored plant material. J. Pharm. Sci. 62, 1601–1605.
5. Turner, C. E., Bouwsma, O. J., Billets, S., and ElSohly, M. A. (1980) Constituents of
cannabis sativa L. XVIII-electron voltage selected ion monitoring study of cannabinoids.
Biomed. Mass Spectrom. 7, 247–256.
6. Turner, C. E. (1983) Cannabis: the plant, its drugs, and their effects. Aviat. Space Environ.
Med. 54, 363–368.
7. ElSohly, H. N., Boeren, E. G., Turner, C. E., and ElSohly, M. A. (1984) Constituents of
cannabis sativa L. XXIIII: Cannabitetrol, a new Polyhydroxylated cannabinoid, in The
Cannabinoids: Chemical, Pharmacologic and Therapeutic Aspects (Agurell, S., Dewey,
W. L., and Willette, R. E., eds.), Academic Press, Inc., Orlando, FL, pp. 89–96.
8. Turner, C. E., Hadley, K., and Fetterman, P. S. (1973) Constituents of cannabis sativa L.
VI: Propyl homologs in samples of known geographical origin. J. Pharm. Sci. 62, 1739–
1741.
9. Hemphill, J. K., Turner, J. C., and Mahlberg, P. G. (1980) Cannabinoid content of individual
plant organs from different geographical strains of cannabis sativa L. J. Nat. Products
43(1), 112–122.
Human Cannabinoid Pharmacokinetics 229
10. Iversen, L. (2003) Cannabis and the brain. Brain 126, 1252–1270.
11. Roth, M. D., Baldwin, G. C., and Tashkin, D. P. (2002) Effects of delta-9-tetrahydrocannabinol
on human immune function and host defense. CPL 121, 229–239.
12. Salmeron, B. J. and Stein, E. A. (2002) Pharmacological applications of magnetic resonance
imaging. Psychopharmacol. Bull. 36, 102–129.
13. Mathew, R. J., Wilson, W. H., Turkington, T. G., et al. (2002) Time course of tetrahydrocannabinol-
induced changes in regional cerebral blood flow measured with positron emission
tomography. Psychiatry Res. Neuroimaging 116, 173–185.
14. Kumar, R. N., Chambers, W. A., and Pertwee, R. G. (2001) Pharmacological actions and
therapeutic uses of cannabis and cannabinoids. Anaesthesia 56, 1059–1068.
15. Pertwee, R. G. (2002) Cannabinoids and multiple sclerosis. Pharmacol. Ther. 95, 165–174.
16. Mechoulam, R. and Hanu, L. (2001) The cannabinoids: an overview. Therapeutic implications
in vomiting and nausea after cancer chemotherapy, in appetite promotion, in multiple
sclerosis and in neuroprotection. Pain Res. Manag. 6, 67–73.
17. Baker, D., Pryce, G., Giovannoni, G., and Thompson, A.J. (2003) The therapeutic potential
of cannabis. Lancet Neurol. 2, 291–298.
18. Ross, S. A., Mehmedic, Z., Murphy, T. P., and ElSohly, M. A. (2000) GC-MS analysis of
the total delta-9-THC content of both drug- and fiber-type cannabis seeds. J. Anal.
Toxicol. 24, 715–717.
19. Pitts, J. E., Neal, J. D., and Gough, T. A. (1992) Some features of Cannabis plants grown
in the United Kingdom from seeds of known origin. J. Pharm. Pharmacol. 44, 947–951.
20. ElSohly, M. A., Ross, S. A., Mehmedic, Z., Arafat, R., Yi, B., and Banahan, B. F. III
(2000) Potency trends of delta-9-THC and other cannabinoids in confiscated marijuana
from 1980-1997. J. Forensic Sci. 45, 24–30.
21. Drug Enforcement Administration (2003) Illegal drug price and purity report. DEA-02058
April, 1–16.
22. Claussen, U. and Korte, F. (1968) Concerning the behavior of hemp and of delta-9-6a,10atrans-
tetrahydrocannabinol in smoking. Justus Liebigs. Ann. Chem. 713, 162–165.
23. Abrams, R. M., Davis, K. H., Jaeger, M. J., and Szeto, H .H. (1985) Marijuana smoke
production and delivery system, in Marihuana ’84 Proceedings of the Oxford Symposium
on Cannabis (Harvey, D. J., Paton, S. W., and Nahas, G. G., eds.), IRL Press Limited,
Oxford, pp. 205–209.
24. Davis, K. H., McDaniel, I. A., Cadwell, L. W., and Moody, P. L. (1984) Some smoking
characteristics of marijuana cigarettes, in The Cannabinoids: Chemical, Pharmacologic,
and Therapeutic Aspects (Agurell, S., Dewey, W. L., and Willette, R. E., eds.), Academic
Press, Orlando, FL, pp 97–109.
25. Ohlsson, A., Lindgren, J. E., Wahlen, A., Agurell, S., Hollister, L. E., and Gillespie, H.K.
(1980) Plasma delta-9-tetrahydrocannabinol concentrations and clinical effects after oral
and intravenous administration and smoking. Clin. Pharmacol. Ther. 28, 409–416.
26. Agurell, S., Halldin, M., Lindgren, J. E., et al. (1986) Pharmacokinetics and metabolism
of delta1-tetrahydrocannabinol and other cannabinoids with emphasis on man.
Pharmacol. Rev. 38, 21–43.
27. Azorlosa, J. L., Heishman, S. J., Stitzer, M. L., and Mahaffey, J. M. (1992) Marijuana
smoking: effect of varying delta 9-tetrahydrocannabinol content and number of puffs. J.
Pharmacol. Exp. Ther. 261(1), 114–122.
28. Heishman, S. J., Stitzer, M. L., and Yingling, J. E. (1989) Effects of tetrahydrocannabinol
content on marijuana smoking behavior, subjective reports, and performance.
Pharmacol. Biochem. Behav. 34, 173–179.
29. Tinklenberg, J. R., Melges, F. T., Hollister, L. E., and Gillespie, H. K. (1970) Marijuana
and immediate memory. Nature 226, 1171–1172.
230 Huestis and Smith
30. Huestis, M. A., Henningfield, J. E., and Cone, E. J. (1992) Blood cannabinoids. I. Absorption
of THC and formation of 11-OH-THC and THCCOOH during and after smoking
marijuana. J. Anal. Toxicol. 16, 276–282.
31. Mason, A. P. and McBay, A. J. (1984) Ethanol, marijuana, and other drug use in 600
drivers killed in single-vehicle crashes in North Carolina, 1978-1981. J. Forensic Sci. 29,
987–1026.
32. Law, B., Mason, P. A., Moffat, A. C., Gleadle, R. I., and King, L. J. (1984) Forensic
aspects of the metabolism and excretion of cannabinoids following oral ingestion of cannabis
resin. J. Pharm. Pharmacol. 36, 289–294.
33. Ohlsson, A., Lindgren, J. E., Wahlen, A., Agurell, S., Hollister, L. E., and Gillespie, H.K.
(1981) Plasma levels of delta-9-tetrahydrocannabinol after intravenous, oral and smoke
administration. NIDA Monograph 34, 250–256.
34. Wall, M. E., Sadler, B. M., Brine, D., Taylor, H., and Perez-Reyes, M. (1983) Metabolism,
disposition, and kinetics of delta-9-tetrahydrocannabinol in men and women. Clin.
Pharmacol. Ther. 34, 352–363.
35. Perez-Reyes, M., Timmons, M. C., Davis, K. H., and Wall, E. M. (1973) A comparison of
the pharmacological activity in man of intravenously administered delta-9-tetrahydrocannabinol,
cannabinol and cannabidiol. Experientia 29, 1368–1369.
36. Hunt, C. A. and Jones, R. T. (1980) Tolerance and disposition of tetrahydrocannabinol in
man. J. Pharmacol. Exp. Ther. 215, 35–44.
37. Kelly, P. and Jones, R. T. (1992) Metabolism of tetrahydrocannabinol in frequent and
infrequent marijuana users. J. Anal. Toxicol. 16, 228–235.
38. Harvey, D. J. (2001) Absorption, distribution, and biotransformation of the cannabinoids,
in Marijuana and Medicine (Nahas, G. G., Sutin, K. M., Harvey, D. J., and Agurell, S.,
eds.), Humana Press, Totowa, NJ, pp. 91–103.
39. Johansson, E., Noren, K., Sjovall, J., and Halldin, M. M. (1989) Determination of delta-
1-tetrahydrocannabinol in human fat biopsies from marihuana users by gas chromatography-
mass spectrometry. Biomed. Chromatogr. 3, 35–38.
40. Kreuz, D. S. and Axelrod, J. (1973) Delta-9-tetrahydrocannabinol: localization in body
fat. Science 179, 391–393.
41. Johansson, E., Agurell, S., Hollister, L. E., and Halldin, M. M. (1988) Prolonged apparent
half-life of delta-1-tetrahydrocannabinol in plasma of chronic marijuana users. J.
Pharm. Pharmacol. 40, 374–375.
42. Iribarne, C., Berthou, F., Baird, S., et al. (1996) Involvement of cytochrome P450 3A4
enzyme in the N-demethylation of methadone in human liver microsomes. Chem. Res.
Toxicol. 9, 365–373.
43. Matsunaga, T., Iwawaki, Y., Watanabe, K., Yamamoto, I., Kageyama, T., and Yoshimura,
H. (1995) Metabolism of delta-9-tetrahydrocannabinol by cytochrome P450 isozymes
purified from hepatic microsomes of monkeys. Life Sci. 56, 2089–2095.
44. Lemberger, L., Silberstein, S. D., Axelrod, J., and Kopin, I. J. (1970) Marihuana: studies
on the disposition and metabolism of delta-9-tetrahydrocannabinol in man. Science 170,
1320–1322.
45. Ben-Zvi, Z., Bergen, J. R., Burstein, S., Sehgal, P. K., and Varanelli, C. (1976) The metabolism
of delta-tetrahydrocannabinol in the rhesus monkey, in The Pharmacology of
Marihuana (Braude, M. C. and Szara, S., eds.), Raven Press, New York, pp. 63–75.
46. Greene, M. L. and Saunders, D. R. (1974) Metabolism of tetrahydrocannabinol by the
small intestine. Gastroenterology 66, 365–372.
47. Krishna, D. R. and Klotz, U. (1994) Extrahepatic metabolism of drugs in humans. Clin.
Pharmacokinet. 26, 144–160.
48. Watanabe, K., Tanaka, T., Yamamoto, I., and Yoshimura, H. (1988) Brain microsomal
oxidation of delta-8- and delta-9-tetrahydrocannabinol. Biochem.and Biophys. Res.
Commun. 157, 75–80.
Human Cannabinoid Pharmacokinetics 231
49. Widman, M., Nordqvist, M., Dollery, C. T., and Briant, R. H. (1975) Metabolism of
delta-1-tetrahydrocannabinol by the isolated perfused dog lung. Comparison with in vitro
liver metabolism. J. Pharm. Pharmacol. 27, 842–848.
50. Harvey, D. J. and Paton, W. D. M. (1984) Metabolism of the cannabinoids. Rev. Biochem.
Toxicol. 6, 221–264.
51. Mechoulam, R., BenZvi, Z., Agurell, S., et al. (1973) Delta-6 tetrahydrocannabinol-7-oic
acid, a urinary delta-6-THC metabolite: isolation and synthesis. Experientia 29, 1193–1195.
52. Sporkert, F., Pragst, F., Ploner, C. J., Tschirch, A., and Stadelmann, A. M. (2001) Pharmacokinetic
investigations and delta-9-tetrahydrocannabinol and its metabolites after
single administration of 10 mg Marinol in attendance of a psychiatric study. The Annual
Meeting of The International Association of Forensic Toxicologists, Prague, Czech Republic,
Abstract P62.
53. Halldin, M. M., Widman, M., Bahr, C. V., Lindgren, J. E., and Martin, B. R. (1982)
Identification of in vitro metabolites of delta1-tetrahydrocannabinol formed by human
livers. Drug Metab. Dispos. 10, 297–301.
54. Garrett, E. R. and Hunt, C. A. (1977) Pharmacokinetics of delta-9-tetrahydrocannabinol
in dogs. J. Pharm. Sci. 66, 395–407.
55. Williams, P. L. and Moffat, A. C. (1980) Identification in human urine of delta-9-tetrahydrocannabinol-
11-oic glucuronide: a tetrahydrocannabinol metabolite. J. Pharm.
Pharmacol. 32, 445–448.
56. Huestis, M. A., Mitchell, J. M., and Cone, E. J. (1996) Urinary excretion profiles of 11-
nor-9-carboxy-Δ9-tetrahydrocannabinol in humans after single smoked doses of marijuana.
J. Anal. Toxicol. 20, 441–452.
57. Huestis, M. A. and Cone, E. J. (1998) Urinary excretion half-life of 11-nor-9-carboxydelta-
9-tetrahydrocannabinol in humans. Ther. Drug Monit. 20, 570–576.
58. Johansson, E. and Halldin, M. M. (1989) Urinary excretion half-life of delta1-tetrahydrocannabinol-
7-oic acid in heavy marijuana users after smoking. J. Anal. Toxicol. 13, 218–
223.
59. Cone, E. J., Johnson, R. E., Paul, B. D., Mell, L. D., and Mitchell, J. (1988) Marijuanalaced
brownies: Behavioral effects, physiologic effects, and urinalysis in humans following
ingestion. J. Anal. Toxicol. 12, 169–175.
60. Gustafson, R. A., Levine, B., Stout, P. R., et al. (2003) Urinary cannabinoid detection
times after controlled oral administration of delta-9-tetrahydrocannabinol to humans.
Clin. Chem. 49, 1114–1124.
61. Kemp, P. M., Abukhalaf, I. K., Manno, J. E., et al. (1995) Cannabinoids in humans. II.
The influence of three methods of hydrolysis on the concentration of THC and two metabolites
in urine. J. Anal. Toxicol. 19, 292–298.
62. Mason, A. P. and McBay, A. J. (1985) Cannabis: pharmacology and interpretation of
effects. J. Forensic Sci. 30, 615–631.
63. Moskowitz, H. (1985) Marijuana and driving. Accid. Anal. Prev. 17, 323–345.
64. Kurzthaler, I., Hummer, M., Miller, C., et al. (1999) Effect of cannabis use on cognitive
functions and driving ability. J. Clin. Psychiatry 60, 395–399.
65. Ramaekers, J. G., Berghaus, G., van Laar, M., and Drummer, O. H. (2004) Dose related
risk of motor vehicle crashes after cannabis use. Drug Alcohol Depend. 73, 109–119.
66. O’Kane, C. J., Tutt, D. C., and Bauer, L. A. (2002) Cannabis and driving: a new perspective.
Emerg. Med. 14, 296–303.
67. Lukas, S. E. and Orozco, S. (2001) Ethanol increases plasma delta-9-tetrahydrocannabinol
(THC) levels and subjective effects after marihuana smoking in human volunteers.
Drug Alcohol Depend. 64, 143–149.
68. Ramaekers, J. G., Robbe, H. W., and O’Hanlon, J. F. (2000) Marijuana, alcohol and
actual driving performance. Hum. Psychopharmacol. 15, 551–558.
232 Huestis and Smith
69. Huestis, M. A., Sampson, A. H., Holicky, B. J., Henningfield, J. E., and Cone, E. J.
(1992) Characterization of the absorption phase of marijuana smoking. Clin. Pharmacol.
Ther. 52, 31–41.
70. Huestis, M. A., Henningfield, J. E., and Cone, E. J. (1992) Blood cannabinoids. II. Models
for the prediction of time of marijuana exposure from plasma concentrations of delta-
9-tetrahydrocannabinol (THC) and 11-nor-9-carboxy-delta-9-tetrahydrocannabinol
(THCCOOH). J. Anal. Toxicol. 16, 283–290.
71. Cone, E. J. and Huestis, M. A. (1993) Relating blood concentrations of tetrahydrocannabinol
and metabolites to pharmacologic effects and time of marijuana usage. Ther.
Drug Monit. 15, 527–532.
72. Huestis, M. A., Zigbuo, E., Heishman, S. J., et al. (2002) Determination of time of last
exposure following controlled smoking of multiple marijuana cigarettes. Annual Meeting
of the Society of Forensic Toxicologists, Dearborn, MI, Abstract 26.
73. Robbe, H. W. and O’Hanlon, J. F. (1993) Marijuana and Actual Driving Performance,
U.S. Department of Transportation/National Highway Traffic Safety Administration Report,
November, pp. 1–133.
74. Drummer, O. H., Gerostamoulos, J., Batziris, H., et al. (2004) The involvement of drugs
in drivers of motor vehicles killed in Australian road traffic crashes. Accid. Anal. Prev.
36, 239–248.
75. Wilson, W., Mathew, R., Turkington, T., Hawk, T., Coleman, R. E., and Provenzale, J.
(2000) Brain morphological changes and early marijuana use: a magnetic resonance and
positron emission tomography study. J. Addict. Dis. 19, 1–22.
76. Mathew, R. J., Wilson, W. H., Coleman, R. E., Turkington, T. G., and DeGrado, T. R.
(1997) Marijuana intoxication and brain activation in marijuana smokers. Life Sci. 60(23),
2075–2089.
77. Gatley, S. J., Lan, R., Volkow, N. D., et al. (1998) Imaging the brain marijuana receptor:
development of a radioligand that binds to cannabinoid CB1 receptors in vivo. J.
Neurochem. 70, 417–423.
78. Evans, S. M., Cone, E. J., and Henningfield, J. E. (1996) Arterial and venous cocaine
plasma concentrations in humans: relationship to route of administration, cardiovascular
effects and subjective effects. J. Pharmacol. Exp. Ther. 279, 1345–1356.
79. Martin, B. R., Mechoulam, R., and Razdan, R. K. (1999) Discovery and characterization
of endogenous cannabinoids. Life Sci. 65, 573–595.
80. Pertwee, R. (1993) The evidence for the existence of cannabinoid receptors. Gen.
Pharmacol. 24(4), 811–824.
81. Devane, W. A., Hanus, L., Breuer, A., et al. (1992) Isolation and structure of a brain
constituent that binds to the cannabinoid receptor. Science 258, 1946–1949.
82. Mechoulam, R., Shabat, S. B., Hanus, L., et al. (1996) Endogenous cannabinoid ligands—
chemical and biological studies. J. Lipid Mediators Cell Signal. 14, 45–49.
83. Rinaldi-Carmona, M., Barth, F., Heaulme, M., et al. (1995) Biochemical and pharmacological
characterization of SR141716A, the first potent and selective brain cannabinoid
receptor antagonist. Life Sci. 56, 1941–1947.
84. Aceto, M. D., Scates, S. M., Lowe, J. A., and Martin, B. R. (1996) Dependence on delta9-
tetrahydrocannabinol: studies on precipitated and abrupt withdrawal. J. Pharmacol. Exp.
Ther. 278, 1290–1295.
85. Huestis, M. A., Gorelick, D. A., Heishman, S. J., et al. (2001) Blockade of effects of
smoked marijuana by the CB1-selective cannabinoid receptor antagonist SR141716.
Arch. Gen. Psychiatry 58, 322–328.
86. Cohen, C., Perrault, G., Voltz, C., Steinberg, R., and Soubrie, P. (2002) SR141716, a
central cannabinoid (CB1) receptor antagonist, blocks the motivational and dopaminereleasing
effects of nicotine in rats. Behav. Pharmacol.13, 451–463.
Human Cannabinoid Pharmacokinetics 233
87. LeFur, G., Arnone, M., Rinaldi-Carmona, M., Barth, F., and Heshmati, H. (2001)
SR141716, a selective antagonist of CB1, receptors and obesity. Annual Meeting of the
International Cannabinoid Research Society, El Escorial, Spain, Abstract 101.
88. Preston, K. L. and Jasinski, D. R. (1991) Abuse liability studies of opioid agonist-antagonists
in humans. Drug Alcohol Depend. 28, 49–82.
89. Huestis, M. A. and Cone, E. J. (1998) Differentiating new marijuana use from residual
drug excretion in occasional marijuana users. J. Anal. Toxicol. 22, 445–454.
90. Lafolie, P., Beck, O., Blennow, G., et al. (1991) Importance of creatinine analyses of
urine when screening for abused drugs. Clin. Chem. 37, 1927–1931.
91. Manno, J. E., Ferslew, K. E., and Manno, B. R. (1984) Urine excretion patterns of cannabinoids
and the clinical application of the EMIT-d.a.u. cannabinoid urine assay for
substance abuse treatment, in The Cannabinoids: Chemical, Pharmacologic, and Therapeutic
Aspects (Agurell, S., Dewey, W. L., and Willette, R. E., eds.), Academic Press,
Orlando, FL, pp. 281–290.
92. Cone, E. J., Lange, R., and Darwin, W. D. (1998) In vivo adulteration: excess fluid ingestion
causes false-negative marijuana and cocaine urine test results. J. Anal. Toxicol. 22,
460–473.
93. Fraser, A. D. and Worth, D. (1999) Urinary excretion profiles of 11-nor-9-carboxy-delta-
9-tetrahydrocannabinol: a delta-9-THCCOOH to creatinine ratio study. J. Anal. Toxicol.
23, 531–534.
94. Fraser, A. D. and Worth, D. (2003) Urinary excretion profiles of 11-nor-9-corboxy-delta-
9-tetrahydrocannabinol: a delta-9-THC-COOH to creatinine ratio study #2. Forensic Sci.
Int. 133, 26–31.
95. Kim, I., Barnes, A. J., Oyler, J. M., et al. (2002) Plasma and oral fluid pharmacokinetics
and pharmacodynamics after oral codeine administration Clin. Chem. 48, 1486–1496.
96. Just, W. W., Werner, G., Erdmann, G., and Wiechmann, M. (1975) Detection and identification
of delta-8- and delta 9-tetrahydrocannabinol in saliva of man and autoradiographic
investigation of their distribution in different organs of the monkey.
Strahlentherapie-Sonderbande 74, 90–97.
97. Maseda, C., Hama, K., Fukui, Y., Matsubara, K., Takahashi, S., and Akane, A. (1986)
Detection of delta-9-THC in saliva by capillary GC/ECD after marihuana smoking. Forensic
Sci. Int. 32, 259–266.
98. Gross, S. J., Worthy, T. E., Nerder, L., Zimmermann, E. G., Soares, J. R., and Lomax, P.
(1985) Detection of recent cannabis use by saliva delta-9-THC radioimmunoassay. J.
Anal. Toxicol. 9, 1–5.
99. Hawks, R. L. (1984) Developments in cannabinoid analyses of body fluids: implications
for forensic applications, in The Cannabinoids: Chemical, Pharmacologic, and Therapeutic
Aspects (Agurell, S., Dewey, W., and Willette, R., eds.), Academic Press, Orlando,
FL, pp. 123–134.
