Testing

for Abuse

Liability

of Drugs

in Humans

U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES • Public Health Service • Alcohol, Drug Abuse, and Mental Health Administration
Testing for Abuse Liability of

Drugs in Humans

Editors:

Marian W. Fischman, Ph.D.

The Johns Hopkins University School of Medicine

Baltimore, MD

Nancy K. Mello, Ph.D.

Harvard Medical School/McLean Hospital

Belmont, MA

NIDA RESEARCH MONOGRAPH No. 92

1989

U.S. Department of Health and Human Services

Public Health Service

Alcohol, Drug Abuse, and Mental Health Administration

National Institute on Drug Abuse

5600 Fishers Lane

Rockville, MD 20857

i
NIDA