100. Huestis, M. A., Dickerson, S., and Cone, E. J. (1992) Can saliva THC levels be correlated
to behavior?, in American Academy of Forensic Science Annual Meeting, Fittje Brothers,
Colorado Springs, CO, p. 190.
101. Niedbala, R. S., Kardos, K. W., Fritch, D. F., et al. (2001) Detection of marijuana use by
oral fluid and urine analysis following single-dose administration of smoked and oral
marijuana. J. Anal. Toxicol. 25, 289–303.
102. Kintz, P., Cirimele, V., and Ludes, B. (2000) Detection of cannabis in oral fluid (saliva)
and forehead wipes (sweat) from impaired drivers. J. Anal. Toxicol. 24, 557–561.
103. Samyn, N., De Boeck, G., and Verstraete, A. G. (2002) The use of oral fluid and sweat
wipes for the detection of drugs of abuse in drivers. J. Forensic Sci. 47, 1380–1387.
104. Cone, E. J., Presley, L., Lehrer, M., et al. (2002) Oral fluid testing for drugs of abuse:
positive prevalence rates by intercept immunoassay screening and GC-MS-MS confirmation
and suggested cutoff concentrations. J. Anal. Toxicol. 26, 541–546.
234 Huestis and Smith
105. Gronholm, M. and Lillsunde, P. (2001) A comparison between on-site immunoassay
drug-testing devices and laboratory results. Forensic Sci. Int. 121, 37–46.
106. Jehanli, A., Brannan, S., Moore, L., and Spiehler, V. R. (2001) Blind trials of an onsite
saliva drug test for marijuana and opiates. J. Forensic Sci. 46, 1214–1220.
107. Samyn, N. and van Haeren, C. (2000) On-site testing of saliva and sweat with Drugwipe
and determination of concentrations of drugs of abuse in saliva, plasma and urine of
suspected users. Int. J. Leg. Med. 113, 150–154.
108. Yacoubian, G. S., Jr., Wish, E. D., and Perez, D. M. (2001) A comparison of saliva testing
to urinalysis in an arrestee population. J. Psychoactive Drugs 33, 289–294.
109. Walsh, J. M., Flegel, R., Crouch, D. J., Cangianelli, L., and Baudys, J. (2003) An evaluation
of rapid-point-of-collection oral fluid drug-testing devices. J. Anal. Toxicol. 27,
429–439.
110. Substance Abuse and Mental Health Services Administration. (2004) http://
workplace.samhsa.gov/.
111. Menkes, D. B., Howard, R. C., Spears, G. F., and Cairns, E. R. (1991) Salivary THC
following cannabis smoking correlates with subjective intoxication and heart rate. Psychopharmacology
103, 277–279.
112. ROSITA (2004) http://www.rosita.org. Rosita website.
113. Steinmeyer, S., Ohr, H., Maurer, H. J., and Moeller, M. R. (2001) Practical aspects of
roadside tests for administrative traffic offences in Germany. Forensic Sci. Int. 121, 33–
36.
114. Cone, E. J., Johnson, R. E., Darwin, W. D., et al. (1987) Passive inhalation of marijuana
smoke: urinalysis and room air levels of delta-9-tetrahydrocannabinol. J. Anal. Toxicol.
11, 89–96.
115. Hayden, J. W. (1991) Passive inhalation of marijuana smoke: a critical review. J. Substance
Abuse 3, 85–90.
116. Mule, S. J., Lomax, P., and Gross, S. J. (1988) Active and realistic passive marijuana
exposure tested by three immunoassays and GC/MS in urine. J. Anal. Toxicol. 12, 113–
116.
117. Kidwell, D. A., Holland, J. C., and Athanaselis, S. (1998) Testing for drugs of abuse in
saliva and sweat. J. Chromatogr. B Biomed. Sci. Appl. 713, 111–135.
118. Crouch, D. J., Cook, R. F., Trudeau, J. V., et al. (2001) The detection of drugs of abuse in
liquid perspiration. J. Anal. Toxicol. 25, 625–627.
119. Kintz, P. (1996) Drug testing in addicts: a comparison between urine, sweat, and hair.
Ther. Drug Monit. 18, 450–455.
120. Cone, E. J. (1996) Mechanisms of drug incorporation into hair. Ther. Drug Monit. 18,
438–443.
121. Borges, C. R., Roberts, J. C., Wilkins, D. G., and Rollins, D. E. (2003) Cocaine,
benzoylecgonine, amphetamine, and N-acetylamphetamine binding to melanin subtypes.
J. Anal. Toxicol. 27, 125–134.
122. Cone, E. J., Darwin, W. D., and Wang, W. L. (1993) The occurrence of cocaine, heroin
and metabolites in hair of drug abusers. Forensic. Sci. Int. 63, 55–68.
123. Rollins, D. E., Wilkins, D. G., Krueger, G. G., et al. (2003) The effect of hair color on the
incorporation of codeine into human hair. J. Anal. Toxicol. 27, 545–551.
124. Henderson, G. L., Harkey, M. R., Zhou, C., Jones, R. T., and Jacob, P. III (1996) Incorporation
of isotopically labeled cocaine and metabolites into human hair: 1. Dose-response
relationships. J. Anal. Toxicol. 20, 1–12.
125. Cone, E. J. (1990) Testing human hair for drugs of abuse. I. Individual dose and time
profiles of morphine and codeine in plasma, saliva, urine, and beard compared to druginduced
effects on pupils and behavior. J. Anal. Toxicol. 14, 1–7.
Human Cannabinoid Pharmacokinetics 235
126. Joseph, R. E., Jr., Hold, K. M., Wilkins, D. G., Rollins, D. E., and Cone, E. J. (1999) Drug
testing with alternative matrices II. Mechanisms of cocaine and codeine deposition in
hair. J. Anal. Toxicol. 23, 396–408.
127. Kintz, P., Cirimele, V., Jamey, C., and Ludes, B. (2003) Testing for GHB in hair by GC/
MS/MS after a single exposure. Application to document sexual assault. J. Forensic Sci.
48, 195–200.
128. Miyazawa, N. and Uematsu, T. (1992) Analysis of ofloxacin in hair as a measure of hair
growth and as a time marker for hair analysis. Ther. Drug Monit. 14, 525–528.
129. Baez, H., Castro, M. M., Benaventa, M. A., et al. (2000) Drugs in prehistory: chemical
analysis of ancient human hair. Forensic Sci. Int. 108, 173–179.
130. Springfield, A. C., Cartmell, L. W., Aufderheide, A. C., Buikstra, J., and Ho, J. (1993)
Cocaine and metabolites in the hair of ancient Peruvian coca leaf chewers. Forensic. Sci.
Int. 63, 269–275.
131. Goldberger, B. A., Darraj, A. G., Caplan, Y. H., and Cone, E. J. (1998) Detection of
methadone, methadone metabolites, and other illicit drugs of abuse in hair of methadonetreatment
subjects. J. Anal. Toxicol. 22, 526–530.
132. Cairns, T., Kippenberger, D. J., and Gordon, A. M. (1997) Hair analysis for detection of
drugs of abuse, in Handbook of Analytical Therapeutic Drug Monitoring and Toxicology
(Wong, S. H. Y. and Sunshine, I., eds.) CRC Press, New York, pp. 237–251.
133. Thorspecken, J., Skopp, G., and Potsch, L. (2004) In vitro contamination of hair by marijuana
smoke. Clin. Chem. 50, 596–602.
134. Kintz, P., Cirimele, V., and Mangin, P. (1995) Testing human hair for cannabis II. Identification
of THC-COOH by GC-MS-NCI as a unique proof. J. Forensic Sci. 40, 619–
622.
135. Jurado, C., Menendez, M., Repetto, M., Kintz, P., Cirimele, V., and Mangin, P. (1996)
Hair testing for cannabis in Spain and France: is there a difference in consumption? J.
Anal. Toxicol. 20, 111–115.
136. Cirimele, V., Kintz, P., and Mangin, P. (1995) Testing human hair for cannabis. Forensic
Sci. Int. 70, 175–182.
137. Cairns, T., Kippenberger, D. J., Scholtz, H., and Baumgartner, W. A. (1995) Determination
of carboxy-THC in hair by mass spectrometry, in Hair Analysis in Forensic Toxicology:
Proceedings of the 1995 International Conference and Workshop (de Zeeuw, R. A.,
Al Hosani, I., Al Munthiri, S., and Maqbool, A., eds.), The Organizing Committee of the
Conference, Abu Dhabi, pp. 185–193.
138. Jurado, C. and Sachs, H. (2003) Proficiency test for the analysis of hair for drugs of
abuse, organized by the Society of Hair Testing. Forensic Sci. Int. 133, 175–178.
236 Huestis and Smith
Medical and Health Consequences of Marijuana 237
From: Forensic Science and Medicine: Marijuana and the Cannabinoids
Edited by: M. A. ElSohly © Humana Press Inc., Totowa, New Jersey
237
Chapter 10
Medical and Health Consequences
of Marijuana
Jag H. Khalsa
1. INTRODUCTION
Marijuana is the most frequently used illegal drug in the world today. Some 146
million people, or 3.7% of the population 15–64 years of age, consumed cannabis in
2001–2003 (1). In the United States, 95 million Americans over the age of 12 have
tried marijuana at least once. In 2002, an estimated 15 million Americans had used the
drug in the month before a survey (2), representing 6.2% of the population age 12
years and older. Marijuana was used either alone or in combination with other drugs
by 75% of the current illicit drug users. Approximately 2–3 million new users of marijuana
are added each year, with about 1.1% becoming clinically dependent on it (3).
In the case of young people, according to a recent survey of high school students
known as Monitoring the Future, supported by the US National Institute on Drug Abuse
(NIDA) and conducted yearly, at least 19% of 8th graders had tried marijuana at least
once and 18% of 10th graders were ”current” drug users (i.e., had used the drug within
the past month before the survey). Among 12th graders, nearly 48% had tried marijuana
at least once, and approx 21% were ”current” marijuana users (4). Marijuana
use by young people has increased or decreased at various times during the last decade,
possibly as a result of its potency, which has been on the rise, although nonsignificantly—
from a 3% concentration of Δ9-tetrahyrocannabinol (THC; marijuana’s active
chemical constituent) in 1991 to 4.4% in 1997—possibly because of changes in the
perceptions of youths about marijuana’s dangers or other unknown factors. Research
suggests that marijuana use usually peaks in the late teens to early 20s, and then declines
in later years (5).
238 Khalsa
Marijuana use has been reported to cause adverse psychosocial and health consequences.
The psychosocial consequences of marijuana use—such as dropping out
of school, poor school performance, antisocial and other behaviors of youth—have
been the subjects of many publications. Therefore, this chapter presents current research
on the medical and health consequences of marijuana use (6), including the adverse
effects on the immune, cardiopulmonary/respiratory, hepatic, renal, endocrine, reproductive,
and central nervous systems, genetic aspects, and general health. The chapter
also includes a brief discussion of the treatment of marijuana dependence, the carcinogenic
potential of marijuana, and motor effects with respect to driving performance
and traffic accidents.
Marijuana use is associated with a myriad of pharmacological effects that may
be attributable to THC as well as to some of its less psychoactive chemical constituents,
known as cannabinoids and endocannabinoids: the latter have been observed in
the central and peripheral nervous systems, as well as in the immune, cardiovascular,
and reproductive systems. However, the physiological roles of these cannabinoids have
not yet been fully defined. Evidence suggests that endocannabinoids are involved in
the amelioration of pain, blocking of working memory, enhancement of appetite and
suckling, cardiovascular modulation including blood pressure lowering during shock,
and embryonic development. They may also be of importance in psychomotor control
and in the regulation of some immune responses (7).
The acute effects of marijuana use may include euphoria, anxiety, and panic,
especially in naïve users; impaired attention, memory, and psychomotor performance;
perceptual alterations; intensification of sensory experiences, such as eating, watching
films, listening to music; increased risk of psychotic symptoms, especially among
those who are already vulnerable because of a personal or family history of psychiatric/
psychological problems (8); and possibly increased risk of motor accidents, especially
if used concomitantly with alcohol (9).
2. IMMUNE SYSTEM EFFECTS
Marijuana impairs cell-mediated and humoral immunity in rodents and decreases
resistance to bacterial and viral infections; noncannabinoids in cannabis smoke impair
alveolar macrophages (10). However, the few nonhuman animal studies that found
adverse immunological consequences of marijuana have not been replicated in humans
(11). There is no conclusive evidence to suggest that use of marijuana impairs immune
function, as measured by number of T-cell lymphocytes, B-cell lymphocytes, macrophages,
or levels of immunoglobulin (11). No epidemiological data or data from
case reports suggest that marijuana is immunotoxic or that it increases the risk of
exacerbating other bacterial or viral diseases in marijuana users. Two recent prospective
studies of HIV infection in homosexual men showed no clear association between
marijuana use and increased risk of progression to AIDS (12,13). Kaslow and colleagues
(13) conducted a prospective study of progression to AIDS among HIV-positive
men in a cohort of 4954 homosexual and bisexual men. Marijuana use did not
predict an increased rate of progression to AIDS among men who were HIV positive,
nor was marijuana use related to changes in a limited number of measures of immunoMedical
and Health Consequences of Marijuana 239
logical functioning. Thus, although persons infected with HIV have been advised to
avoid marijuana, this advice appears to be reasonable as a general health precaution.
The fact that Marinol (dronabinol, THC) has been approved by the US Food and Drug
Administration for the treatment of anorexia associated with weight loss in patients
with AIDS and the nausea and vomiting associated with cancer chemotherapy shows
that Marinol does not impair the immune system significantly and does not exacerbate
bacterial or viral infections. It is not known whether studies have been conducted in
this area.
3. CARDIOPULMONARY/CARDIORESPIRATORY EFFECTS
Marijuana use is associated with serious cardiovascular consequences. Acutely,
marijuana increases heart rate, supine blood pressure, and, after higher doses, orthostatic
hypotension; it increases cardiac output, decreases peripheral vascular resistance,
and dose-dependently decreases maximum exercise performance. With prolonged
exposure, supine blood pressure falls, orthostatic hypotension disappears, blood volume
increases, heart rate slows, and circulatory responses to exercise diminish, which
is consistent with the centrally mediated, reduced sympathetic and enhanced parasympathetic
activity in animals. These studies were reviewed by Jones (14), who cautioned
that although marijuana’s cardiovascular effects do not seem to cause serious
health problems for young, healthy users, marijuana smoking by older people with
cardiovascular disease poses greater risks because of the resulting increased cardiac
work, increased catecholamines, carboxyhemoglobin, and hypotension. On the basis
of results from a NIDA-funded study in which more than 65,000 medical charts of
enrollees in the Kaiser Permanente Hospital system were reviewed for medical consequences
of marijuana use, Sidney (15) reported no clear temporal association of marijuana
use with hospitalizations from cardiovascular disease. On the other hand,
marijuana use was associated with an increased number of hospitalizations for respiratory
and pulmonary complications, injuries, and slightly increased mortality (discussed
in the next paragraph).
Regarding the pulmonary/respiratory consequences, chronic heavy smoking of
marijuana is associated with increased symptoms of chronic bronchitis, coughing, production
of sputum, and wheezing (16,17) and with impairment of pulmonary function,
pulmonary responsiveness, and bronchial cell characteristics in marijuana-only smokers.
Tashkin and co-workers (17) further show that chronic marijuana smoking is
associated with poorer lung function and greater abnormalities in the large airways of
marijuana smokers than in nonsmokers. In 1997, Tashkin and colleagues (18) reported
that the rate of decline in respiratory function over 8 years among marijuana smokers
did not differ from that in nonsmokers of any substance—marijuana or tobacco. However,
in another cohort there was a greater rate of decline in respiratory function among
marijuana-only smokers than in tobacco-only smokers (19). Both studies showed that
long-term smoking of marijuana increased bronchitis symptoms. Starr and Renneker
(20) also reported that marijuana smokers show significantly higher levels of cytological
components in the sputum when compared with sputum from tobacco smokers.
According to Tashkin and colleagues (21), marijuana smoking may predispose
240 Khalsa
individuals to pulmonary infection, especially patients whose immune defenses are
already compromised by HIV infection and/or cancer and related chemotherapy. They
report that THC produces a concentration-dependent reduction in T-cell proliferation
and interferon-γ production via a CB2 receptor-dependent pathway. At the level of
gene expression, THC increased expression of Th1 cytokines (interferon- γ/interleukin
[IL]-2) and reduced expression of Th2 cytokines (IL-4/IL-5). Tashkin and colleagues
(20) caution that suppression of cell-mediated immunity by THC may place marijuana
smokers at risk for infection or cancer. Caiaffa and colleagues (22) reported that the
incidence of bacterial pneumonia was almost four times higher in HIV-seropositive
subjects than among HIV-negative subjects; smoking illicit drugs (marijuana, cocaine,
or crack) had the strongest effect on risk of bacterial pneumonia among HIV-seropositive
intravenous drug users with a previous history of Peumocystic carinii pneumonia.
On the other hand, results from a NIDA-funded, randomized, prospective, controlled
clinical trial, in which HIV-infected patients on antiretroviral therapy smoked one
marijuana cigarette (containing 3.9% THC) three times daily for 21 days, Brendt and
colleagues (23) showed no significant changes in naive/memory cells, activated lymphocytes,
B-cells, or natural killer cell numbers that could be directly attributed to the
administration of cannabinoids. Thus, there were no untoward effects of cannabinoids
on immune system function in HIV patients in this short trial (23).
Polen et al. (24) identified marijuana use as a risk factor for ill health. They
examined the health effects of smoking marijuana by comparing the medical experience
of daily marijuana smokers who never smoked tobacco (n = 452) with a demographically
similar group of nonsmokers of either substance (n = 450). Frequent smokers
had a small but significant increased risk of outpatient visits for respiratory illness
(relative risk = 1.19; 95% confidence interval = 1.01, 1.41), injuries (relative risk =
1.32; confidence interval = 1.10, 1.57), and other types of illnesses compared with
nonsmokers. The authors concluded that daily marijuana smoking was associated with
an elevated risk of health care use for various health problems. There was an increased
rate of presentation for respiratory conditions among marijuana-only users, although
its significance remains uncertain because infectious and noninfectious respiratory
conditions were aggregated. Nevertheless, marijuana use was associated with increased
respiratory/pulmonary complications and increased rates of hospitalizations for such
complications among chronic marijuana smokers (12,24).
Marijuana smoking produces histopathological changes that precede lung cancer,
and long-term marijuana smoking may increase the risk of respiratory cancer (25).
Johnson and colleagues (26) presented case histories of four men with multiple, large,
upper-zone lung bullae but otherwise relatively preserved lung parenchyma. Each had
a history of significant exposure to marijuana. In three of the four cases, the tobacco
smoking had been relatively small, suggesting a possible causal role for marijuana in
the pathogenesis of this unusual pattern of bullous emphysema. aWengen (27) reported
a case series of 34 young patients (between 20 and 40 years of age) with squamous
cell carcinomas of the oral cavity in association with chronic smoking of marijuana
(unfortunately the abstract reviewed did not provide the length of marijuana or other
drug use). In another report, Caplan and Brigham (28) reported on two cases of squamous
cell carcinoma of the tongue in men who chronically smoked marijuana but had
Medical and Health Consequences of Marijuana 241
no other risk factors such as smoking of tobacco or chronic use of alcohol. Caplan (29)
also reviewed 13 reports of cancer of the mouth and larynx among chronic marijuana
smokers in Australia and the United States in the last 5 years. Five of the cases had no
other risk factors, and all were young. Caplan hypothesized that deep inhalation leads
to earlier deposition of particulate matter as a result of turbulence and internal impaction.
These reports of cancers in young individuals are of concern because such cancers
are rare among adults under the age of 60, even those who smoke tobacco and
drink alcohol (30), and also because smoke from each marijuana cigarette contains
more carcinogenic chemical constituents, such as benzopyrene, than smoke from a
tobacco cigarette (31). Thus, although no epidemiological studies show a causal relation
between lung disease, including cancer, and marijuana use, the available evidence
suggests that marijuana use may increase the risk of cancer and significant adverse
respiratory/pulmonary consequences.
4. HEPATIC AND RENAL CONSEQUENCES
No significant reports of hepatic effects in humans have been reported that could
be attributed to the use of marijuana. In the case of renal effects; a few case reports
show that use of marijuana could cause reversible renal consequences such as impaired
renal function (32), acute renal infarction (33), or renal insufficiency (34).
5. ENDOCRINE EFFECTS
Marijuana use affects endocrine and reproductive functions as well, inhibits the
secretion of gonadotropins from the pituitary gland, and may act directly on the ovary
or testis. Although the effects are subtle, it is important to determine the true incidence
of hypothalamic dysfunction, metabolic abnormalities, and mechanism of action of
marijuana from well-designed studies (35). Cannabinoids affect multiple reproductive
functions, from hormone secretion to birth of offspring (36). Schuel and colleagues
reported that endocannabinoid anandamide signaling regulates sperm functions required
for fertilization in the human reproductive tract and that abuse of marijuana could
affect these processes (36). Chronic administration of high doses of THC lowers testosterone
secretions; impairs semen production, motility, and viability; and disrupts
the ovulatory cycle in animals (37). Furthermore, according to Harclerode (38), THC
lowers testosterone levels by lowering luteinizing hormone and follicle-stimulating
hormone. Marijuana depresses the levels of prolactin, thyroid function, and growth
hormone while elevating adrenal cortical steroids. Chronic exposure of laboratory
animals (rats, mice, and monkeys) to marijuana altered the function of several accessory
reproductive organs. Reduced testosterone levels leads to reduced testicular function
and reduced prostate and seminal vesicle weights. Chronic administration of
marijuana also produces testicular degeneration and necrosis in dogs (39).
In 1986, Mendelson and colleagues (40) reported that marijuana smoking suppressed
luteinizing hormone levels in normal women but not in menopausal women
(41). Barnett et al. (42) showed that testosterone levels were depressed both after smoking
one marijuana cigarette and after intravenous infusion of THC. This antiandrogenic
effect of marijuana appears to occur through action on the hypothalamic–pituitary–
242 Khalsa
gonadal axis (37) or, in part, from inhibition of androgen action at the receptor level
(43). Besides a single case of retarded growth in a 16-year-old marijuana smoker (44),
no epidemiological studies or reports show that marijuana impairs sexual maturation
and reproduction in humans.
6. BIRTH AND LATER DEVELOPMENTAL OUTCOMES
Marijuana administration at high doses can produce teratogenic effects in mice,
rats, rabbit, and hamsters. In humans, although far from definitive, evidence from
longitudinal studies with women who abused marijuana during pregnancy suggests
that prenatal exposure to marijuana is related to some aspects of postnatal developmental
deficits in the offspring (45).
Two major studies, both funded by NIDA, have followed women who smoked
marijuana during pregnancy to examine the developmental consequences of marijuana
use on the offspring. The study by Fried and colleagues at the University of Ottawa,
Canada (46,47), examined the developmental consequences of marijuana in a cohort
of Canadian, mostly Caucasian women. Another study by Day and colleagues (48), at
the University of Pittsburgh, examined the consequences of prenatal marijuana in mainly
poor African American women who smoked marijuana during pregnancy. Such use
was reported to be associated with fetal growth retardation, as shown by reduction in
birthweight, reduced length at birth, and reduced gestation period; the latter may be a
result of the hormonal effects of marijuana. Fried (46,47) found that in the newborns,
marijuana use by the mother was associated with mild withdrawal symptoms and some
autonomic disruption of nervous system state regulation. Between 6 months and 3
years of age, after controlling for confounders, no behavioral consequences of prenatal
marijuana exposure were observed among the children. At 4 years of age, no differences
were observed between exposed and nonexposed children on global tests of
intelligence, but differences were observed in verbal ability and memory. Impairment
of verbal ability, memory, and sustained attention were also seen at 5 and 6 years of
age. The pattern of results suggested an association of prenatal marijuana exposure
with impaired “executive functioning”—the latter thought to be a marker of prefrontal
lobe functioning that may not be apparent until 4 years of age.
Day and co-workers (48) reported similar findings of impaired cognition in children
who were exposed prenatally to marijuana. Recently, Goldschmidt and colleagues
(49) reported significant effects on academic achievement in 10-year-old children who
had been exposed to prenatal marijuana. However, it is important to note that the
cognitive effects of prenatal exposure to marijuana on the offspring are quite complex,
in that marijuana exposure appears to be associated with impairment of particular
aspects of intelligence, such as tasks that require visual analysis, visual memory,
analysis, and integration among children 9–12 as well as 13–16 years of age (50). By
comparison, prenatal exposure to tobacco affects the overall IQ and verbal functioning
aspects of cognitive performance. By using the newer imaging techniques, Smith
et al. (51) reported that, with increased exposure to prenatal marijuana, there was a
significant increase in neural activity in bilateral prefrontal cortex and right premotor
cortex during response inhibition. There was also an attenuation of activity in the left
Medical and Health Consequences of Marijuana 243
cerebellum with increased prenatal exposure to marijuana when challenging the
response inhibition neural circuitry. Prenatally exposed offspring had significantly
more commission errors than nonexposed participants, but all participants were able
to perform the task with more than 85% accuracy. These findings suggest that prenatal
marijuana exposure is related to changes in neural activity during response inhibition
that may last into young adulthood (51).
7. EFFECTS ON THE BRAIN:
COGNITIVE, PSYCHOLOGICAL, AND MENTAL CONSEQUENCES
Research by Pope and Yurgelum-Todd (52), Kouri et al. (53), Solowij et al. (54),
and Block and Ghoneim (55) has shown that chronic use of marijuana was associated
with impairment of cognition, particularly affecting short-term memory and executive
functioning in humans; and this impairment did not recover after abstaining from heavy
use of marijuana (up to 5000 times in a lifetime) for at least 24 hours (52), 7 days (56),
or 6 weeks (54). However, in the study of Pope and colleagues (57), the subjects did
recover after 28 days of abstinence from marijuana use. In studies by Pope and colleagues
(52,56,57), the subjects smoked marijuana up to 5000 times in their lifetime
(8-15 years), whereas in the study by Solowij et al. (54), the subject had smoked approx
6 g of marijuana each day for about 17 years. Many other older studies have also
reported that marijuana use is associated with impairment of short-term memory and
not “old” memory.
Pope and Yurgelum-Todd (52) found that heavy use of marijuana is associated
with cognitive impairment in college undergraduate students. The researchers enrolled
two groups of students—65 “heavy users” (38 male, 27 female), who had smoked
marijuana a median of 29 days in the past 30 days (range 22–30) and who also displayed
cannabinoids in their urine, and 64 “light users” (31 male, 33 female), who had
smoked a median of 1 day in the previous 30 days (range 0–9) and who displayed no
urinary cannabinoids. All of the subjects were assessed by several neuropsychological
tests when they were abstinent from marijuana and other drug use for at least 19 hours.
The outcome measures were general intellectual functioning, abstraction ability, sustained
attention, verbal fluency, and ability to learn and recall new verbal and
visuospatial information. Heavy users displayed significantly greater impairment than
light users in attention/executive functions, as evidenced by greater perseverations on
card sorting and reduced learning of word lists. These differences remained after controlling
for potential confounding variables, such as estimated levels of premorbid
cognitive functioning, and for use of alcohol and other substances in the two groups. It
is not clear whether this cognitive impairment is a reslut of a residue of drug in the
brain, a withdrawal effect from the drug, or a frank neurotoxic effect of the drug.
Similarly, Fletcher and colleagues (58) reported cognitive impairment from
chronic marijuana use, but in older subjects. They studied two cohorts of older chronic
cannabis-using and cannabis-nonusing adult men. Both cohorts were comparable in
age and socioeconomic status. Polydrug users and users who tested positive for use of
cannabis at the time of cognitive assessment after a 72-hour abstention period were
excluded. The older cohort (17 users, 30 nonusers; mean age 45 years) had consumed
244 Khalsa
cannabis for an average of 34 years; the younger cohort (37 users and 49 nonusers;
mean age 28 years) had consumed cannabis for an average of 8 years. Each subject
received measures of short-term memory, working memory, and attentional skills.
Results showed that the older chronic users performed more poorly than older nonusers
on two short-term memory tests involving lists of words and on selective and
divided attention tasks associated with working memory. No significant differences
were apparent between younger users and nonusers. The authors concluded that longterm
cannabis use was associated with disruption of short-term memory, working
memory, and attention skills in older long-term cannabis users.
Crowley and colleagues (59) examined 89 seriously delinquent, drug-dependent
adolescent males 2 years after their admission to a residential treatment program. All
had at least three lifetime symptoms of conduct disorder. Of these boys, 82% were
dependent on alcohol and 81% were dependent on cannabis, and many also were
dependent on a wide variety of other substances. The boys were very aggressive by
history, and more than half had committed a crime in the past month. Many of them
also had major depression and/or attention deficit hyperactivity disorder (ADHD) at
the time of admission. Nearly half had been in jail or detention just before admission.
When followed up 2 years later, the boys showed highly significant reduction in antisocial
and criminal acts. Both major depression and ADHD had nearly disappeared.
About 40% of the group had achieved high school graduation or GED equivalency at
the time of follow-up. However, the number reporting recent drug use had changed
little, although the prevalence of heavy daily use had significantly declined. Research
shows that seriously delinquent adolescents who are heavily involved in drug-taking
behavior can improve in antisocial behaviors and depression after treatment. But the
authors emphasize the need for more research on effective treatments for the drug
dependence commonly found among delinquents.
Crowley and colleagues (60) carried out a study to determine the consequences
of marijuana use among adolescents. The subjects were 165 male and 64 female 13- to
19-year-old patients recruited from a university treatment program for delinquent,
substance-involved youths who had been referred for substance use and conduct problems
(usually from social service or criminal justice agencies). The admission criteria
were one or more dependence diagnoses and three or more lifetime conduct disorder
symptoms (stealing, lying, running away, physical cruelty). The diagnoses were: substance
dependence, 100%; conduct disorder, 82%; major depression, 17.5%; and
ADHD, 14.8%. Standardized diagnostic interview instruments were used for substance
dependence, psychiatric disorders, and patterns of substance abuse. Results showed
that of the 229 teens, 220 had dependence on at least one nontobacco substance and 9
were dependent on tobacco with abuse of other substances. On average the youths
were dependent on 3.2 substances, with marijuana and alcohol producing the most
cases. Among the marijuana-dependent teens, 31.2% reported at least daily use of
marijuana in the previous year. The rate of progression from first to regular marijuana
use was as rapid as tobacco progression and more rapid than that of alcohol, indicating
potent reinforcing effects of marijuana. Most patients described serious problems from
marijuana: more than 80% of male and 60% of female patients met criteria for marijuana
dependence, 66% of marijuana-dependent patients reported withdrawal, and more
Medical and Health Consequences of Marijuana 245
than 25% had used marijuana to relieve withdrawal symptoms (e.g., irritability, restlessness,
insomnia, anorexia, nausea, sweating, salivation, elevated body temperature,
tremor, and weight loss) that were clinically significant. About 85% said that marijuana
interfered with their responsibilities at school, at work, or at home or endangered
them while, for example, driving. Finally, the patients reported that in most
cases, conduct problems arose before marijuana use, which typically began around
the time of appearance of the third conduct disorder symptom. In summary, among
adolescents with conduct problems, marijuana is not benign; moreover, its use by
susceptible youths may be considered unsafe. It was stated that marijuana potentially
reinforced marijuana taking, producing both dependence and withdrawal (59,60).
Although “cannabis psychotic disorder” with delusions or with hallucinations is
recognized in the Diagnostic and Statistical Manual of Mental Disorders, 4th ed.,
relatively little information is available on this disorder. Gruber and Pope (61) reviewed
395 eligible charts of the 9432 admissions at two psychiatric centers between
April 1991 and October 1992 and October 1989 and November 1992, respectively,
seeking cases of cannabis-induced disorders. There were no convincing cases of a
cannabis-induced psychotic syndrome. The authors also reviewed published studies
on the subject. There were 10 series of 10 or more cases, all describing primarily
cannabis-induced psychotic syndromes. None of the 10 studies was performed in the
United States; only two have been published in the last 10 years, neither of which
supported the existence of a distinct cannabis-induced psychosis. Furthermore, most
studies were retrospective and uncontrolled. The overall evidence from both reviews
was insufficient to prove that marijuana alone can produce a psychotic syndrome in
previously asymptomatic individuals, and further research is needed to validate the
diagnosis of cannabis psychosis (61). On the other hand, more recent and excellent
reviews by Zammit and colleagues (62), Aresneault et al. (63), and Smit et al. (64)
show that marijuana use is causally associated with the development of psychosis. For
example, Zammit and colleagues concluded that cannabis use is associated with an
increased risk of developing schizophrenia, consistent with a causal relation, and that
this association is not explained by the use of other psychoactive drugs or personality
traits relating to social integration. Aresneault et al. (63) also stated that on an individual
level, cannabis use increases the risk at least twofold in the relative risk for
later schizophrenia, while at the population level, elimination of cannabis would reduce
the incidence of schizophrenia by approx 8% assuming a causal relationship.
Similarly, Smit and colleagues (64) also suggested a relationship between cannabis
use and schizophrenia. The reader is further directed to these excellent reviews on
marijuana and psychosis.
8. MARIJUANA DEPENDENCE
Animal and human studies show that marijuana can produce tolerance and
dependence. Lichtman and Martin (65) have shown that abstinence leads to clinically
significant withdrawal symptoms that can be precipitated by treating the marijuanadependent
animals with a cannabinoid receptor antagonist, SR14176A. The most prominent
signs of marijuana withdrawal in rats were wet-dog shakes; less frequent signs
246 Khalsa
included grooming, retropulsion, and stretching; while the most prominent signs in
the mice were head shakes and paw tremors. Similarly, mice exposed repetitively to
marijuana smoke exhibit a dependence syndrome similar to that produced by THC.
The development of cannabinoid or marijuana dependence in laboratory animals was
consistent with marijuana dependence in humans (57,66). Moreover, marijuana dependence
is much more similar than dissimilar to other forms of drug dependence
(67). In humans, daily marijuana smoking in healthy individuals produces dependence,
as demonstrated by withdrawal symptoms such as increased irritability and anxiety
and decreased food intake. Furthermore, some aspects of marijuana dependence can
be treated. During marijuana abstinence, sustained-release bupropion increases ratings
of irritability, depression, and stomach pain and decreases food intake compared
with placebo, suggesting ineffectiveness, whereas nefazodone was effective in
decreasing anxiety during marijuana withdrawal compared with placebo. Nefazodone
also did not alter the ratings of irritability and misery during withdrawal (66–68).
Withdrawal of marijuana after chronic use leads to “inner unrest,” increased
activity, irritability, insomnia, and restlessness in humans (69). Common symptoms
reported were hot flashes, sweating, rhinorrhea, loose stools, hiccups, and anorexia.
These symptoms were reduced by resumption of marijuana use (70). Studies from
Sweden have shown that chronic marijuana users seeking treatment became dependent
on marijuana and were unable to give up its use (71). Further epidemiological
evidence (72,73) also supports the observation that chronic marijuana use produces
dependence, the consequences of which are the loss of control over their drug use,
cognitive and motivational impairments that interfere with occupational performance,
lowered self-esteem and depression, and the complaints of spouses and partners.
In terms of marijuana-associated amotivational syndrome, the available evidence
is equivocal. Research is needed to study this rare, inadequately defined, and insufficiently
studied clinical consequence of prolonged heavy marijuana use.
9. GENETIC EFFECTS
Research shows a more than threefold and more than twofold increase over nonsmoking
pregnant women in mutations of the hypoxanthine phosphoribosyl transferase
(hprt) gene in among pregnant women who smoked marijuana and cigarettes, respectively,
early in their pregnancies and before (74). Authors indicated that these observations
from a preliminary study suggest that marijuana smokers may have an elevated
risk of cancer. For pregnant marijuana smokers, there is also concern about the possibility
of genotoxic effects on the fetus, resulting in heightened risk of birth defects or
childhood cancer.
The role of genetics in marijuana abuse was suggested by the studies of Tsuang
and colleagues (75–77). In a twin study of drug abuse, 4000 pairs of twins—monozygotic
and dizygotic—were assessed for drug abuse and dependence. They showed that
marijuana use was affected to a great extent by genetic factors. The common or family
environment made a significant contribution to the use of marijuana. Initiation of
marijuana use could be influenced by characteristics of the environment (drug availability,
peer groups) and the characteristics of the individual (personality). For the
continuation of drug use, other individual characteristics, such as physiological and
Medical and Health Consequences of Marijuana 247
subjective reactions to the drugs, may be important. Furthermore, among the marijuana
users, suspiciousness and agitation appeared to be genetically related, whereas
the pleasant psychological effects appeared to be mediated by the twins’ shared environment,
and not by genes. Using this twin model, additional studies are underway to
examine the medical and health consequences, including psychiatric consequences, of
drug abuse and genetic influences on drug use/abuse and associated conduct disorders
and antisocial behaviors in childhood and later in adults.
10. MARIJUANA AND HEALTH
Sidney (15) and Polen et al. (24) at Kaiser Permanente HMO reviewed the medical
charts of approx 65,000 patients and showed that, after adjusting for gender, age,
race, education, marital status, and alcohol use, frequent marijuana smokers (duration
of marijuana use between 5 and 15 years) had an increased risk of making outpatient
visits for respiratory illness, injuries, and “other” illnesses compared with nonsmokers. In
addition, the relative risk of cervical cancer among women who used marijuana but never
smoked tobacco was 1.42 compared with those who used marijuana. However, there was
no increased risk for other cancers in association with marijuana use. There was an increased
risk of mortality associated with ever using marijuana among men, AIDS (probably reflective
of lifestyles), injury/poisoning, and other causes of death, whereas among marijuana
using women, there was a decreased risk for mortality.
11. MARIJUANA AND CANCER
It is currently unclear whether long-term smoking of marijuana causes cancer.
As mentioned above, marijuana smoke contains more carcinogenic chemical constituents
than tobacco smoke (31); thus, one might expect to see more cases of lung cancer
than with tobacco smoking. However, no significantly large number of cases of lung
cancer or other cancers has been reported in marijuana smokers, possibly because no
such studies have ever been conducted. Recently, after controlling for age, sex, race,
education, alcohol consumption, pack-years of cigarette smoking, and passive smoking,
Zhang and colleagues (78) reported that the risk of squamous cell carcinoma of
the head and neck was increased with marijuana use in a strong dose–response pattern.
The researchers also suggested that marijuana use might interact with mutagenicity
and other risk factors to increase the risk of head and neck cancer. However, the
investigators noted that the results should be interpreted with some caution in drawing
causal inferences because of certain methodological limitations, especially with regard
to interactions between marijuana smoking and concomitant use of alcohol and
tobacco. On the other hand, on the basis of a large case–control study of head, neck, or
lung cancer in marijuana smokers, Hashibe et al. (79) reported that although the use of
tobacco and alcohol was associated with these cancers, the use of marijuana was not
associated with these cancers in young adults.
12. MARIJUANA AND HIGHWAY ACCIDENTS
The published evidence suggests that marijuana use may impair motor performance.
In a recent review, Ramaekers and colleagues (80) report that both epidemio248
Khalsa
logical and experimental studies show that marijuana use is associated with motor
accidents. Further, they state that combined use of THC and alcohol produced severe
impairment of cognitive, psychomotor, and actual driving performance in experimental
studies and sharply increased the crash risk in epidemiological analyses. Significantly
increased rates of motor vehicle injuries resulting in hospitalization have also
been reported among marijuana users (81). Despite many reports in the published
literature, the incidence and prevalence of accidents causally related to marijuana use
are not known. More research is needed to establish a causal association between
marijuana use and traffic accidents.
13. SUMMARY
For the past several years marijuana has been the most commonly abused drug in
the United States, with approx 6% of the population 12 years and older having used
the drug in the month before interview. The use of marijuana is not without significant
health risks. Marijuana is associated with effects on almost every organ system in the
body, ranging from the central nervous system to the cardiovascular, endocrine, respiratory/
pulmonary, and immune systems. Research shows that in addition to marijuana
abuse/dependence, marijuana use is associated with serious health consequences in
some studies with impairment of cognitive function in the young and old, fetal and
developmental consequences, cardiovascular effects (heart rate and blood pressure
changes), respiratory/pulmonary complications such as chronic cough and emphysema,
impairment of immune function, and risk of developing head, neck, and/or lung
cancer. In general, acute effects are better studied than those of chronic use, and more
studies are needed that focus on disentangling effects of marijuana from those of other
drugs and adverse environmental conditions. More research is needed in the following
areas: (1) the general health consequences of marijuana use, neurocognitive effects of
chronic marijuana use by adolescents and young adults using traditional as well as
newer imaging techniques; marijuana dependence in animal models and humans; marijuana
effects in various human diseases (endocrine, pulmonary/respiratory diseases;
immune dysfunction-related infections); effects of chronic marijuana use on sleep disorders;
drug interactions between marijuana and medications used in the treatment of
mental disorders or other diseases; effects of acute and chronic marijuana use on the
reproductive system; and functional assays to study neuropsychiatric/behavioral effects;
(2) in the cardiovascular area, the effects of chronic marijuana use and atherosclerotic
events (effects on clotting mechanisms; lipid metabolism) and endothelial function;
arrhythmic effects of chronic marijuana use; effects on body weight resulting from
plasma fluid retention (renal effects via renin–angiotensin–aldosterone system); and
long-term effects on coronary output using noninvasive techniques; (3) future pulmonary
and cancer studies addressing lung immunity among chronic marijuana smokers;
incidence, prevalence, and underlying pathophysiology (molecular/genetic basis) of
head and neck cancer and other cancers (cervix, prostate) associated with chronic
marijuana use; population epidemiological studies; and tumor registries to determine
whether chronic marijuana smoking is associated with cancers; and finally (4) training
for new investigators and those from other disciplines to conduct research on the
medical and health consequences of marijuana.
Medical and Health Consequences of Marijuana 249
REFERENCES
1. 2004 World Drug Report, United Nations, Office of Drugs and Crime. Oxford University
Press, Oxford, UK.
2. Substance Abuse and Mental Health Services Administration (2004) National Household
Survey on Drug Abuse, Main Findings, 2004, Rockville, MD, US Department of Health
and Human Services.
3. Wagner, F. A. and Anthony, J. C. (2002) From first drug use to drug dependence: developmental
periods of risk for dependence upon marijuana, cocaine, and alcohol.
Neuropsychopharmacology 26, 479–488.
4. 2003 Monitoring the Future, National Survey Results on Drug Use, National Institutes of
Health, Department of health and Human Services; conducted by the University of
Michigan’s Institute for Social Research, National Institute on Drug Abuse, Bethesda,
Maryland. The latest data are available at www.drugabuse.gov.
5. Chen, K. and Kandel, D. B. (1998) Predictors of cessation of marijuana use: an event
history analysis. Drug Alcohol Depend. 50(2), 109–121.
6. Khalsa, J., Genser, S., Francis, H., and Martin, B. R. (2002) Medical and health consequences
of marijuana. J. Clin. Pharmacol. 42 (11, Suppl.), 7s–10s.
7. Mechoulam, R., Parker, L. A., and Gallily, R. (2002) Cannabidiol: An over view of some
pharmacological aspects. J. Clin. Pharmacol. 42 (11, Suppl.), 11s–19s.
8. Hall, W., Solowij, N., and Lemon, J. (1994) The health and psychological consequences of
cannabis use, National Drug Strategy Monograph Series no.25, Canberra; Australian Government
Publishing Service, 1994.
9. Hall, W. and Solowij, N. (1998) Adverse effects of cannabis use. Lancet 352, 1611–1616.
10. Munson, A. E. and Fehr, K. O. (1983) Immunological effects of cannabis, in Cannabis and
Health Hazards, (Fehr K. O. and Kalant H., eds.), Addiction Research Foundation, Toronto,
Canada, pp. 257–253.
11. Hollister, L.E. (1992) Marijuana and immunity. J. Psychoactive Drugs. 24, 159–164.
12. Coates, R. A., Farewell, V. T., Raboud, J., et al. (1990) Cofactors of progression to acquired
immunodeficiency syndrome in a cohort of male sexual contacts of men with human
immunodeficiency virus disease. Am. J. Epidemiol. 132, 717–722.
13. Kaslow, R. A., Blackwelder, W. C., Ostrow, D. G., et al. (1989) No evidence for a role of
alcohol or other psychoactive drugs in accelerating immunodeficiency in HIV-1-positive
individuals. A report from the Multicenter AIDS Cohort Study. JAMA 261(23), 3424–3429.
14. Jones, R. T. (2002) Cardiovascular system effects of marijuana. J. Clin. Pharmacol. 42
(11, Suppl.), 58s–63s.
15. Sidney, S. (2002) Cardiovascular complications of marijuana use. J. Clin. Pharmacol. 42
(11, Suppl.), 64s–70s.
16. Bloom, J. W., Kaltenborn, W. T., Paoletti, P., Camilli, A., and Lebowitz, M. D. (1987)
Respiratory effects of non-tobacco cigarettes. Br. Med. J. Clin. Res. Ed. 295(6612), 1516–
1518.
17. Tashkin, D. P., Fligiel, S., Wu, T. C., et al. (1990) Effects of habitual use of marijuana and/
or cocaine on the lung. NIDA Res. Monogr. 99, 63–87.
18. Tashkin, D. P., Simmons, M. S., Sherrill, D. L., and Coulson, A. H. (1997) Heavy habitual
marijuana smoking does not cause accelerated decline in FEV1 with age. Am. J. Respir.
Crit. Care Med. 155, 141–148.
19. Sherrill, D. L., Kryzanowski, M., Bloom, J. W., and Lebowitz, M. D. (1991) Respiratory
effects of non-tobacco cigarettes: a longitudinal study in general population. Int. J.
Epidemiol. 20, 132–137.
20. Starr, K. and Renneker, M. (1994) A cytologic evaluation of sputum in marijuana smokers.
J. Family Practice 39(4), 359–363.
250 Khalsa
21. Tashkin, D.P., Baldwin, G.C., Sarafian, T., Dubinett, S., and Roth, M.D. (2002) Respiratory
and immunologic consequences of marijuana smoking, J. Clin. Pharmacol. 42(11,
Suppl.), 71s–81s.
22. Caiaffa, W. T., Vlahov, D., Graham, N. M., et al. (1994) Drug smoking, Peneumocystis
carinii pneumonia, and immunosppression increase risk of bacterial pneumonia in human
immunodeficiency virus-seropositive injection drug users, Am. J. Respir. Crit. Care Med.
150(6 Pt. 1), 1493–1498.
23. Brendt, B. M., Higuera-Alhino, D., Shade, S. B., Herbert, S. J., McCune, J. M., and Abrams,
D. I. (2002) Short-term effects of cannabinoids on immune phenotype and function in
HIV-1-infected patients. J. Clin. Pharmacol. 42 (11, Suppl.), 82s–89s.
24. Polen, M. R., Sidney, S., Tekawa, I. S., Sadler, M., and Friedman, G. D. (1993) Health care
use by frequent marijuana smokers who do not smoke tobacco. Western J. Med. 158, 596–
601.
25. Fligiel, S. E., Roth, M. D., Kleerup, E. C., Barsky, S. H., Simmons, M. S., and Tashkin, D.
P. (1997) Tracheobronchial histopathology in habitual smokers of cocaine, marijuana, and/
or tobacco. Chest 112(2), 319–326.
26. Johnson, M. K., Smith, R. P., Morrison, D., Laszlo, G., and White, R. J. (2000) Large lung
bullae in marijuana smokers. Thorax 55, 340–342.
27. aWengen, D. F. (1993) Marijuana and malignant tumors of the upper aerodigestive tract in
young patients. Laryngorhinootologie 72(5), 264–267.
28. Caplan, G. A. and Brigham, B. A. (1990) Marijuana smoking and carcinoma of the tongue.
Is there an association? Cancer 66, 1005–1006.
29. Caplan, G. A. (1991) Marihuana and mouth cancer. J. Royal Soc. Med. 84, 386.
30. Tashkin, D. P. (1993) Is frequent marijuana smoking harmful to health? Western J. Med.
158, 635–637.
31. Novotny, M., Lee, M. L., and Bartle, K. D. (1976) A possible chemical basis for the higher
mutagenicity of marijuana smoke as compared to tobacco smoke. Experentia 32(3), 280–
282.
32. Vupputuri, S., Batuman, V., Muntner, P., et al. (2004) The risk for mild kidney function
decline associated with illicit drug use among hypertensive men. Am. J. Kidney Dis. 43(4),
629–635.
33. Lambrecht, G. L., Malbrain, M. L., Coremans, P., Verbist, L., and Verhaegen, H. (1995)
Acute renal infarction and heavy marijuana smoking. Nephron 70(4), 494–496.
34. Farber, S. J. and Huertas, V.E. (1976) Intravenously injected marihuana syndrome. Arch.
Intern. Med. 136(3), 337–339.
35. Brown, T. T. and Dobs, A. S. (2002) Endocrine effects of marijuana. J. Clin. Pharmacol.
42 (11, Suppl.), 90s–96s.
36. Schuel, H., Burkman, L. J., Lippes, J., et al. (2002) Evidence that anandamide-signaling
regulates human sperm functions required for fertilization. Mol. Reprod. Dev. 63(3), 376–
387.
37. Bloch, E. (1983) Effects of marijuana and cannabinoids on reproduction, endocrine function,
development and chromosomes, in Cannabis and Health Hazards (Fehr, K. O and
Kalant, H., eds.), Addiction Research Foundation, Toronto.
38. Harclerode, J. (1984) Endocrine effects of marijuana in the male: preclinical studies. NIDA
Res. Monogr. 44, 46–64.
39. Dixit, V. P., Gupta, C. L., and Agarwal, M. (1977) Testicular degeneration and necrosis
induced by chronic administration of cannabis extract in dogs. Endocrinologie 69(3), 299–
305.
40. Mendelson, J. H., Mello, K., Ellingboe, J., Skupny, A. S., Lex, B. W., and Griffin, M.
(1986) Marijuana smoking suppresses luteinizing hormone in women. J. Pharmacol. Exp.
Ther. 237(3), 862–866.
Medical and Health Consequences of Marijuana 251
41. Mendelson, J. H., Cristofaro, P., Ellingboe, J., Benedikt, R., and Mello, N. K. (1985) Acute
effects of marihuana on luteinizing hormone in menopausal women. Pharmacol. Biochem.
Behav. 23(5), 765–768.
42. Barnett, G., Chiang, C. W., and Licko, V. (1983) Effects of marijuana on testosterone in
male subjects. J. Theor. Biol. 104(4), 685–692.
43. Purohit, V., Ahluwalia, B. S., and Vigersky, R. A. (1980) Marihuana inhibits
dihydrotestosterone binding to the androgen receptor. Endocrinology 107(3), 848–850.
44. Copeland, K. C., Underwood, L. E., and Van Wyck, J. J. (1980) Marijuana smoking and
prepubertal arrest. J. Pediatrics 96, 1079–1080.
45. Khalsa, J. H. and Gfroerer, J. (1991) Epidemiology and health consequences of drug abuse
among pregnant women. Sem. Perinatol. 15(4), 265–270.
46. Fried, P. A. (1995) The Ottawa prenatal prospective study (OPPS): methodological issues
and findings—it’s easy to throw the baby out with the bath water. Life Sciences. 56, 2159–
2168.
47. Fried, P. A. (1995) Prenatal exposure to marihuana and tobacco during infancy, early and
middle childhood: effects and an attempt at synthesis. Arch. Toxicol. Suppl. 17, 233–260.
48. Day, N. L., Richardson, G. A., Goldschmidt, L., et al. (1994) Effect of prenatal marijuana
exposure on the cognitive development of offspring at age three. Neurotoxicology & Teratology.
16(2), 169–175.
49. Goldschmidt, L., Richardson, G. A., Cornelius, M. D., and Day, N. L. (2004) Prenatal
marijuana and alcohol exposure and academic achievement at age 10. Neurotoxicol.
Teratol. 26, 521–532.
50. Fried, P. A., Watkinson, B., and Gray, R. (2003) Differential effects on cognitive functioning
in 13- to 16- year-olds prenatally exposed to cigarettes and marihuana. Neurotoxicol.
Teratol. 25(4), 427–436.
51. Smith, A. M., Fried, P. A., Hogan, M. J., and Cameron, I. (2004) Effects of prenatal marijuana
on response inhibition: an fMRI study of young adults. Neurotoxicol. Teratol. 26(4),
533–542.
52. Pope, H. G., Jr, Gruber, A. J., and Yurgelum-Todd, D. (1995) The residual neuropsychological
effects of cannabis:the current status of research. Drug Alcohol Depend. 38, 25–34.
53. Kouri, E., Pope, H. G., Jr., Yurgelun-Todd, D., and Gruber, S. (1995) Attributes of heavy
vs. occasional marijuana smokers in a college population. Biol. Psychiatry 38, 475–481.
54. Solowij, N., Grenyer, B. F., Chesher, G., and Lewis, J. (1995) Biopsychological changes
associated with cessation of cannabis use: a single case study of acute and chronic cognitive
effects, withdrawal and treatment. Life Sci. 56(23/24), 2127–2134.
55. Block, R. I. and Ghoneim, M. M. (1993) Effects of chronic marijuana use on human cognition.
Psychopharmacology 110, 219–228.
56. Pope, H. G., Jr. and Yurgelun-Todd, D. (1996) The residual cognitive effects of heavy
marijuana use in college students. JAMA 275(7), 521–527.
57. Harrison, G. P. Jr., Gruber, A. J., Hudson, J. I., Huestis, M. A., and Yiurgelun-Todd, D.
(2002) Cognitive measures in long-term cannabis users. J. Clin. Pharmacol. 42 (11,
Suppl.), 41s–47s.
58. Fletcher, J. M., Page, J. B., Francis, D. J., et al. (1996) Cognitive correlates of chronic
cannabis use in Costa Rican men. Arch. Gen. Psychiatry 53,1051–1057.
59. Crowley, T. J., Mikulich, S. K., Macdonald, M., Young, S. E., and Zerbe, G .O. (1998)
Substance-dependent, conduct-disordered adolescent males: severity of diagnosis predicts
two-year outcome. Drug Alcohol Depend. 49(3), 225–237.
60. Crowley, T. J., MacDonald, M. J., Whitmore, E. A., and Mikulich, S. K. (1998) Cannabis
dependence, withdrawal, and reinforcement among adolescents with conduct symptoms
and substance use disorders. Drug Alcohol Depend. 50 (1), 27–37.
252 Khalsa
61. Gruber, A. J. and Pope, H. G. (1994) Cannabis psychotic disorder: Does it exist? Am. J.
Addict. 1(1), 72–83.
62. Zammit, S., Allebeck, P., Andreasson, S., Lundberg, I., and Lewis, G. (2002) Self-reported
cannabis use as a risk factor for schizophrenia in Swedish conscripts of 1969: historical
cohort study. Br. Med. J. 325, 1199.
63. Arseneault, L., Cannon, M., Witton, J., and Murray, R. M. (2004) Causal association between
cannabis and psychosis: examination of the evidence. Br. J. Psychiatry 184, 110–
117.
64. Smit, F., Bolier, L., and Cuijpers, P. (2004) Cannabis use and the risk of later schizophrenia:
a review. Addiction 99(4), 425–430.
65. Lichtman, A. H. and Martin, B. R. (2002) Marijuana withdrawal syndrome in the animal
model. J. Clin. Pharmacol. 42 (11, Suppl.), 20s–27s.
66. Budney, A. J. and Moore, B. A. (2002) Development and consequences of cannabis dependence.
J. Clin. Pharmacol. 42 (11, Suppl.), 28s–33s.
67. Haney, M. (2002) Effects of smoked marijuana in healthy and HIV + marijuana smokers.
J. Clin. Pharmacol. 42 (11, Suppl.), 34s–40s.
68. Haney, M., Hart, C. L., Vosburg, S. K., et al. (2004) Marijuana withdrawal in humans:
effects of oral THC or divalproex. J. Neuropsychopharmacol. 29(1), 158–170.
69. Jones, R. T. and Benowitz, N. (1976) The 30-day trip-clinical studies of cannabis tolerance
and dependence, in Pharmacology of Marijuana, Vol. 2 (Braude, M. C. and Szara, S., eds),
Academic Press, New York.
70. Jones, R. T., Benowitz, N., and Herning, R. I. (1981) The clinical relevance of cannabis
tolerance and dependence. J. Clin. Pharmacol. 21, 143s–152s.
71. Tunving, K., Lundquist, T., and Ericksson, D. (1988) “A way out of fog”: an outpatient
program for cannabis abusers, in Marijuana: An International Research Report, (Chesher,
G., Consroe, P., and Musty, R., eds.), Australian Government Publishing Service, Canberra,
pp. 207–212.
72. Robins, L. N. and Regier, D. A. (eds) (1991) Psychiatric Disorders in America, MacMillan,
New York, Free Press.
73. Anthony, J. C. and Helzer, J. E. (1991) Syndromes of drug abuse and dependence, in Psychiatric
Disorders in America (Robins, L. N. and Regier, D. A., eds), Free Press,
MacMillan, New York.
74. Ammenheuser, M. M., Berenson, A. B., Babiak, A. E., et al. (1998) Frequencies of hprt
mutant lymphocytes in marijuana-smoking mothers and their newborns. Mutat. Res. 403(1–
2), 55–64.
75. Tsuang, M. T., Llyons, M., Isen, S., Goldberg, J., and True, W. (1993) Heritability of
initiation and continuation of drug use. Psychiatr. Genet. 3(3), 141.
76. Tsuang, M. T., Lyons, M. J., Harley, R. M., et al. (1999) Genetic and environmental
inflences on transitions in drug use. Behav. Genet. 29(6), 473–479.
77. Lyons, M. J., Toomey, R., Meyer, J. M., et al. (1997) How do genes influence marijuana
use? The role of subjective effects. Addiction 92(4), 409–417.
78. Zhang, Z. F., Morgenstern, H., Spitz, M. R., et al. (1999) Marijuana use and increased risk
of squamous cell carcinoma of the head and neck. Cancer Epidemiol. Biomarkers Prev. 8,
1071–1078.
79. Hashibe, M., Ford, D. E., and Zhang, Z. F. (2002) Marijuana smoking and head and neck
cancer. J. Clin. Pharmacol. 42 (11, Suppl.), 103s–107s.
80. Ramaekers, J. G., Berghaus, G., van Laar, M., and Drummer, O. H. (2004). Dose related
risk of motor vehicle crashes after cannabis use. Drug Alcohol Depend. 73, 109–119.
81. Gerberich, S. G., Sidney, S., Braun, B. L., Tekawa, I. S., Tolan, K. K., and Quesenberry, C.
P. (2003) Marijuana use and injury events resulting in hospitalization. Ann. Epidemiol. 13,
230–237.
Effects of Marijuana on Immune Defenses 253
From: Forensic Science and Medicine: Marijuana and the Cannabinoids
Edited by: M. A. ElSohly © Humana Press Inc., Totowa, New Jersey
253
Chapter 11
Effects of Marijuana on the Lung
and Immune Defenses
Donald P. Tashkin and Michael D. Roth
1. INTRODUCTION
Cannabis has been used as a drug for thousands of years, but marijuana smoking
has become prevalent in Western society only during the last 40 years (1,2). An annual
survey conducted in the United States from 1975 to 2002 documented that marijuana
is now the second most commonly smoked substance after tobacco (1,2). Marijuana
smoke, like tobacco smoke, is generated by the pyrolysis of dried plant leaves. As a
result, it shares thousands of chemical features in common with tobacco smoke,
including qualitatively similar amounts of carbon monoxide, cyanide, acrolein, benzene,
vinyl chlorides, aldehydes, phenols, nitrosamines, reactive oxygen species (ROS),
and a variety of polycyclic aromatic hydrocarbons (3,4). The primary distinction
between marijuana and tobacco is the presence of Δ9-tetrahydrocannabinol (THC) and
other cannabinoids in Cannabis vs the presence of nicotine in tobacco (3,4). Although
the hazardous effects of tobacco smoking have been extensively documented and
include emphysema, chronic obstructive pulmonary disease (COPD), heart disease,
and risk for developing several different types of cancer, studies on the health effects
of marijuana smoking are less abundant. The common perception is that marijuana
smoke is less toxic and that smoking a few marijuana joints per day has far fewer
consequences than smoking a pack of tobacco cigarettes (5). However, the lack of
filtering and differences in the smoking technique associated with marijuana use result
in an approximately fourfold greater deposition of tar particulates in the lung than
occurs from smoking similar amounts of tobacco (6). In addition, the concentration of
pro-carcinogens such as benz-[α]-anthracene and benzo-[α]-pyrene are up to twofold
higher in marijuana tar (3,7). The presence of irritants and pro-carcinogens in mari254
Tashkin and Roth
juana smoke and the enhanced deposition of these in the lung during smoking suggest
that habitual smoking of marijuana might result in a spectrum of respiratory consequences
similar to those described for tobacco smoking. Moreover, THC has recently
been shown to exert potent biological effects on lung epithelial cells and on the immune
system (8–10). Consequently, it is possible that regular exposure to marijuana smoke,
a large proportion of which is THC, might predispose to lung injury, pulmonary infections,
and/or tumor growth. This chapter reviews the current knowledge concerning
the pulmonary and immune consequences of marijuana smoking and THC, as briefly
outlined in Fig. 1.
2. ACUTE EFFECTS OF MARIJUANA ON AIRWAY PHYSIOLOGY
Although anecdotal reports dating back to the 19th century suggested a therapeutic
role for marijuana in the relief of asthma, formal experiments first documented
this effect in the 1970s. Smoke from marijuana cigarettes was found to produce shortterm
bronchodilation both in healthy individuals (11,12) and in patients with asthma
(13). This bronchodilator effect was clearly attributable to the presence of THC, because
oral administration of synthetic THC also produced a dose-dependent bronchodilatation
(11). Recently, a potential mechanism for this effect on bronchomotor tone was identified.
Cannabinoid type 1 (CB1) receptors were found on axon terminals of postganglionic
parasympathetic nerve fibers in rat lung. These nerve terminals are in close
proximity to airway smooth muscle (14). In the guinea pig airway, stimulation of
these receptors by the endogenous cannabinoid anandamide resulted in dose-dependent
relaxation of capsaicin-contracted airway smooth muscle, whereas anandamide
caused dose-dependent bronchoconstriction in vagotomized preparations in which airway
smooth muscle was maximally relaxed (14). These observations suggest that the
Fig. 1. Habitual marijuana smoking delivers toxic smoke components and high
concentrations of tetrahydrocannabinol to the lung with subsequent effects on the
lung, respiratory cell function, and host immune defenses.
Effects of Marijuana on Immune Defenses 255
endogenous cannabinoid system may play a regulatory role in the bidirectional control
of airway smooth muscle tone.
From a clinical standpoint, however, smoking marijuana does not have a therapeutic
role in obstructive airways diseases such as asthma. Despite its short-term bronchodilator
properties, the long-term pulmonary consequences of marijuana smoking
include airway inflammation, edema, and mucus hypersecretion (5). On the other hand,
the development of aerosolized preparations of pure THC for inhalation (15) could
produce local physiological effects with a rapid and reproducible onset of action. However,
inhalation of pure THC has been shown to induce bronchospasm in individuals
with airways hyperreactivity because of local irritant effects (16). THC can also disrupt
mitochondrial function and the generation of adenosine triphosphate (ATP) in
airway epithelial cells, as well as promote necrotic cell death (8,17). These toxic effects
occur rapidly, and the impact of THC on mucociliary function and noxious lung injury
can be significant.
3. EFFECTS OF HABITUAL MARIJUANA EXPOSURE ON THE LUNG
3.1. Animal Studies
Several long-term animal exposure studies (dog, rat, monkey) have demonstrated
extensive inflammatory changes in small airways (bronchioles) and focal inflammation
within the lung parenchyma, as well as proliferative alterations in alveolar epithelium
(18–20). On the other hand, a carefully conducted study in rats in which animals
were exposed to increasing concentrations of marijuana or tobacco smoke for 1 year
demonstrated morphological and physiological changes of emphysema (decreased
alveolar surface area and reduced lung elastic recoil) in the tobacco-exposed rats but
not in the animals exposed to a similar quantity of marijuana (21). The results of these
animal studies are difficult to extrapolate to humans because of differences in exposure
of different regions of the respiratory system to the inhaled smoke as well as
species differences.
3.2. Human Studies
3.2.1. Older Studies on the Effects of Cannabis on Respiratory
Disorders and Lung Function
Several older human studies conducted in the 1970s yielded conflicting results
concerning the impact of regular cannabis use on clinical features of chronic respiratory
disease and/or lung function (22–25). These results are difficult to interpret because
the studies were mostly small in scale, cross-sectional in design, and subject to selection
bias. In addition, many of them failed to control adequately for the important
confounding effect of concomitant tobacco use.
3.2.2. Newer Studies on the Pulmonary Consequences of Marijuana Use
Three relatively large-scale, controlled observational studies of the pulmonary
consequences of regular use of marijuana have been conduced since 1980. One longitudinal
cohort study reported on a convenience sample of heavy habitual smokers of
marijuana alone (MS; N = 144) or with tobacco (MTS; N = 134), regular smokers of
256 Tashkin and Roth
tobacco alone (TS; N = 80), and nonsmokers of either substance (NS; N = 99) recruited
from the greater Los Angeles area (26,27). A second cohort study reported on
a random stratified sample of young residents of Tucson, AZ (28,29). The third study
was a population-based approach employing a birth cohort of individuals residing in
Dunedin, New Zealand (30,31). Results of these studies have revealed a number of
adverse pulmonary consequences of habitual marijuana use (Table 1).
3.2.2.1. RESPIRATORY SYMPTOMS
All three studies reported comparable results with respect to the association
between regular marijuana smoking and chronic respiratory symptoms: the prevalence
of chronic cough and/or sputum and wheeze was significantly higher in the marijuana
smokers than in the nonsmokers, indicating a link between regular marijuana use and
symptoms of chronic bronchitis. In the Los Angeles study, the incidence of acute
lower respiratory infections was also higher in both MS and TS than NS, and the
prevalence of chronic respiratory symptoms was comparable between MS and TS
without evidence of additive effects in those who smoked both substances (26,27).
However, an additive adverse effect of combined marijuana and tobacco smoking was
suggested in the Tucson study (28,29).
3.2.2.2. LUNG FUNCTION
The Los Angeles study failed to reveal any association between marijuana smoking
and abnormalities on pulmonary function tests including sensitive tests of small airway
function, the major site of involvement in COPD, and the diffusing capacity for
carbon monoxide, a sensitive physiological indicator of emphysema. Moreover, no
impact of even heavy regular smoking of marijuana alone (average of three joints per
day) was found on the annual rate of change in the forced expiratory volume in 1
second (FEV1), an indicator of obstructive lung disease. In contrast, TS from the same
cohort study demonstrated an accelerated rate of loss of FEV1 (27), consistent with the
known predisposition of tobacco smokers to the development of COPD. These findings,
therefore, did not support the concept that marijuana smoking leads to the devel-
Table 1
Pulmonary Consequences of Habitual Marijuana Use
• Increased prevalence of acute and chronic bronchitis (26,28,30)
• Inconsistent evidence of mild, progressive airflow obstruction (26–31)
• Visual evidence of airway inflammation (mucosal erythema, edema, and increased secretions)
that correlates with inflammatory findings on airway biopsy (5)
• Histopathological alterations in tracheobronchial epithelium and subepithelium, including
squamous metaplasia, basal cell hyperplasia, goblet cell hyperplasia, loss of ciliated surface
epithelium, basement membrane thickening, epithelial inflammation, cellular disorganization,
and increased nuclear-to-cytoplasm ratio (35,36)
• Overexpression of epidermal growth factor receptor and Ki-67, a nuclear marker of cell
proliferation, by bronchial epithelial cells suggesting dysregulated growth and a risk for
progression to bronchogenic carcinoma (36)
• Epidemiological evidence of increased risk for both bacterial and opportunistic pneumonia
in HIV-seropositive individuals (83–85)
Effects of Marijuana on Immune Defenses 257
opment of COPD and are consistent with the results of the rat exposure experiments
cited above. In contrast, both the Tucson study and the Dunedin study did find evidence
of mild airflow obstruction in association with marijuana use (28,30), and the
airflow obstruction progressed over time in the continuing marijuana users (29,31). In
contrast to the Los Angeles study, these two reports suggest that regular use of marijuana
may be a risk factor for the subsequent development of COPD.
A specialized test of lung function that serves as a measure of alveolar epithelial
permeability was carried out in a subset of the participants in the Los Angeles study
(32). This test measures the rate of clearance from the lung of a radiolabeled small
molecule (99mTc-DTPA) after inhalation. Elimination of the 99mTc-DTPA through the
normally tight junctions between adjacent alveolar epithelial cells is accelerated in the
presence of epithelial cell injury. Interestingly, while the results of this test were abnormal
in regular tobacco smokers, consistent with tobacco-related lung injury, findings
in the regular smokers of marijuana only (MS) were similar to those in nonsmoking
healthy control subjects (NS). These negative results parallel the findings of a normal
diffusing capacity for carbon monoxide in the MS and provide further evidence of
disparate effects of marijuana and tobacco on lung function.
Thus, the available evidence is mixed and contradictory with regard to the possible
link between marijuana and COPD. Clearly, further research is required to resolve
these conflicting findings.
3.2.2.3. EFFECTS ON AIRWAY INJURY AND BRONCHIAL EPITHELIAL PATHOLOGY
A subset of MS, TS, MTS, and NS from the Los Angeles cohort underwent
fiberoptic bronchoscopy during which videotapes of the tracheobronchial airway
mucosa were recorded and a series of mucosal biopsies obtained. The videotapes were
reviewed in a blinded manner for the presence and degree of airway injury according
to a semiquantitative scoring system (“bronchitis index”; ref. 5). Visual evidence of
airway injury among the MS comparable to that noted in the TS was identified with
abnormal scores for mucosal erythema, swelling, and increased secretions as compared
to control NS. These visual abnormalities were corroborated by histopathological
alterations on the mucosal biopsies in which an increased number and size of
submucosal blood vessels, submucosal edema, and hyperplasia of the mucus-secreting
surface epithelial cells (goblet cells) were observed. These findings indicate that
regular smoking of marijuana by young adults leads to the same frequency, type, and
degree of aiway inflammation as that seen in the lungs of regular tobacco smokers,
despite a marked difference in the number of cigarettes smoked for the two types of
substances (~3 joints per day in the MS vs 22 tobacco cigarettes per day in the TS).
It is possible that the presence of THC in marijuana smoke directly contributes to
this higher than expected degree of airway injury. During smoking, THC is concentrated
in the particulate phase of the smoke and deposited onto the respiratory mucosa.
To examine its potential impact on cell function, endothelial cells (ECV 304 cell line),
lung tumor cells (A549 cell line), and primary human airway epithelial cells were
exposed in vitro to either purified THC or to smoke from marijuana cigarettes
(8,17,33,34). Exposure to whole marijuana smoke stimulated the formation of more
ROS than did exposure to the same amount of tobacco smoke. Furthermore, the magnitude
of ROS was directly proportional to the concentration of THC in the cigarettes
258 Tashkin and Roth
(33). Marijuana smoke exposure was also associated with a reduction in intracellular
glutathione and a toxic effect on mitochondial electron transport, resulting in ATP
depletion (8,33,34). Mitochondrial dysfunction was observed with both purified THC
and with the tar extracts from marijuana cigarettes, but not when cells were exposed to
extracts from placebo marijuana smoke (not containing THC) or regular tobacco smoke.
ATP depletion may impair important energy-dependent functions, including ciliary
activity, phagocytosis, and normal fluid and electrolyte transport. Another potential
consequence of mitochondial toxicity is an inhibition of apoptosis and the promotion
of necrotic cell death, a pattern observed when respiratory epithelial cells are exposed
to THC in vitro (17,34). The shift from apoptotic to necrotic cell death has been shown
in animal models to disrupt normal epithelial defenses and promote inflammation and
infection. Further studies are required to determine the relevance of these toxic cellular
effects of THC to the degree of lung injury observed in marijuana smokers.
Bronchial mucosal biopsies were also obtained during fiberoptic bronchoscopy
from 40 MS, 31 TS, 44 MTS, and 53 NS as part of their participation in the Los
Angeles study (35). Light microscopy revealed extensive histopathological abnormalities
in the epithelium of the MS, including goblet cell hyperplasia, reserve cell hyperplasia,
squamous metaplasia, cellular disorganization, nuclear atypia, increased mitotic
index, increased nuclear/cytoplasmic ratio, and inflammatory changes. These abnormalities
were comparable to those noted in the TS, and the data suggested additive
changes resulting from habitual use of both substances in the MTS. Some of these
histological alterations are associated with the subsequent development of bronchogenic
carcinoma in tobacco smokers (36).
Immunohistology was used to examine bronchial biopsies from 52 of the previously
mentioned subjects for abnormal expression of genes involved in the pathogenesis
of lung cancer, including overexpression of epidermal growth factor receptor (Fig.
2), a pathway that promotes autonomous cell growth, and Ki-67, a nuclear proliferation
protein involved in cell replication (36). Results of these immunohistochemical
studies revealed marked overexpression of epidermal growth factor receptor and Ki-
67 among the MS compared to the NS and even numerically greater expression than
was noted in the TS, with the suggestion of additivity in the MTS. Together with the
aforementioned light microscopic changes, these findings suggest that regular marijuana
smoking damages the airway epithelium, leading to dysregulation of bronchial
epithelial cell growth and potentially malignant transformation.
3.2.2.4. EFFECTS ON ALVEOLAR MACROPHAGES
Alveolar macrophages (AM) are key immune effector cells in the lung that protect
against infection and other noxious insults. AM were recovered by bronchoalveolar
lavage during the bronchoscopy studies performed on subjects studied in Los Angeles.
The number of AM recovered from MS was approximately twice that from NS,
whereas the yield of AM from TS and MTS was three and four times that of NS,
respectively, indicating an additive effect of the two substances on either AM recruitment
to, and/or replication in, the lung (Table 2; Fig. 3; refs. 37 and 38). The increased
accumulation of AM in the lungs of MS may be viewed as an inflammatory response
to chronic low-grade lung injury from habitual exposure to irritants, including
oxyradicals, within the smoke of marijuana. Ultrastructural examination of AM
Effects of Marijuana on Immune Defenses 259
recovered from MS revealed large irregular-shaped cytoplasmic inclusions that most
likely contain particulates from marijuana tar, possibly including metabolites of THC
and other cannabinoids (39). AM from TS also show abnormal cytosolic inclusion
bodies, and the number of these inclusions is dramatically increased in smokers of
both marijuana and tobacco (39). It seems plausible that the presence of a large number
of abnormal inclusion bodies within the cytoplasm of AM from smokers of marijuana
and/or tobacco might interfere with the function of these important immune
effector cells.
Table 2
Effects of Marijuana on Human Alveolar Macrophages
• Increased number of alveolar macrophages recovered by bronchoalveolar lavage from
habitual marijuana smokers compared to nonsmokers (37,38)
• Increased size of intracytoplasmic inclusions (39)
• Impaired ability to kill Candida albicans (40) and Candida pseudotropicalis (41)
• Impaired phagocytosis and killing of Staphylococcus aureus (41,42)
• Decreased respiratory burst activity (superoxide anion production) under both basal and
stimulated conditions (40)
• Limited tumoricidal activity against tumor cell targets in vitro (41)
• Reduced production of proinflammatory cytokines (tumor necrosis factor-α, interleukin-6,
and granulocyte macrophage–colony-stimulating factor [GM-CSF]) when stimulated by
bacterial lipopolysaccharide (41)
• Inability to express inducible nitric acid synthase or produce nitric oxide upon exposure to
pathogenic bacteria, largely reversed by stimulation with proinflammatory cytokines such
as GM-CSF and interferon-γ (42)
Fig. 2. Habitual marijuana smoking is associated with abnormal expression of epidermal
growth factor receptor (EGFR), a growth factor receptor that promotes autonomous
cell growth. Airway mucosal biopsies were obtained from a cohort of nonsmokers and
smokers of marijuana alone, tobacco alone, or both marijuana and tobacco, and
evaluated for EGFR expression by immunohistology. Compared to the limited basal
staining present in normal epithelium (left panel), biopsies demonstrated diffuse and
dark staining of epithelial cells in 58% of marijuana smokers (right panel) and in 89%
of those who smoked both marijuana and tobacco (not shown).
260 Tashkin and Roth
The function of AM recovered from a subset of MS, TS, MTS, and NS was
systematically evaluated ex vivo with respect to their phagocytic and killing activity
for fungi and bacteria, their production of reactive oxygen and nitrogen intermediates
during incubation with fungal or bacterial microorganisms, their ability to produce
pro-inflammatory cytokines when stimulated, and their cytotoxic activity against tumor
cell targets. Briefly, findings from these studies showed the following: (1) an
impairment in fungicidal activity against Candida albicans and Candida tropicalis
when AM from both MS and TS were compared to AM collected from control NS
(40,41); (2) impairment in phagocytosis and killing of the pathogenic bacterium, Staphylococcus
aureus, by AM from MS but not TS (41); (3) a reduction in basal superoxide
production by AM from MS (in contrast to an increase in basal superoxide
generation by AM from TS) and an apparent attenuation by AM from marijuana smokers
of the stimulated production of superoxide by AM from concomitant smokers of both
tobacco and marijuana (40); (4) an impairment in the generation of nitric oxide by AM
from MS (but not TS) that parallels their impairment in bactericidal activity (42); (5)
a reduction in production of pro-inflammatory cytokines, tumor necrosis factor (TNF)-
α and granulocyte macrophage–colony-stimulating factor (GM-CSF), by AM from
MS when stimulated with bacterial lipopolysaccharide (41); and (6) an impairment in
tumoricidal activity by AM from MS (41). A more detailed description of the effects
of marijuana and THC on the function of AM and other immune cells and the likely
clinical consequences of these immunological effects is provided below.
Fig. 3. The number of alveolar macrophages (AM) increases in response to smoking.
Bronchoalveolar lavage was used to recover AM from the lungs of nonsmokers (NS)
and smokers of marijuana alone (MS), tobacco alone (TS), or both marijuana and
tobacco (MTS). The number of AM recovered from MS was approximately twice that
from NS, while the yield of AM from TS and MTS was three and four times that of NS,
respectively, indicating an additive effect of the two substances on the recruitment
and/or replication of macrophages in the lung.
Effects of Marijuana on Immune Defenses 261
4. POTENTIAL EFFECTS OF MARIJUANA ON RESPIRATORY CARCINOGENESIS
Several lines of evidence suggest that marijuana smoking may be a risk factor
for the development of respiratory cancer (Table 3). First, the tar phase of marijuana
smoke contains more of some pro-carcinogenic polycyclic aromatic hydrocarbons,
including benz[α]pyrene, than the tar collected from tobacco cigarettes (3,4,7). Second,
because of the manner in which marijuana cigarettes are smoked, approximately
fourfold more of the particulate phase of the smoke (tar) is deposited in the human
respiratory tract than occurs during tobacco smoking (6). This enhanced lung deposition
during marijuana smoking, combined with the high concentration of known carcinogens
in marijuana smoke, significantly magnifies the level of exposure to
carcinogens from each marijuana cigarette. Third, THC can interact with the aryl
hydrocarbon receptor and, independent of other components in the smoke, activate
transcription of cytochrome P4501A1 (7). Cytochrome P4501A1 is involved in the
biotransformation of polycyclic aromatic hydrocarbons into active carcinogens and
plays a central role in the development of lung cancer. Fourth, hamster lung explants
exposed to marijuana smoke for up to 2 years exhibited abnormalities in cell growth
and accelerated malignant transformation (43). Fifth, bronchial biopsies from habitual
marijuana smokers overexpressed surrogate endpoint markers of pretumor progression,
as already described (36). Sixth, non-small-cell lung cancer cell lines implanted
into immunocompetent mice displayed accelerated growth when the animals were
Table 3
Evidence Supporting Carcinogenic Effects of Marijuana
• Increased concentrations of pro-carcinogenic polycyclic aromatic hydrocarbons (PAHs),
including benzo-[α]-pyrene, in the tar phase of marijuana smoke compared to tobacco
smoke (3,4,7)
• Fourfold increase in lung deposition of tar from marijuana smoke as compared to tobacco
smoke mainly as a result of the differences in cigarette filtration and smoking technique (6)
• Activation of the cytochrome P4501A1 gene by THC, potentially enhancing the transformation
of PAHs into active carcinogens (7)
• Accelerated malignant transformation in hamster lung explants exposed to marijuana
smoke for up to 2 years (43)
• Premalignant histopathological alterations in bronchial biopsies from smokers of marijuana
only, including metaplastic and dysplastic changes in the bronchial epithelium (35)
• Overexpression of cell proteins associated with malignant transformation in the bronchial
epithelium of habitual smokers of marijuana (36)
• Systemic administration of Δ9-tetrahydrocannabinol accelerates the growth of non-smallcell
lung cancer cells implanted into immunocompetent mice (44)
• Case series reporting a disproportionately high percentage of chronic marijuana smokers
in young patients (<45 n =" 65,000)" n =" 173" n =" 611)" n =" 601)," t =" 35" t =" 190" t =" 35" t =" 190" t =" 35" t =" 190" n =" 212)a">9.0
THC 32% 55% 9% 2% 2% 0.5%
THC-COOH 26% 42% 18% 8% 2% 4%
THC, Δ9-tetrahydrocannabinol; THC-COOH, 11-carboxy-THC.
aThe corresponding whole blood concentrations would be approximately
half the reported serum amount.
From ref. 13.
286 Logan
2.1.1.4. SUMMARY
Blood concentrations of both THC and THC-COOH drop precipitously in the
first few hours following smoking, because these substances partition into fatty compartments.
It is recommended that blood or plasma concentrations of THC and THCCOOH
be interpreted with caution. Under most circumstances, detection of parent
THC will reflect recent use, meaning within the last few hours, making the likelihood
of impairment within that time frame that much greater. More distant, higher-intensity
marijuana use cannot be ruled out, however, when THC is detected, and under that
pattern of use impairment may persist longer than the 2–3 hours typical of the low- to
moderate-dose administration. Detection of THC-COOH in the absence of the parent
drug (i.e., <2>2 hours). It should go without
saying that the screening threshold and confirmatory test sensitivity of the analytical
laboratory must be taken into consideration when evaluating these results.
3. EPIDEMIOLOGY OF MARIJUANA AND DRIVING
A thorough review of epidemiological studies related to marijuana in various
driving populations was done recently by Huestis (14), and we will not attempt to replicate
that in this chapter. The focus of this discussion is on studies that have attempted to
relate marijuana use to risk of accident involvement or accident culpability.
A survey of many of the studies cited by Huestis shows various rates of marijuana
positivity in impaired drivers, fatally injured drivers, drivers injured in motor
vehicle accidents, and commercial vehicle operators. The rates of positivity vary
depending on whether blood or urine was tested, whether the parent or metabolite was
tested for, whether the samples were provided voluntarily or following arrest, the sensitivity
of the testing method, and whether the study group was selected out (e.g., only
subjects without alcohol tested). In spite of these variables, in the fatally injured driving
population overall, 10–20% of drivers test positive for cannabinoids, whereas in
the arrest population rates are between 15 and 60%, suggesting a significant role for
marijuana use.
None of these studies has control data, however, that would show the rate of
marijuana use in the local driving population not killed or injured in a collision, such
that a comparative rate or odds ratio for fatal accident involvement could be calculated.
Another limiting factor was that in some studies urine was tested, and, as noted
above, urine can test positive for marijuana use for a few days following use, while the
impairing effects last only for a few hours.
These studies do uniformly find evidence, however, that there is widespread use
of marijuana in all these driving populations. In nonselected populations (e.g., all fatally
injured drivers, trauma patients), the incidence of cannabinoid positives was typically
between 5 and 20%, and in selected populations (e.g., young males, fatally injured
drivers) the rate was as high as between 15 and 60%.
A recent voluntary test of commercial vehicle operators in Washington and Oregon
(15) showed a marijuana-positive rate of 5%, in spite of a 19% refusal rate in what is
a heavily regulated industry with mandatory random testing. A similar survey done in
1988 showed 15% of tractor trailer drivers positive for cannabinoids, suggesting some
improvement following the introduction of testing (16).
Marijuana and Driving Impairment 287
3.1. Assessment of Relative Crash Risk Following Marijuana Use
Studies that have assessed crash responsibility offer more insight into the quantitative
relationship between marijuana usage and crash involvement. An excellent
review of culpability studies has recently been published (17). The general design of
these studies is to compare rates of drug use in at-fault drivers vs no-fault drivers and
compute the ratio, with values greater than 1.0 indicating increased rates of risk. The
95% confidence interval is also computed, and when the range includes 1.0, the difference
in responsibility rates is not significant at the p = 0.05 level.
In most of these studies, authors validate their data set and methodology by
assessing odds ratios for alcohol. The relationship between alcohol and risk of crash
involvement has been well established, most famously in the 1960 Grand Rapids Study.
In each case the method showed the expected significant relationship at the p = 0.05
(95% confidence interval) level between alcohol positivity and greater odds of crash
involvement.
The data from studies that made odds ratio assessments based on the presence of
the inactive THC-COOH metabolite uniformly failed to show significant differences
at the p = 0.05 level in rates of accident involvement for the drug-positive drivers.
This can be rationalized in terms of the fact that the metabolite is inactive and that in
most cases urine was being tested. Bearing this in mind, together with the fact that
urine can test positive for the metabolite for many hours or even days after the effect
has passed, its detection in urine is not a good surrogate for impairment, and the negative
findings are not surprising.
Studies assessing crash risk based on parent THC in blood are more informative.
One study of 2500 injured drivers (18,19) showed a trend towards increasing odds
ratio with increasing THC concentration (although not significant at p = 0.05) and
found that culpable drivers had a higher mean THC concentration (p = 0.057). This
suggests a dose-dependent increase in risk, with the threshold for significance being
somewhere above 2 ng/mL THC. One limitation of the Hunter study is the lack of
control of the interval between driving and when the sample was collected. Intervals
of an hour or less between the driving and the time the sample was collected would
cause appreciable decreases in THC concentration.
In a cohort of 3398 fatally injured drivers (20), the authors avoid this limitation
because absorption of THC will stop at the time of death. Those data showed an odds
ratio of 2.7 in cases in which THC was detected and 6.6 when the THC concentration
was greater than 5 ng/mL.
Several studies have evaluated crash risk in drivers positive for both alcohol and
marijuana (THC or THC-COOH). Table 4 shows that irrespective of whether the parent
drug or metabolite was measured, when combined with alcohol the odds ratio for
crash involvement was between 3.5 and 11.5 (significant in all cases, p = 0.05) and
compared to alcohol positive cases was still significant, with an odds ratio of 2.9.
Taken together, these data represent strong evidence for a concentration-dependent
(and consequently dose-dependent) relationship between THC and risk of
crash involvement and enhanced risk for any use of marijuana when combined
with alcohol.
288 Logan
4. MARIJUANA AND ON-ROAD DRIVING STUDIES
The above considerations suggest that in addition to the empirical intoxicating
properties of marijuana, there is epidemiological and behavioral evidence that it can
cause impairment in the first few hours following use. Assessments of psychomotor
performance following marijuana use have been performed, and these have been
reviewed recently by Ramaekers et al. (17). These studies support the idea that dosedependent
impairments in psychomotor performance and cognition appear immediately
following marijuana administration, peak after the blood concentration peaks,
and persist for 3–4 hours. Although there is a relationship between many of these
tasks and the driving task, the clearest means of assessing the actual effects of mari-
Table 4
Summary of Odds Ratio of Becoming Involved in Fatal or Injurious Traffic
Accidents Under the Influence of Cannabis, Alcohol, or Their Combination as
Reported in Culpability Studies
Substance Authors Odds ratio 95% CI
Drug-free cases 1.0
Alcohol Terhune and Fell (21) 5.4* 2.8–10.5
Williams et al. (22) 5.0* 2.1–12.2
Terhune et al. (23) 5.7* 5.1–10.7
Drummer (24) 5.5* 3.2–9.6
Hunter et al. (18) 6.8* 4.3–11.1
Lowenstein and Koziol-Mclain (25) 3.2* 1.1–9.4
Drummer et al. (20) 6.0* 4.0–9.1
THC-COOH Terhune and Fell (21) 2.1 0.7–6.6
Williams et al. (22) 0.2 0.2–1.5
Terhune et al. (23) 0.7 0.2–0.8
Drummer (24) 0.7 0.4–1.5
Hunter et al. (18) 0.9 0.6–1.4
Lowenstein and Koziol-Mclain (25) 1.1 0.5–2.4
TCH (range: ng/mL)
<1.0>2.0 1.74 0.6–5.7
1–100 Drummer et al. (26) 2.7* 1.02–7.0
5–100 6.6* 1.5–28.0
Alcohol/THC or Williams et al. (22) 8.6* 3.1–26.9
THC-COOH Terhune et al. (23) 8.4* 2.1–72.1
Drummer (24) 5.3* 1.9–20.3
Hunter et al. (18) 11.5* 4.6–36.7
Lowenstein and Koziol-Mclain (25) 3.5* 1.2–11.4
Significant changes in OR indicated as follows: *<0.05.>90%) THC is distributed to the plasma, with 10% in red blood cells (7).
Almost all of the THC in plasma is protein bound, mainly to lipoproteins, but also to
albumin (8). These physical properties must be considered when making postmortem
measurements; postmortem measurements are conducted on whole blood, but the pharmacokinetic
data sometimes used to interpret these concentrations are based on measurements
made using plasma obtained from the living.
THC is extremely lipophilic, but, because of strong protein binding, it has a relatively
small apparent plasma volume of 2–4 L, at least initially (9). The steady-state
volume of distribution is much higher (10 L/kg; ref. 10). Plasma THC levels decline
very rapidly because tissue uptake is so rapid. Only small amounts (probably <1%)
reside in the brain during periods of peak psychoactivity (11). This seemingly paradoxical
finding is explained by the brain’s very high blood flow and the ease with
which THC enters and departs cells (12). With repeated use, THC accumulates in less
Fig. 1. Current breakdown of illicit drug use in the United States.
Postmortem Considerations 297
vascular tissue, especially body fat (13). This property makes fat a useful alternative
matrix for testing (14).
Maximum plasma concentrations occur within minutes of smoking, and psychological
effects become apparent within a few seconds to a few minutes. Maximum
psychological effects are observed after 15–30 minutes, and these taper off within 2–
3 hours. When taken orally there is a delay of 30–90 minutes before the onset of
psychotropic effects, and these effects remain relatively constant for 2–3 hours. The
psychological effects then dissipate slowly over the following 4–12 hours (15).
3. CARDIOVASCULAR EFFECTS
THC, the major psychoactive component of Cannabis sativa, like anandamide, the
endogenous cannabinoid ligand, activates G protein-coupled receptors in the heart, brain,
and periphery. Two distinct types of cannabinoid receptors have been identified: CB1
and CB2. Activation of peripheral CB1 receptors elicits profound coronary and cerebral
vasodilatation (16). In vitro studies have shown that this response is a result of direct
receptor activation and that the process occurs independently of the sympathetic nervous
system (17). In animal models, the predictable result is hypotension.
In humans the vascular response is a largely dose-dependent increase in heart
rate, usually accompanied by a mild increase in systolic pressure, although orthostatic
hypotension is a recognized complication in occasional users. Studies with human
volunteers have shown that complete tolerance to the tachycardiac and blood pressure
effects develops and that electrocardiographic alterations produced by marijuana smoking
are minimal (18).
Whether or not these recognized cardiovascular effects are sufficient to actually
trigger myocardial infarction is still debated, although there is ample evidence for
concern. The acute onset of coronary syndromes is thought to result from the disruption
of vulnerable plaque. Vulnerable plaques are not necessarily the largest plaques
(i.e., they do not cause clinically significant obstruction of large epicardial arteries)
but, rather, are comprised of thin-capped, lipid-rich lesions that may be located in
second-order vessels. “Triggers,” whether intense athletic activity, marijuana smoking,
or even intense sexual activity, result in homodynamic forces that can disrupt the
thin fibrous cap, probably because changes in arterial pressure disrupt the underlying
vulnerable plaque (19).
Epidemiological evidence supports the triggering theory. Investigators in the
Myocardial Infarction Onset Study interviewed 3882 patients (1258 women) hospitalized
with acute myocardial infarction (20). Of these, 124 (3.2%) reported smoking
marijuana in the prior year, 37 within 24 hours and 9 within 1 hour of the onset of
symptoms. As is true for most patients with coronary artery disease, marijuana users
were more likely to be men (94 vs 67%, p < 0.001), more likely to be current cigarette
smokers (68 vs 32%, p < 0.001), and more likely to be obese (43 vs 32%, p = 0.008).
The risk of myocardial infarction onset in the marijuana smokers was elevated 4.8
times over baseline (95% confidence interval 2.4–9.5) in the 60 minutes after marijuana
use, dropping to a relative risk of 1.7 in the second hour, after which no increase
risk was apparent.
298 Karch
The authors of the study concluded that smoking marijuana was a rare trigger of
acute myocardial infarction. A number of other “triggers” for myocardial infarction
have been identified (21,22). These include heavy physical exertion, mental stress,
particulate air pollution, and sexual activity. The increased relative risk associated
with sexual activity is comparable to that associated with marijuana smoking—roughly
double the relative risk of acute myocardial infarction in healthy individuals or even
in patients with a prior history of angina or those with prior infarction.
Although the relative risk for infarction is definitely increased, the absolute risk
of marijuana-triggered infarction is extremely low because the baseline risk of infarction
is low for most individuals. The increased risk is transient, probably because
marijuana-induced changes in pulse and blood pressure changes are transient, if they
occur at all. Tolerance to vascular effects rapidly emerges in chronic marijuana smokers.
These factors must be given due weight in any cause of death determination.
4. OTHER MEDICAL EFFECTS
Chronic marijuana smoking is clearly related to lung injury, although there is
nothing diagnostic about the resultant pattern of injury (23). Because of the way marijuana
is smoked, more particulate matter is generated than by smoking tobacco, which
means that damage to the respiratory tract is more likely than with tobacco smoking.
The effects of cannabis and tobacco smoking are additive and independent. The resultant
histopathological effects include changes consistent with acute and chronic bronchitis
but are in no way diagnostic. In the only published autopsy series, lungs were examined
in 13 known marijuana smokers with sudden death. Decedents ranged in age
from 15 to 40 years. There were accumulations of pigmented monocytes within
the alveoli and variable, spotty, infiltrates of monocytes and lymphocytes within the
intersititum. The study authors suggest that the degree of infiltrate was dose-related,
with heavier smokers having heavier infiltrates (24).
Alveolar macrophages recovered from the lungs of marijuana smokers have a
decreased ability to release pro-inflammatory cytokines and nitric oxide and are less
effective at killing bacteria. THC alters human immune responses. Lymphocytes of
marijuana smokers contain increased amounts of messenger RNA encoding for both
type 1 and 2 cannabinoid receptors. THC suppresses T-cell proliferation, inhibits the
release of interferon-γ, and alters the production of T-helper cytokines (25). Habitual
exposure to THC impacts human cell-mediated immunity and host defenses, but there
is little evidence to support the notion that, like tobacco smoking, cannabis exposure
actually causes malignancy. In fact, there is equally good evidence that, as a group,
cannabinoids induce tumor regression in rodents. The mechanism of cannabinoid antitumoral
action in vivo is as yet unknown, but it may involve the direct inhibition of
vascular endothelial cell migration and survival as well as decreased expression of
pro-angiogenic factors (vascular endothelial growth factor and angiopoietin-2) and
matrix metalloproteinase-2 found within tumors.
5. POSTMORTEM MEASUREMENTS
Forensic pathologists occasionally screen for THC and its metabolites, but only
if impairment is an issue or, in the rare episode of atherosclerotic sudden cardiac death,
Postmortem Considerations 299
where “trigger” factors are being sought. Routine screening for cannabanoids is, however,
not considered cost-effective (an important issue for medical examiner’s offices).
When nonspecific populations have been screened, results have generally mirrored
patterns of drug abuse within the rest of the population. Of 500 sequential specimens
screened by the Medical Examiner’s Office in Maryland, 63 (13%) were initially positive
by enzyme multiplied immunoassay technique, and 58 of those (12%) were confirmed
positive (26).
6. CAUSE-OF-DEATH DETERMINATION
There are no unique or diagnostic lesions associated with acute THC toxicity. It
is not even clear what the clinical signs of massive overdose would be. Pathological
abnormalities identified in chronic users are likely to be a consequence of chronic
polydrug abuse and are nonspecific. The question to be answered by forensic pathologists
is whether marijuana use has “triggered” an episode of myocardial infarction or
sudden cardiac death, but answers are unlikely to be forthcoming. “Trigger” theories
can only be applied in situations in which coronary artery disease is already established,
which almost surely means that the decedent will be in an older age group, the
very group most likely to experience myocardial infarction in the first place.
Blood and tissue measurements of THC are of little or no diagnostic value in
cause-of-death determination and are seldom measured. Even when postmortem blood
concentrations are measured, a number of toxicological issues make interpretation of
these measurements difficult. Perhaps the greatest impediment to interpretation is that
all published studies (and formulas for predicting time of use) are based on measurement
made in plasma (27,28). Even in the living, relating measurement made in whole
blood to measurements made in plasma is problematic. When THC, 11-OH-THC, and
THC-COOH concentrations were measured in the plasma and whole blood taken from
eight chronic marijuana smokers, the values of the plasma-to-whole blood distribution
ratios were very similar, and the individual coefficient of variation was relatively
low. These results suggest that plasma levels could be calculated from whole blood
concentrations by taking into account a multiplying factor of 1.6. Unfortunately, similar
attempts with postmortem “blood” resulted in a distribution of cannabinoids between
whole blood and “serum” that was scattered over too wide a range to be of any
forensic value; the Huestis models could not be applied (29).
Tolerance to the vascular—and many of the psychological—effects of marijuana
smoking rapidly emerges, and even in the living, plasma concentrations do not predict
pulse or blood pressure (18). Slow diffusion of THC from plasma into body fat and
reentry into the blood is a constant ongoing process. Within 6–8 hours after use, plasma
THC concentrations drop below 2 μg/L, and then continue to decrease somewhat more
slowly. After smoking cigarettes containing 16 mg (low dose), levels fall below 0.5 μg/L
(the limit of detection for most laboratories) after 7.2 hours (27,28). When the dose is
doubled, plasma concentration remained above 0.5 for an average of 12.5 hours, and
THC-COOH remained detectable for an average of 3.5 days.
With higher doses and long-term use, substantial amounts of THC and its
metabolites accumulate in deep body stores (30). After death these stores are slowly
released. Although there exist a host of reliable methods for THC extraction (31) and
300 Karch
quantitation (32), THC’s large volume of distribution virtually guarantees that postmortem
redistribution will occur, which means that postmortem THC concentration
measurements are of even less use than antemortem measurements, which is to say
not at all.
REFERENCES
1. Compton, W. M., Grant, B. F., Collier, J. D., Glantz, M. D., and Stinson, F. S. (2004)
Prevalence of marijuana use disorders in the United States: 1991-1992 and 2001-2002.
JAMA 291, 2114–2121.
2. Substance Abuse and Mental Health Service Administration. (2003) Results: 2002 National
Survey on Drug Use & Health (NSDUH), in NHSDA Series H-22, DHHS Publication
NO SMA 03-3836, O.o.A. Studies, Rockville, MD.
3. American Heart (2004) American Heart Association’s Heart Disease and Stroke Statistics—
2004 Update, in Stats2004, NRO3, Dallas.
4. Garrett, E. R. and Hunt, C. A. (1974) Physiochemical properties, solubility, and protein
binding of delta9-tetrahydrocannabinol. J. Pharm. Sci. 63, 1056–1064.
5. Agurell, S. and Leander, K. (1971) Metabolism of cannabis. VIII. Stability, transfer and
absorption of cannabinoid constituents of cannabis (hashish) during smoking. Acta Pharm.
Suec. 8, 391-402.
6. Thompson, G. R., Rosenkrantz, H., Schaeppi, U. H., and Braude, M. C. (1973) Comparison
of acute oral toxicity of cannabinoids in rats, dogs and monkeys. Toxicol. Appl.
Pharmacol. 25, 363–372.
7. Widman, M., Agurell, S., Ehrnebo, M., and Jones, G. (1974) Binding of (+)- and (minus)-
delta-1-tetrahydrocannabinols and (minus)-7-hydroxy-delta-1-tetrahydrocannabinol to
blood cells and plasma proteins in man. J. Pharm. Pharmacol. 26, 914–916.
8. Wahlqvist, M., Nilsson, I. M., Sandberg, F., and Agurell, S. (1970) Binding of delta-1-
tetrahydrocannabinol to human plasma proteins. Biochem. Pharmacol. 19, 2579–2584.
9. Wall, M. E., Sadler, B. M., Brine, D., Taylor, H., and Perez-Reyes, M. (1983) Metabolism,
disposition, and kinetics of delta-9-tetrahydrocannabinol in men and women. Clin.
Pharmacol. Ther. 34, 352–363.
10. Lemberger, L., Tamarkin, N. R., Axelrod, J., and Kopin, I. J. (1971) Delta-9-tetrahydrocannabinol:
metabolism and disposition in long-term marihuana smokers. Science 173,
72–74.
11. Gill, E. W. and Jones, G. (1972) Brain levels of delta1-tetrahydrocannabinol and its metabolites
in mice—correlation with behaviour, and the effect of the metabolic inhibitors
SKF 525A and piperonyl butoxide. Biochem. Pharmacol. 21, 2237–2248.
12. Chiang, C. N. and Rapaka, R. S. (1987) Pharmacokinetics and disposition of cannabinoids.
NIDA Res. Monogr. 79, 173–188.
13. Kreuz, D. S. and Axelrod, J. (1973) Delta-9-tetrahydrocannabinol: localization in body fat.
Science 179, 391–393.
14. Levisky, J. A., Bowerman, D. L., Jenkins, W. W., Johnson, D.G., and Karch, S. B. (2001)
Drugs in postmortem adipose tissues: evidence of antemortem deposition. Forensic Sci.
Int. 121, 157–160.
15. Grotenhermen, F. (2003) Pharmacokinetics and pharmacodynamics of cannabinoids. Clin.
Pharmacokinet. 42, 327–360.
16. Wagner, J. A., Jarai, Z., Batkai, S., and Kunos, G. (2001) Hemodynamic effects of cannabinoids:
coronary and cerebral vasodilation mediated by cannabinoid CB1 receptors. Eur. J.
Pharmacol. 423, 203–210.
17. Sidney, S. (2002) Cardiovascular consequences of marijuana use. J. Clin. Pharmacol.
42(11 Suppl.), 64S–70S.
Postmortem Considerations 301
18. Benowitz, N. L. and Jones, R. T. (1975) Cardiovascular effects of prolonged delta-9-tetrahydrocannabinol
ingestion. Clin. Pharmacol. Ther. 18, 287–297.
19. Servoss, S. J., Januzzi, J. L., and Muller, J. E. (2002) Triggers of acute coronary syndromes.
Prog. Cardiovasc. Dis. 44, 369–380.
20. Mittleman, M. A., Lewis, R. A., Maclure, M., Sherwood, J. B., and Muller, J. E. (2001)
Triggering myocardial infarction by marijuana. Circulation 103, 2805–2809.
21. Mittleman, M. A., Maclure, M., Nachnani, M., Sherwood, J. B., and Muller, J.E. (1997)
Educational attainment, anger, and the risk of triggering myocardial infarction onset. The
Determinants of Myocardial Infarction Onset Study Investigators. Arch. Intern. Med. 157,
769–775.
22. Mittleman, M. A. and Siscovick, D. S. (1996) Physical exertion as a trigger of myocardial
infarction and sudden cardiac death. Cardiol. Clin. 14, 263–270.
23. Barsky, S. H., Roth, M. D., Kleerup, E. C., Simmons, M., and Tashkin, D P. (1998) Histopathologic
and molecular alterations in bronchial epithelium in habitual smokers of marijuana,
cocaine, and/or tobacco. J. Natl. Cancer Inst. 90, 1198–1205.
24. Morris, R. R. (1985) Human pulmonary histopathological changes from marijuana smoking.
J. Forensic Sci. 30, 345–349.
25. Roth, M. D., Baldwin, G. C., and Tashkin, D. P. (2002) Effects of delta-9-tetrahydrocannabinol
on human immune function and host defense. Chem. Phys. Lipids 121, 229–239.
26. Isenschmid, D. S. and Caplan, Y. H. (1988) Incidence of cannabinoids in medical examiner
urine specimens. J. Forensic Sci. 33, 1421–1431.
27. Huestis, M. A., Henningfield, J. E., and Cone, E. J. (1992) Blood cannabinoids. II. Models
for the prediction of time of marijuana exposure from plasma concentrations of delta 9-
tetrahydrocannabinol (THC) and 11-nor-9-carboxy-delta9-tetrahydrocannabinol
(THCCOOH). J. Anal. Toxicol. 16, 283–290.
28. Huestis, M. A., Henningfield, J. E., and Cone, E. J. (1992) Blood cannabinoids. I. Absorption
of THC and formation of 11-OH-THC and THCCOOH during and after smoking marijuana.
J. Anal. Toxicol. 16, 276–282.
29. Giroud, C., Menetrey, A., Augsburger, M., Buclin, T., Sanchez-Mazas, P., and Mangin, P.
(2001) Delta(9)-THC, 11-OH-delta(9)-THC and delta(9)-THCCOOH plasma or serum to
whole blood concentrations distribution ratios in blood samples taken from living and dead
people. Forensic Sci. Int. 123, 159–164.
30. Leuschner, J. T., Harvey, D. J., Bullingham, R. E. S., and Paton, W. D. M. (1986) Pharmacokinetics
of delta 9-tetrahydrocannabinol in rabbits following single or multiple intravenous
doses. Drug Metab. Dispos. 14, 230–238.
31. Nyoni, E. C., Sitaram, B. R., and Taylor, D. A. (1996) Determination of delta 9-tetrahydrocannabinol
levels in brain tissue using high-performance liquid chromatography with electrochemical
detection. J. Chromatogr. B Biomed. Appl. 679, 79–84.
32. Moffat, A., Osselton, D., and Widdop, B. (eds.) (2004) Clarke’s Analysis of Drugs and
Poisons in Pharmaceuticals, Body Fluids and Postmortem Material, 3rd ed., Vol. 2, Pharmaceutical
Press, London, pp. 740–743.
302 Karch
Cannabinoid Effects on Mental Processes 303
From: Forensic Science and Medicine: Marijuana and the Cannabinoids
Edited by: M. A. ElSohly © Humana Press Inc., Totowa, New Jersey
303
Chapter 14
Cannabinoid Effects
on Biopsychological, Neuropsychiatric,
and Neurological Processes
Richard E. Musty
1. INTRODUCTION
There have been several reviews of the therapeutic potential of both natural and
synthetic cannabinoids (1,2). These reviews strongly suggest potential therapeutic
effects of cannabinoids in motivational processes and their associated disorders (hunger,
appetite, pain), psychological disorders (anxiety, depression, bipolar disorder,
schizophrenia, alcohol dependence), and central nervous system (CNS) disorders (vomiting
and nausea, spasticity, dystonia, brain damage, epilepsy). This chapter, for the
most part, covers developments since these reviews were published.
2. HUNGER AND APPETITE
Cannabis was reported to be an appetite stimulant as early as 1845 by Donovan
(3), suggesting that it might be used for anorexia nervosa. Although it is common
knowledge that cannabis stimulates hunger, very little research has been accomplished
over subsequent years.Van Den Broek et al. (4) administered 9-aza-cannabinol to sheep
intravenously and found that feeding behavior was increased along with a decrease in
gastric secretion.
Foltin et al. (5) tested nine normal subjects in a live-in laboratory setting. He
found that administration of two or three active marijuana cigarettes (1.84%) during a
time when subjects could smoke in a social setting increased caloric intake as a result
of between-meal snack food, but not during regular meals. These data seem to be the
304 Musty
most objective test of the appetite/hunger-stimulating effects of cannabinoid agonists
(see also ref. 6).
Beal et al. (7) examined the effects of dronabinol on 94 late-stage AIDS patients
who received dronabinol orally 2.5 mg twice daily (90%) or 2.5 mg once daily (10%)
for 12 months. Appetite was measured using a visual analog scale for hunger. They
found an increase in appetite of 48.6–76.1%, which peaked at 4 months, after which
dronabinol induced appetite increases of at least double that at baseline and stable
weight for the remaining months. These data seem to suggest that dronabinol stimulates
appetite and leads to maintained weight in advanced AIDS patients. Further research
in this area is certainly needed, especially in patients earlier in the progression
of the disease.
2.1. Appetite Supression
Sanofi-Aventis (8) reported the following concerning the effects of the cannabinoid
type 1 (CB1) receptor antagonist SR141716, now known as rimonabant (also
Acomplia™).
The results of a 2-year phase III study in 3040 patients with rimonabant
(Acomplia), the first in a new class of therapeutic agents called selective CB1 blockers,
demonstrate that the benefits achieved with rimonabant 20 mg at the end of the first
year of the study were sustained in the second year of therapy with a good safety and
tolerability profile vs placebo. Patients treated with rimonabant 20 mg for 2 years
experienced a reduction in body weight and in waist circumference, demonstrating a
significant reduction in abdominal fat, a key marker for cardiovascular disease.
Patients treated with rimonabant 20 mg over the 2-year period also achieved a
significant increase in high-density lipoprotein (HDL) cholesterol (good cholesterol),
a reduction in triglycerides, and an improvement in insulin sensitivity. The RIO–
North America study is the largest of all rimonabant studies presented to date. The
results from this study are consistent with the findings from two previous large-scale
studies on rimonabant–RIO-Lipids and RIO-Europe–communicated earlier this year
and add to the ever-growing body of evidence supporting the drug’s efficacy and tolerability
profile. Rimonabant is currently being developed for the management of cardiovascular
risk factors, including reduction of abdominal obesity, improving lipid
and glucose metabolism, and as an aid to smoking cessation.
Obesity is a major public health burden and one of the most frequent causes of
death worldwide, mainly through cardiovascular disease. Obesity is typically measured
by body mass index. However, recent findings have shown that visceral
(abdominal) fat (simply measured by waist circumference) is a better predictor for
heart attack than weight or body mass index. Forty-four percent of adult Americans
have a waist circumference size exceeding the at-risk level (40 in. for men and 35 in.
for women). Visceral fat is associated with the cause of metabolic risk factors such as
dyslipidemia or insulin resistance that may lead to diabetes, heart attack, stroke, and
other cardiovascular disease. Reducing abdominal fat is a recognized priority for preventing
cardiovascular disease.
RIO–North America was a phase III, multinational multicenter, randomized,
double-blind, placebo-controlled trial comparing two fixed-dose regimens of
rimonabant (5 and 20 mg once daily) to placebo for a period of 2 years. The study was
conducted in 3040 patients at 72 centers in the United States and Canada.
Cannabinoid Effects on Mental Processes 305
The objectives of the trial were to assess the effect of rimonabant on weight loss
over a period of 1 year and to determine the ability of rimonabant to prevent weight
regain during a second year of treatment. The study objectives also included an
assessment of improvement in risk factors associated with abdominal obesity (as measured
by waist circumference), such as dyslipidemia, glucose metabolism, and the
metabolic syndrome, and an evaluation of the safety and tolerability of rimonabant
over a period of 2 years.
After a screening period of 1 week, patients were prescribed a mild hypocaloric
diet (designed to reduce daily caloric intake by 600 kcal from the patient’s energy
requirements) and entered a 4-week single-blind placebo run-in period. Afterward,
patients were randomly allocated to one of the three treatment groups: placebo or
rimonabant 5 or 20 mg for 52 weeks of double-blind treatment using a randomization
ratio of 1:2:2.
After the first year of treatment, patients who received rimonabant 5 or 20 mg
were rerandomized to either the same dose of rimonabant or placebo using a randomization
ratio of 1:1 for an additional 52-week treatment period (the placebo group
remained on placebo during the second year).
2.2. Rio–North America Findings
The findings show that 2-year treatment with rimonabant 20 mg significantly
lowered weight, reduced abdominal fat, diminished cardiovascular risk factors, and
decreased metabolic disorders in this patient population. Waist circumference, a simple
measure of abdominal fat, in patients treated with rimonabant 20 mg for the full 2-
year period was reduced by 8 cm (3.1 in.) vs 4.9 cm (1.9 in.) for rimonabant 5 mg and
3.8 cm (1.5 in.) in the placebo group (p < 0.001). Of the patients who received treatment
with rimonabant 20 mg throughout the 2-year period, 62.5% lost more than 5%
of their initial body weight vs 36.7% of those on rimonabant 5 mg and 33.2% of those
on placebo (p < 0.001). In the same period, 32.8% of patients treated with rimonabant
20 mg lost in excess of 10% of their initial body weight vs 20% of those on rimonabant
5 mg and 16.4% of patients on placebo (p < 0.001).
Metabolic parameters were also significantly improved in patients treated with
rimonabant 20 mg throughout the 2-year period, with HDL cholesterol increased by
24.5% in the rimonabant 20 mg group vs 15.6 and 13.8% in the rimonabant 5 mg and
placebo groups, respectively (p < 0.001). Triglycerides were reduced by 9.9% in patients
treated with rimonabant 20 mg throughout the 2-year period vs 5.9 and 1.6% in the
rimonabant 5 mg and placebo groups, respectively (p < 0.05).
Although diabetic patients were not included in the study, patients on rimonabant
20 mg had significantly improved their insulin sensitivity compared to those on
rimonabant 5 mg and on placebo. The effect of rimonabant on HDL cholesterol, triglycerides,
fasting insulin, and insulin sensitivity (as measured by homeostasis model
assessment) appeared to be twice that which would be expected from the degree of
weight loss achieved (all p < 0.05). Of particular note is that the number of patients
diagnosed with metabolic syndrome at baseline and treated with rimonabant 20 mg
over the 2-year study period was reduced by more than one third (p < 0.001). Metabolic
syndrome encompasses a series of serious health risks or conditions that increase
a person’s chance to develop heart disease, stroke, and diabetes.
306 Musty
2.3. A Good Safety and Tolerability Profile
Rimonabant 20 mg proved to be safe and tolerable vs placebo throughout the 2-
year study period. Side effects were mainly minor and short-lived. Overall discontinuation
rates for adverse events in the first year of the study were 7.2, 9.4, and 12.8% in
the placebo, rimonabant 5 mg, and rimonabant 20 mg groups, respectively. The discontinuation
rates for patients randomly assigned to continue their first-year treatment
for a second year were 6.7, 8.3, and 6.0% in the placebo, rimonabant 5 mg and 20 mg
groups, respectively. No differences were noted in the three groups with regard to
scores measured by the Hospital Anxiety Depression scale. In this trial and in two
preceding studies, rimonabant was also shown to have no significant electrocardiogram
or heart rate changes.
2.4. Rimonabant and the Endocannabinoid System
The Endocannabinoid (EC) System is a newly discovered physiological system
in the body that is believed to play a key role in the central and peripheral regulation
of energy balance, glucose and lipid metabolism, as well as in the control of tobacco
dependence. CB1 receptors are found in the brain as well as in peripheral tissues of the
body, such as adipocytes (or “fat cells”), which are associated with lipid and glucose
metabolism. Excessive food intake or chronic tobacco use results in an overactive EC
system. This can trigger a cycle of increased eating and fat storage or, in the case of
smoking, sustained tobacco dependence.
Rimonabant is the first in a new class of drugs called CB1 blockers. By selectively
blocking both centrally and peripherally the CB1 receptors, rimonabant modulates
the overactive EC System. The results have been seen in reducing cardiovascular
risk factors through reduction in abdominal fat and a corresponding improvement in
metabolic parameters that is beyond that expected through weight reduction.
The new clinical results from the RIO–North America study further suggest that
rimonabant may become an important tool in the cardiovascular risk factor reduction
armamentarium.
LeFur (6) reviewed a number of findings that support the effects of the mechanisms
by which rimonabant acts:
1. CB1 receptors are located in brain areas associated with hunger and appetite.
2. “Endocannabinoids may tonically activate the CB1 receptors to maintain food intake,
and increase the incentive value of food as well as reinforcing the rewarding effects of
nicotine involving the brain reward circuits...”
3. In mutant obese mice, rimonabant decreased food intake and led to a sustained loss in
body weight.
4. Rimonabant had no effect in CB1 receptor knockout mice, confirming the fact that
CB1 receptors are necessary for the action of this drug.
To conclude, it seems that cannabinoid agonists increase hunger and appetite,
whereas antagonists decrease appetite and hunger. There seems to be significant promise
for both stimulating appetite and decreasing it. If these results continue to show promise,
medications of significant value might be developed.
Cannabinoid Effects on Mental Processes 307
3. PAIN
In a review, Walker et al. (9) concluded that cannabinoids suppress nociceptive
neurotransmission, synthetic agonists are as potent as morphine, there are both direct effects
on spinal cord, the periphery, and the brain.
Bicher and Mechoulam (10) found that Δ9-tetrahydrocnnabinol (THC) and Δ8-
THC (ip) were about half as effective as morphine (sc) on three tests of analgesia: the
hot plate test, the acetic acid writhing test, and the tail flick test. In a review of human
anecdotal studies and controlled studies (11), pain relief has been reported anecdotally
as well as in controlled studies. Of the four double-blind placebo-controlled studies
reviewing THC administration for cancer pain, THC was effective at 15 and 20 mg
in one study and in the second study was more effective than placebo and THC for
postoperative pain: levonatradol was effective at 1.5–3 mg, and THC was not effective
at doses of 0.22 and 0.44 mg/kg (pain after extraction of impacted molar teeth). In
a questionnaire study, Dunn and Davis (12) reported that patients who smoked cannabis
found relief from phantom limb pain. In a single case report, Finnegan-Ling and
Musty (13) reported that THC p.o. was more effective than conventional pain medications,
including opiates and nonsteroidal anti-inflammatory drugs.
Very few studies have examined the effects of extracts with a low THC/cannabidiol
(CBD) ratio or experimentally varied pure THC and CBD mixtures. Sofia et al.
(14) conducted a comparison of the pain-relieving effects of Δ9-THC, a crude marihuana
extract (CME), cannabinol (CBN), CBD, morphine SO-4, and aspirin (all po).
They used the acetic acid induced writhing test, the hot plate test, and the Randall–
Selitto paw pressure tests in rats. Δ9-THC and morphine were equipotent in all tests
except that morphine was significantly more potent in elevating pain threshold in the
uninflamed rat hind paw. In terms of Δ9-THC content, CME was nearly equipotent in
the hot plate and Randall–Selitto tests, but was three times more potent in the acetic
acid writhing test. On the other hand, CBN, like aspirin, was only effective in reducing
writhing frequency in mice (three times more potent than aspirin) and raising the
pain threshold of the inflamed hind paw of the rat (equipotent with aspirin). CBD did
not display a significantly analgesic effect in any of the test systems used. The results
of this investigation seem to suggest that both Δ9-THC and CME possess analgesic
activity similar to morphine, whereas CBN appears to be a nonanalgesic at the doses
used. Only one human case study that used an extract with known amounts of THC,
CBD, and CBN (15) has been published prior to reports with orally administered
extracts. The extract contained THC (5.75%), CBD (4.73%), and CBN (2.42%). They
administered an oral extract to a person with chronic abdominal pain associated with
familial Mediterranean fever in a 6-week randomized placebo-controlled study. Both
normal use of morphine and escape use (dosing when an acute attack of pain occurs)
were significantly reduced. Self-reports on the visual analog scale also demonstrated
significant reductions in perception of pain.
Recently there have been several studies suggesting therapeutic potential for CB1
and CB2 agonists.
Dogrul et al. (16) reported that diabetic neuropathic pain is common and is resistant
to morphine treatment. Streptozotocin (200 mg/kg) was used to induce diabetes in
mice, which were tested between 45 and 60 days after onset of diabetes. Antinociception
308 Musty
was measured using the radiant tail flick test, Von Frey filaments, and the hot-plate
test, respectively. Tactile allodynia but not thermal hyperalgesia was found. WIN 55-
212-2a, a cannabinoid receptor agonist that acts in the CNS but is not inhibited by the
CB1 antagonist AM 251, produced a dose-dependent decrease in allodynia at doses of
1, 5, and 10 mg/kg.
Ibrahim et al. (17) tested the effects of AM 1241 (a selective CB2 receptor agonist)
on experimental neuropathic pain in rats. Tactile hypersensitivity and thermal
hypersensitivity were induced by ligation of L5 and L6 spinal nerves. AM 1241 dosedependently
reversed hypersensitivity. When tested in CB1 knockout mice using the
same ligation procedure, AM 1241 was effective in reducing pain sensitivity, suggesting
that this peripherally active agonist blocks neuropathic pain. The authors suggest
that CB2 receptor agonists, devoid of CNS activity, are predicted to be effective without
the CNS side effects of centrally acting cannabinoid agonists.
Johanek and Simone (18) examined whether or not cannabinoids attenuated
hyperalgesia produced by a mild heat injury to the glabrous hind paw and if the
antihyperalgesia was receptor-mediated. Mild heat injury (55°C for 30 seconds) to
one hind paw was given to anesthetized rats. Fifteen minutes after injury, decreased
withdrawal latency to radiant heat and increased withdrawal frequency to a von Frey
monofilament (200 mN force) delivered to the injured hindpaw was observed.
Intraplantar injection of vehicle or the agonist WIN 55,212-2 (1, 10, or 30 μg in 100 μL)
decreased heat and and mechanical hyperalgesia in a dose-dependent fashion, whereas
the inactive enantiomer WIN 55,212-3 did not. The CB1 receptor antagonist AM 251
(30 μg) co-injected with WIN 55,212-2 (30 μg) decreased the antihyperalgesic effects
of WIN 55,212-2,.and CB2 receptor antagonist AM 630 (30 μg) co-injected with WIN
55,212-2 decreased the antihyperalgesic effects of the agonist. Injection of WIN 55,212-
2 into the contralateral paw did not change heat-injury-induced hyperalgesia. These
results suggest that antihyperalgesia was mediated by peripheral mechanisms. The
authors conclude, like Ibrahim (17), that this reduction of hyperanalgesia may be
peripheral.
Nackley et al. (19) examined the effects of CB2-selective cannabinoid agonist
AM1241 on activity in spinal wide dynamic range neurons by transcutaneous electrical
stimulation urethane-anesthetized rats during either carrageenan inflammation or
not. Intravenous administration decreased activity in wide dynamic range neurons
induced by stimulation. This effect was blocked by the CB2 antagonist SR144528 but
not by the CB1 antagonist SR141716A. In addition, activity of nonnociceptive neurons
recorded in the lumbar dorsal horn was not affected by AM1241.
In a recent report, Chichewizc and Welch (20) found that Δ9-THC (20 mg/kg)
and morphine (20 mg/kg) induced analgesia in both vehicle-treated and morphinetolerant
mice. In both groups analgesia was equally effective, “indicating that analgesia
produced by the combination is not hampered by existing morphine treatment (no
cross tolerance to the combination).” Mice were tested with Δ9-THC (20 mg/kg) and
morphine (20 mg/kg) twice daily for 6.5 days and tested for tolerance, and on day 8,
Δ9-THC tolerance was observed, but morphine tolerance did not occur. These results
suggest that low-dose combinations of Δ9-THC and morphine might prevent morphine
tolerance. The authors conclude that combinations of these drugs may be useful in
chronic pain patients over morphine administration alone.
Cannabinoid Effects on Mental Processes 309
In summary, animal research indicates that there are potential effects on the control
of pain at many different levels of analysis. Some of these results are supported by
human studies, to be discussed later. Others must await clinical trials, assuming toxicity
and safety standards are met.
3.1. Human Studies
Brenneisen et al. (21) administered multiple does of either THC capsules
(Marinol®) or THC hemisuccinate suppositories at 24-hour intervals to two patients
who had spasticity due to organic damage. They found that the oral bioavailability
was 45–53% compared with the rectal route of administration, because the oral route
involves less absorption and higher first-pass metabolism. Both patients experienced
lower pain (self-rated) and decreased spasticity and rigidity as measured by the
Ashworth Scale and walking ability. Passive mobility also improved. Using physiological
and psychological testing, no differences were found in cardiovascular functioning,
ability to concentrate, or mood. Finally, the comparative effectiveness of the
oral form of administration was 25–50% of the rectal route.
Wade et al. (22) conducted a study testing the effects of plant-derived CME,
administered by buccal spray. Using a double-blind drug and placebo, single-patient
randomized crossover design, patients were administered the extracts THC, CBD, 1:1
CBD:THC by self-titration to doses providing symptom relief with the lowest possible
unwanted side effects. Doses to achieve relief were highly individual, ranging from 2.5
to 120 mg in a 24-hour period. Patients included 18 with multiple sclerosis (MS), 4 with
spinal cord injury, and one each with brachial plexus damage (7) and limb amputation.
Pain relief was measured using visual analog scales. THC, CBD, and the combination
were significantly superior to placebo. Impaired bladder control, muscle spasms, and
spasticity were improved by CME in some patients with these symptoms.
Brady et al. (23) tested the effects of cannabis-based medicinal extracts in patients
with advanced MS who had developed troublesome lower urinary tract symptoms.
Using an open-label design, THC and CBD (2.5 mg of each per oral spray) for 8
weeks followed by THC only (2.5 mg THC per oral spray) for a further 8 weeks and
then into a long-term extension were taken by the patients. Fifteen patients were evaluated
using the following measures: urinary frequency and volume charts, incontinence
pad weights, cystometry and visual analog scales for secondary troublesome symptoms.
Significant decreases in urinary urgency, the number and volume of incontinence
episodes, frequency nocturia, and daily total voided occurred in patients.
Self-assessment of spasticity, pain, and quality of sleep improved continuously for a
35-week period with both extracts.
Burstein et al. (24) reported that ajulemic acid, also known as CT-3 and IP-751,
derived from the major metabolite of THC, had many of the properties of the nonsteroidal
anti-inflammatory drugs and is apparently free of the intoxicating effects of
THC. In healthy patients and those with neuropathic pain, no psychotropic effects
were found. In short-term trials of 1 week, pain was reduced in patients with neuropathic
pain using a visual analog scale. Neither normal subjects nor pain patients
experienced any signs of either dependence or withdrawal. These data suggest that
ajulemic acid has therapeutic potential in the treatment of chronic pain.
310 Musty
Zajicek et al. (25) evaluated the effects of THC (Marinol) and a cannabis extract
(oral Cannador, a capsule with THC and an unstated amount of cannabidiol) in patients
with MS in a multicenter randomized placebo-controlled trial. They found no
effects on the Ashworth Scale in the 611 patients in the trial, but objective improvement
in mobility and reduction in pain occurred. One problem with this study is that
both THC and Cannador are poorly absorbed, which might explain the differences
between buccal spray administration and oral administration.
Svendsen et al. (26) tested the effects of dronabinol in patients with MS in a
randomized double-blind placebo-controlled crossover trial for 3 weeks followed by a
3-week washout period, then crossover to either drug or placebo for the final 3 weeks.
Twenty-four patients were enrolled through an outpatient clinic. Drug doses were
adjusted to a maximum dose of 10 mg daily. Using a numerical pain scale, scores were
significantly measured during the last week of treatment when compared with the
placebo condition. Dizziness occurred frequently during the first week of treatment.
Although the authors comment correctly that pain reduction was moderate in this study,
the design of the study did not allow patients to self-titrate doses of dronabinol, probably
minimizing the efficacy of pain reduction achieved by the patients.
In summary, it seems that cannabinoid agonists have potential for therapeutic
use in pain and MS. This is supported by the reports of GW Phamaceuticals discussed
in the next section.
4. VARIOUS POTENTIAL FOR NATURAL CANNABINOIDS
GW Pharmaceuticals (27) has an ambitious program testing a natural cannabinoid
mixture, Sativex® (THC:CBD ratio 1.1), in the form of an oral spray. Applications
for regulatory approval have been approved in Canada for neuropathic pain and
for symptoms of MS. Regulatory findings will be submitted in the United Kingdom.
Figure 1 shows the drug-development progress as of mid-2004. Note that Sativex is
presently in phase III trials for spinal cord injury and bladder dysfunction and in phase
II trials for diabetic neuroropathy. High-THC extracts are in various stages of development
for several types of pain. In addition, extracts high in CBD are also in various
stages of development.
5. PSYCHOLOGICAL DISORDERS (ANXIETY, DEPRESSION, BIPOLAR
DISORDER, SCHIZOPHRENIA, ALCOHOL DEPENDENCE)
5.1. Anxiety
In a review, Musty (28) concluded that for CB1 antagonists, it seems that the
preponderance of the data suggest that these compounds are anxiolytic. Agonists, on
the other hand, seem to have biphasic effects: low doses seem to be anxiolytic, high
doses anxiogenic. In addition, it seems that the context is important. Further research
is needed to sort out the differences among various studies, but it is clear that both
antagonists and agonists on the CB1 receptor have anxiolytic properties. Standardization
of testing procedures across laboratories might be helpful, the problem being that
Cannabinoid Effects on Mental Processes 311
there are many variables that have not been explored with behavioral methods used to
test for anxiolytic properties. Because it is widely known that activation and inactivation
of CB1 receptors has a multitude of modulatory effects on neurotransmitter systems,
it would be advantageous for researchers to examine what changes in
neurotransmitter activity occur in conjunction with the pharmacological effects conserved
in the types of studies. There seems to be quite a convergence between animal
research and human research, strongly suggesting that CBD is a true anxiolytic. Given
the fact that this drug has no psychoactivity in terms of intoxication and is very safe, it
seems important to pursue the potential of CBD with vigor, with further behavioral
pharmacological studies, mechanistic studies employing neuropharmacological methods,
and clinical studies.
5.2. Depression
In a review by Musty (11), the following summaries of research on depression,
bipolar disorder, schizophrenia, and alcohol dependence are presented:
In a study of normal subjects, Musty (29) found a positive correlation on the
depression scale of the Minnesota Multiphase Personality Inventory with feelings of
euphoria after smoking marijuana, while there was no correlation between anxiety
(hysteria scale) and somatic concerns (hypochondriasis scale) with feeling euphoric,
suggesting an antidepressive effect from marijuana use. Schnelle et al. (30), in a survey
of 128 patients in Germany, reported 12% used marijuana for relief of depression.
Fig. 1. Progress on preclinical and clinical trails of cannabinoid products by GW
Pharmaceuticals.
312 Musty
Consroe et al. (31) found that depression was reduced in patients with MS in a selfreport
questionnaire. In another self-report study (32) of patients with spinal cord injuries,
similar reductions in depression were reported. In cancer patients Regalson
(33) found that THC relieved depression in advanced cancer patients. Finally, Warner
et al. (34) found reported relief from depression in a survey of 79 mental patients. At
present, there are very few data supporting the hypothesis that cannabinoids might
relieve depression, but tests of both agonists and antagonists of the CB1 receptor are
clearly indicated to test this hypothesis.
Since the Musty review (11), Musty et al. (35) discovered that cannnabichromene
selectively blocks behavioral despair in a mouse model of depression. This is a novel
finding in that there has been very little work published on the effects of
cannnabichromene.
5.3. Bipolar Disorder
Grinspoon and Bakalar (36,37) presented six case studies of people with bipolar
disorder using cannabis to treat their symptoms. Some used it to treat mania, depression,
or both. They stated that it was more effective than conventional drugs or helped
relieve the side effects of those drugs. One woman found that cannabis curbed her
manic rages. Others described the use of cannabis as a supplement to lithium (allowing
reduced consumption) or for relief of lithium’s side effects.
These clinical observations are important leads to the potential use of cannabinoids
for manic depressive disorder and suggest that clinical trials should be conducted.
5.4. Schizophrenia
5.4.1. Animal Studies
Zuardi et al. (38) tested the effects of CBD and haloperidol in a model that predicts
antipsychotic activity in rats. Apomorphine induces stereotyped sniffing and biting.
Both drugs decreased the frequency of these behaviors. CBD did not induce
catalepsy, even at very high doses, although haloperidol induced catalepsy. The authors
conclude that CBD has a pharmacological profile similar to the atypical antipsychotic
drugs.
Musty et al. (2) tested the effects of the of the CB1 receptor antagonist SR141716
in two animal models of schizophrenia. In the first, ibotenic acid lesions of the hippocampus
were made in neonatal rats, which results in a brain degeneration pattern
similar to that observed in schizophrenics as well as abnormal play behavior in an
anxiety-provoking environment. In a second model, ketamine-induced enhancement
of prepulse inhibition was tested. In both of these tests, SR141716 reversed the abnormal
behavior. These findings in animal models are consistent with the hypothesis that
CB1 receptor antagonists have antipsychotic activity.
5.4.2. Human Studies
The use of cannabis has been associated with exacerbation of symptoms of schizophrenia
(39), but other reports suggest that the use of cannabis helped patients manage
their symptoms of schizophrenia, but several studies have shown potential symptomrelieving
effects of cannabis use.
Cannabinoid Effects on Mental Processes 313
Peralta and Cuesta (40) studied 95 schizophrenics who had used cannabis in the
last year. They found lower scores in the schizophrenics on delusions and alogia scales
of Andreasen’s Scales for the Assessment of Positive and Negative Symptoms, suggesting
that cannabis may affect the negative symptoms of schizophrenia. In a sample
of community-based mentally ill patients, Warner et al. (34) reported fewer hospital
admissions and fewer symptoms of anxiety, depression, and insomnia among users
preferring marijuana.
Zuardi and Morais et al. (41) reported an experiment in a single case, in which
the patient was being treated with haloperidol. The medication was stopped as a result
of side effects followed by a return of symptoms, leading to hospitalization. At this
point the patient was given placebo medication for 4 days, after which she was administered
CBD (two doses per day) on an increasing dose schedule up to 750 mg/dose
until the 26th day. This was followed by 4 days of placebo and finally by a return to
haloperidol for 4 weeks. Interviews were conducted and videotaped, which was followed
by rating of interviews using the Brief Psychiatric Rating Scale (BPRS) and the
Interactive Observation Scale for Psychiatric Patients (IOSPP). A psychiatrist rated
the patient, blind to treatment conditions on the BPRS, and nurse assistants independently,
and blind to treatment conditions rated the patient on the IOSPP. Comparing
placebo to the CBD condition, Hostility–Suspiciousness dropped by 50% of the BPRS
maximum scale score, Thought Disturbance by 37.5%, Anxiety–Depression by 43.7%,
Activation by 41.6%, and Anergia by 31.3%. During 4 days of placebo that followed,
all four scale scores increased somewhat. The patient was then returned to haloperidol
treatment, and the subsequent scores were close to those with CBD treatment. This
experiment demonstrates that antagonists of the CB1 receptor are candidates for testing
in human schizophrenia.
5.5. Alcohol Dependence
Musty (42) found that CBD, Δ9-THC, and clonidine reduced body tremor and
audiogenic seizures during alcohol withdrawal in C57Bl6J mice forced to become
alcohol tolerant on a liquid diet containing alcohol. Equivalent reductions in tremors
and seizures were found with clonidine. Grinspoon and Bakalar (36) reported two
cases of individuals who used marijuana to deal with alcohol dependence.
REFERENCES
1. Musty, R. E. (2004) Natural cannabinoids: interactions and effects, in The Medicinal Use
of Cannabis and the Cannabinoids (Guy, G. W., Whittle, B. A., and Robson, R. J., eds.),
Pharmaceutical Press, London, pp.165–204.
2. Musty, R. E., Deyo, R. A., Baer, J. L., Darrow, S. M., and Coleman, B. (2000) Effects of
SR141716A on animal models of depression. 2000 Symposium on the Cannabinoids, International
Cannabinoid Research Society, Burlington, VT, p. 109.
3. Donovan, M. (1845) On the physical and medicinal qualities of Indian hemp (Cannabis
indica); with observations on the best mode of administration, and cases illustrative of its
powers. Dublin J. Med. Sci. 26, 368–402, 459–461.
4. Van Den Broek, G. W., Robertson, J., Keim, D. A., and Baile, C. A. (1979) Feeding and
depression of abomasal secretion in sheep elicited by elfazepam and 9-aza-cannabinol.
Pharmacol. Biochem. Behav. 11, 51–56.
314 Musty
5. Foltin, R. W., Brady, J. V., and Fischman, M. W. (1986) Behavioral analysis of marijuana
effects on food intake in humans. Pharmacol. Biochem. Behav. 25, 577–582.
6. LeFur, G. (2004) Clinical results with rimonabant in obesity, in 14th Annual Symposium
on the Cannabinoids. International Cannabinoid Research Society, Burlington, VT, p. 67.
7. Beal, J. E., Olson, R., Lefkowitz, L., et al. (1997) Long-term efficacy and safety of
dronabinol for acquired immunodeficiency syndrome-associated anorexia. J. Pain Symptom
Manage. 14, 7–14.
8. Pi-Sunyer, F. X., Aronne, L. J., Heshmati, H. M., Devin, J., Rosenstock, J., RIO-North
America Study Group. (2006) Effect of rimonabant, a cannabinoid-1 receptor blocker, on
weight and cardiometabolic risk factors in overweight or obese patients: RIO-North
America: a randomized controlled trial. JAMA 295, 761–775.
9. Walker, J. M., Strangman, N. M., and Huang, S. M. (2002) Cannabis as analgesics, in
Biology of Marijuana. (Onaivi, E., ed.), Taylor and Francis, New York, pp. 573–590.
10. Bicher, H. I. and Mechoulam, R. (1968) Pharmacological effects of two active constituents
of marihuana, Arch. Int. Pharmacodynam. 172, 24–31.
11. Musty, R. E. (2002) Cannabinoid therapeutic potential in motivational processes, psychological
disorders and central nervous system disorders, in Biology of Cannabis (Onaivi, E.,
ed.), Taylor and Francis, New York, pp. 45–74.
12. Dunn, M. and Davis, R. (1974) The perceived effects of marijuana on spinal cord injured
males. Paraplegia 12, 175.
13. Finnegan-Ling, D. and Musty, R. E. (1994) Marinol and phantom limb pain: a case study.
Paper presented at the International Cannabis Research Society, July 21–23, L’Esterel,
Quebec, Canada.
14. Sofia, R. D., Vassar, H. B., and Knobloch, L. C. (1975) Comparative analgesic activity of
various naturally occurring cannabinoids in mice and rats. Psychopharmacologia 40, 285–295.
15. Holdcroft, A., Smith, M., Jacklin, A., et al. (1997) Pain relief with oral cannabinoids in
familial Mediterranean fever. Anaesthesia 52, 483–486.
16. Dogrul, A., Gul, H., Yildiz, O., Bilgin, F., and Guzeldemir, M. E. (2004) Cannabinoids
blocks tactile allodynia in diabetic mice without attenuation of its antinociceptive effect.
Neurosci. Lett. 368, 82–86.
17. Ibrahim, M. M., Deng, H., Zvonok, A., et al. (2003) Activation of CB2 cannabinoid receptors
by AM1241 inhibits experimental neuropathic pain: pain inhibition by receptors not
present in the CNS. Proc. Natl. Acad. Sci. 100, 10529–10533.
18. Johanek, L. M. and Simone, D. A. (2004) Activation of peripheral cannabinoid receptors
attenuates cutaneous hyperalgesia produced by a heat injury. Pain 109, 432–442.
19. Nackley, A. G., Zvonok, A. M., Makriyannis, A., and Hohmann, A. G. (2004) Activation
of cannabinoid cb2 receptors suppresses c-fiber responses and windup in spinal wide
dynamic range neurons in the absence and presence of inflammation. J. Neurophysiol. 92,
3562–3574.
20. Chichewizc, D. L. and Welch, S. (1999) Symposium on the Cannabinoids, International
Cannabinoid Research Society, Burlington, VT, p. 66.
21. Brenneisen, R., Egli, A., ElSohly, M. A., Henn, V., and Spiess, Y. (1996) The effect of
orally and rectally administered delta 9-tetrahydrocannabinol on spasticity: a pilot study
with 2 patients. Int. J. Clin. Pharmacol. Ther. 34, 446–452.
22. Wade, D. T., Robson, P., House, H., Makela, and Aram, P. (2003) A preliminary controlled
study to determine whether whole-plant cannabis extracts can improve intractable
neurogenic symptoms. J. Clin. Rehab. 17, 21–29.
23. Brady, C. M., DasGupta, R., Dalton, C., Wiseman, O. J., Berkley, K. J., and Fowler, C. J.
(2004) An open-label pilot study of cannabis-based extracts for bladder dysfunction in
advanced multiple sclerosis. Mult. Scler.10, 425–433.
Cannabinoid Effects on Mental Processes 315
24. Burstein, S. H., Karst, M., Schneider, U., and Zurier, R. B. (2004) Ajulemic acid: a novel
cannabinoid produces analgesia without a “high.” Life Sci. 75,1513–1522.
25. Zajicek, J., Fox, P., Sanders, H., et al. (2003) Cannabinoids for treatment of spasticity and
other symptoms related to multiple sclerosis (CAMS study): multicentre randomised placebo-
controlled trial. Lancet 362,17–26.
26. Svendsen, K. B., Jensen, T. S., Bach, F. W., Svendsen, K. B., Jensen, T. S., and Bach, F.
W. (2004) Does the cannabinoid dronabinol reduce central pain in multiple sclerosis?
Randomised double blind placebo controlled crossover trial. BMJ 329, 253.
27. GW Pharmaceuticals (2004) http://www.gwpharm.com/research_pipeline.asp
28. Musty, R. E. (2005) Cannabinoids and anxiety, in Cannabinoids as Therapeutics
(Mechoulam, R., ed.), Birkhauser Verlag, Basel, pp. 141–148.
29. Musty, R. E. (1988) Individual differences as predictors of marihuana phenomenology, in
Marihuana: An International Research Report (Chesher, G., Consroe, P., and Musty, R.,
eds.), Australian Government Publishing Service, Canberra, pp. 201–207.
30. Schnelle, M., Grotenhermen, F., Reif, M., and Gorter, R. W. (1999) Ergebnisse einer
standardisierten Umfrage zur medizinischen Verwendung von Cannabisprodukten im
deutschen Sprachraum [Results of a standardized survey on the medical use of cannabis
products in the German-speaking area]. Forsch. Komplementarmed. Suppl. 3, 28–36.
31. Consroe, P., Musty, R. E., Tillery, W., and Pertwee, R. (1997) Perceived effects of cannabis
smoking in patients with multiple sclerosis. Eur. Neurol. 38, 44–48.
32. Consroe, P., Tillery, W., Rein, J., and Musty, R. E. (1998) Reported marijuana effects in
patients with spinal cord injury. 1998 Symposium on the Cannabinoids, International Cannabinoid
Research Society, Burlington, VT, p. 64.
33. Regelson, W., Butler, J. R., Schultz, J., et al. (1976) Δ9-Tetrahydrocannabinol as an
effective antidepressant and appetite stimulating agent in advanced cancer patients, in
Pharmacology of Marijuana (Braude, M. C. and Szara, S., eds.), Raven Press, New York,
pp. 763–776.
34. Warner, R., Taylor, D., Wright, J., et al. (1994) Substance use among the mentally ill:
prevalence, reasons for use, and effects on illness. Am. J. Orthopsychiatry 64, 30–39.
35. Musty, R. E. and Deyo, R. A. (2003) Cannabichromene (CBC) extract alters Behavioral
Despair on the Mouse Tail Suspension test of depression, 2003 Symposium on the Cannabinoids,
Burlington, VT. International Cannabinoid Research Society, p. 146.
36. Grinspoon, L. and Bakalar, J. B. (eds.) (1997) Marihuana, the Forbidden Medicine, rev.
ed., Yale University Press, New Haven, CT.
37. Grinspoon, L. and Bakalar, J. B. (eds.) (1993) Marihuana, the Forbidden Medicine, Yale
University Press, New Haven, CT.
38. Zuardi, A. W., Rodrigues, J. A., and Cunha, J. M. (1991) Effects of cannabidiol in animal
models predictive of antipsychotic activity. Psychopharmacology 104, 260–264.
39. Negrete, J.C., Knapp, W.P., Douglas, D. E., and Smith, W. B. (1986) Cannabis affects the
severity of schizophrenic symptoms: results of a clinical survey. Psychol. Med. 16, 515–
520.
40. Peralta, V. and Cuesta, M. J. (1992) Influence of cannabis abuse on schizophrenic psychopathology.
Acta Psychiatr. Scand. 85,127–130.
41. Zuardi, A. W., Morais, S. L., Guimaraes, F. S., and Mechoulam, R. (1995) Antipsychotic
effect of cannabidiol. J. Clin. Psychiatry 56, 485–486.
42. Musty, R.E. (1984) Possible anxiolytic effects of cannabidiol, in The Cannabinoids
(Agurell, S., Dewey, W., and Willette, R., eds.), Academic Press, New York, pp. 829–844.

Index
AcompliaTM, see Rimonabant
Acquired immunodeficiency syndrome (AIDS),
marijuana effects on progression, 238,
239
Acute coronary syndrome, marijuana as trigger,
297, 298
Addiction,
endocannabinoid system in addiction to
other drugs, 133–135
marijuana withdrawal management, 132,
133
neural pathways, 113
opioid receptors in cannabinoid dependence,
133, 134
tolerance and dependence, 113, 114, 245, 246
Adipose tissue testing,
mass spectrometry, 184
rationale, 297
2-AG, see 2-Arachidonoyl glycerol
AIDS, see Acquired immunodeficiency
syndrome
Alcohol,
dependence and marijuana management, 313
endocannabinoid system and intake, 134
marijuana combination and impairment, 213
Alcohols, Cannabis composition, 36
Alkaloids, Cannabis composition, 29
Alveolar macrophage, marijuana effects,
258–260, 268, 269
AM 1241, analgesia, 308
Amygdala, CB1 receptors, 109
Analgesia,
cannabinoid agonist studies, 307–309
cannabinoid receptor agonists, 130–132
CB1 receptors, 112, 113, 130–132
endogenous cannabinoid system, 130
human studies of THC, 309, 310
pain pathways, 110, 112
THC efficacy, 307
Anandamide,
neuromodulation, 97–99
synthesis, 98, 127
Anxiety, cannabinoid antagonist studies, 310,
311
Apigenin, pharmacology, 40
Appetite,
cannabinoid effects, 303, 304
endogenous cannabinoid system in
homeostasis, 128, 129
rimonabant and suppression, 304, 305
THC effects, 129
Arachidonoyl ethanolamide, neuromodulation,
97–99
2-Arachidonoyl glycerol (2-AG),
neuromodulation, 97–99
synthesis, 98
vasodilatation, 116
B-cell, cannabinoid effects, 263, 264
Bipolar disorder, marijuana effects, 312
Blood pressure, cannabinoid effects, 115, 116,
239
Blood testing,
cause-of-death determination, 299
driving impairment testing,
11-carboxy-THC, 283, 284
317
318 Index
THC, 283, 284
THC/11-carboxy-THC ratio, 284, 285
interpretation of plasma tests, 212–217
mass spectrometry, 182–184, 192, 193
Bupropion, marijuana withdrawal studies, 132
Cannabichromene,
antidepressant activity, 312
biosynthesis, 7
features, 18
Cannabicyclol, features, 22
Cannabidiol (CBD),
anxiolytic activity, 311
biosynthesis, 7
features, 18, 19
indica content, 11
medical marijuana content, 11, 12
pharmacology and activity, 39
schizophrenia studies, 312, 313
Cannabidiolic acid, features, 18, 19
Cannabielsoin, features, 22
Cannabigerol,
biosynthesis, 7
features, 18
Cannabigerovan, biosynthesis, 7
Cannabinodiol, features, 23
Cannabinoid receptors,
agonist studies of analgesia, 307–309
antagonists, see Rimonabant
CB1 receptors,
addiction role, 113, 114
cardiovascular system, 116
distribution, 101, 126
knockout mice, 101, 112, 117, 133
limbic system, 109, 110
motor function, 103, 104, 106, 107
peripheral blood leukocyte expression, 263,
264, 298
signaling, 99–101, 127
splice variants, 99
types, 99, 126, 127, 297
Cannabinoid test system, features, 150, 151
Cannabinol,
analgesia, 307
features, 23
Cannabis, see also Indica,
chemical fingerprinting for source
identification, see Chemical fingerprinting,
Cannabis
color spot tests, 42
compound biosynthesis, 6, 7
domestication and dispersal, 8, 9, 14
drugs-of-abuse testing, see Immunoassays,
Cannabis; Mass spectrometry
ecology, 1, 2
epidemiology of use, 237, 253, 286, 295
life cycle, 1, 2
medical marijuana, see Medical marijuana
microscopy, 41, 42
origin, 8
production,
drug breeding, 9, 10
field crop, 2, 4
greenhouse and grow room, 4, 5
resin gland anatomy and development, 5, 6
species taxonomy, 9
Cannabis psychotic disorder, features, 245
Cannabitriol, features, 24
Cannachromavarin, biosynthesis, 7
Carbohydrates, Cannabis composition, 30, 31
Cardiovascular disease, epidemiology, 295
CB1 receptor, see Cannabinoid receptors
CBD, see Cannabidiol
CEDIA, see Cloned enzyme donor immunoassay
Cervical cancer, risks in marijuana users, 247
Chemical fingerprinting, Cannabis,
age and sex of plants, 61
chemometrics, 53, 54
compounds of interest, 54, 55
daughter plants grown in a different region, 61
experimental design, 56, 57
extraction, 57, 58
gas chromatography/mass spectrometry, 58
hashish analysis, 62
indoor versus outdoor plants, 60, 61
multivariate data analysis, 58, 59
overview, 51–53
phase II study, 59–63
prospects, 63, 64
storage condition effects, 61
Index 319
Cloned enzyme donor immunoassay (CEDIA),
principles, 148
Cognitive function, marijuana effects, 243–245,
278, 279
Color spot tests, Cannabis, 42
Cytokines, cannabinoid effects, 264–266, 270
DAT, see Drugs-of-abuse testing
Dependence, see Addiction
Depression, marijuana effects, 311, 312
Dihydrotestosterone, marijuana smoke
condensate antagonism, 94
DNA testing, Cannabis, 43
Driving impairment,
alcohol and marijuana combination, 213
cognitive effects of marijuana, 278, 279
epidemiology of marijuana and driving,
286
field sobriety testing, 280, 281
hallucinations, 279
highway accident studies, 247, 248
on-road driving studies, 288–291
physiological effects of marijuana, 277, 278
psychomotor effects of marijuana, 278, 279
relative crash risk assessment following
marijuana use, 287
toxicological tests,
blood, 283–295
oral fluid, 285, 286
overview, 281, 282
urine, 282, 283
Dronabinol, appetite induction, 304
Drugs-of-abuse testing (DAT), see
Immunoassays, Cannabis
Drugwipe®, sweat testing, 223, 224
ELISA, see Enzyme-linked immunosorbent
assay
Emesis, THC prevention, 129
EMIT, see Enzyme-multiplied immunoassay
technique
Enzyme-linked immunosorbent assay (ELISA),
principles, 149
Enzyme-multiplied immunoassay technique
(EMIT), principles, 147
Estrogen receptor, marijuana smoke condensate
interactions, 93, 94
Fatty acids, Cannabis composition, 32–34
Flavonoids, Cannabis composition, 31, 32
Fluorescence polarization immunoassay (FPIA),
principles, 147, 148
FPIA, see Fluorescence polarization
immunoassay
Gas chromatography/mass spectrometry
(GC/MS),
adipose tissue testing, 184
blood testing, 182–184, 192, 193
chemical fingerprinting of Cannabis, 58
chemometrics, 53, 54
hair testing, 187, 188, 197–199
immunoassay comparison, 161, 163, 164, 169
meconium testing, 184–186, 195
oral fluid testing, 186, 187, 196
phytocannabinoid analysis, 40, 42
urine testing, 180, 181, 189–191
GC/MS, see Gas chromatography/mass
spectrometry
Hair testing,
external contamination, 226
growth rate of hair, 225, 281
interpretation, 225–227
mass spectrometry, 187, 188, 197–199
Hallucinations, marijuana induction, 279
Head and neck cancer, marijuana smoking risks,
247
Heredity, marijuana effects, 246, 247
High-performance liquid chromatography
(HPLC), phytocannabinoid analysis, 42, 43
Hippocampus,
CB1 receptors, 109
memory role, 108, 109
HPLC, see High-performance liquid
chromatography
Hydrocarbons, Cannabis composition, 28
Hypothalamus,
CB1 receptors, 110
functions, 109, 110
320 Index
Immune system,
cannabinoid modulation, 116, 117
marijuana effects,
alveolar macrophages, 258–260, 268, 269
cytokine response to THC, 264–266, 270
overview, 239, 239
T-cell activation, 266–268
peripheral blood leukocytes and cannabinoid
receptor expression, 263, 264, 298
Immunoassays, Cannabis,
cannabinoid test system, 150, 151
cannabinoid-to-creatinine ratio studies, 167
evaluation,
cutoff concentrations, 159–161
efficiency, 159
gas chromatography/mass spectrometry
comparison, 161, 163, 164, 169
general evaluations, 159
sensitivity, 159
specificity, 159
hemp products, 166
heterogeneous competitive immunoassays,
148, 149
homogenous competitive immunoassays, 147,
148
immunogen strategies for antibody
generation, 155–157
overview, 147
point-of-collection immunoassays, 150
regulations and guidelines, 157, 158
specimen validity testing, 167, 168
stability of cannabinoids, 164, 166
THC medications, 166, 167
THC pharmacokinetics and metabolite
analysis, 151–155
Indica,
features, 10
sativa hybrids, 11
taxonomy, 9
Ketones, Cannabis composition, 36
KIMS, see Kinetic interaction of microparticles
in solution
Kinetic interaction of microparticles in solution
(KIMS), principles, 148
Lung cancer, marijuana smoking risks, 240, 241,
247, 261–263
Lungs, see Pulmonary function, marijuana
effects
Luteinizing hormone, marijuana effects, 241
Marijuana smoke condensate, see Smoke
condensate
Marijuana, see Cannabis
Mass spectrometry (MS),
adipose tissue testing, 184
blood testing, 182–184, 192, 193
gas chromatography coupling, see Gas
chromatography/mass spectrometry
hair testing, 187, 188, 197–199
marijuana smoke condensate analysis, 68–72
meconium testing, 184–186, 195
oral fluid testing, 186, 187, 196
phytocannabinoid analysis, 40, 42
urine testing, 180, 181, 189–191
Meconium testing, mass spectrometry, 184–186,
195
Medical examiner,
cause-of-death determination, 299, 300
THC screening, 298, 299
Medical marijuana,
abuse liability, 217
breeding, 13, 14
genetic modification, 13
sources and features, 11, 12
Morphine, THC combination for analgesia, 308
Motor function,
marijuana effects on driving, 278, 279
neuroanatomy,
basal ganglia, 103, 104, 106, 107
CB1 receptors, 103, 104, 106, 107
cerebellum, 103, 104, 106, 107
cortical areas, 101–103
MS, see Mass spectrometry
Myocardial infarction, marijuana as trigger,
297, 298
Nabilone, emesis prevention, 130
Naloxone, marijuana withdrawal studies, 133,
134
Index 321
Nefazodone, marijuana withdrawal
management, 132
Noladin ether, neuromodulation, 97–99
Nor-9-carboxy-Δ9-tetrahydrocannabinol
(THCA),
deuterated analogs, 179, 180
mass spectrometry,
blood testing, 182–184
hair testing, 187, 188, 199
meconium testing, 184–186
urine testing, 180, 181
Oral fluid testing,
driving impairment testing, 285
interpretation, 219–223
mass spectrometry, 186, 187, 196
Oropharyngeal cancer, see Head and neck
cancer
Pain, see Analgesia
Peripheral blood leukocytes, cannabinoid
receptor expression, 263, 264, 298
Pharmchek® patch, sweat testing, 223
Phenols, Cannabis composition, 35, 35
Phytocannabinoids, see specific compounds
Pirouette, chemometrics, 53
Plasma, see Blood testing
Postmortem redistribution, THC, 299, 300
Pregnancy, marijuana effects, 242, 243
Prolactin, marijuana effects, 241
Pulmonary function, marijuana effects,
acute effects, 254, 255
airway injury and bronchial epithelial
pathology, 257, 258, 298
alveolar macrophages, 258–260
animal studies, 255
human study overview, 255, 256
lung function testing, 256, 257
overview, 239, 240, 253, 254
respiratory symptoms, 256
Radioimmunoassay (RIA), principles, 148,
149
Reproductive function, marijuana effects, 241
Resin gland, anatomy and development, 5, 6
RIA, see Radioimmunoassay
Rimonabant,
appetite suppression, 304, 305
cannabinoid receptor antagonism, 217, 306
drug dependency studies, 133, 134
safety and tolerability, 306
Saliva, see Oral fluid testing
Sativex®, indications and clinical trials, 309,
310
Schizophrenia, marijuana studies,
animal studies, 312
human studies, 312, 313
Serum, see Blood testing
Smoke condensate,
behavioral activity, 72, 92
dihydrotestosterone antagonism, 94
estrogen receptor interactions, 93, 94
fractionation and analysis, 68–72
mutagenicity, 92, 93
preparation, 67, 68
pulmonary hazards, 93
table of compounds, 73–92
SR141716, see Rimonabant
Sweat testing, interpretation, 223
Tachycardia, cannabinoid induction, 116, 239
T-cell,
cannabinoid receptor expression, 263, 264,
298
THC effects,
activation, 266–268
T-helper balance and cytokine expression,
264–266
Teratogenicity, marijuana, 242
Terpenes,
biosynthesis, 6
Cannabis composition, 28
medical value, 7, 8, 40
types, 28, 29
Testicular function, marijuana effects, 241
Testosterone, marijuana effects, 241
Δ8-Tetrahydrocannabinol,
analgesia, 307
features, 21
322 Index
Δ9-Tetrahydrocannabinol (THC),
appetite effects, 129
biosynthesis, 7
deuterated analogs, 179, 180
emesis prevention, 129, 130
hemp seed product content, 27
isomers, 38
metabolism,
absorption, 207, 209, 210
distribution, 210, 296
elimination, 210–212
ingestion versus smoking, 216
metabolism, 151–155, 210
pharmacodynamics, 296, 297
pharmacokinetics, 151–155, 296, 297
social and scientific questions, 206
potency trends, 25–27
release, 207
synergy with other Cannabis compounds, 39
Δ9-Tetrahydrocannabinolic acids, types and
features, 19, 20
THC, see Δ9-Tetrahydrocannabinol
THCA, see Nor-9-carboxy-Δ9-
tetrahydrocannabinol
Thin-layer chromatography (TLC),
phytocannabinoid analysis, 40, 42
TLC, see Thin-layer chromatography
Urine testing,
driving impairment testing, 282, 283
interpretation, 217–219
mass spectrometry, 180, 181, 189–191
WIN 55,212-2, analgesia, 308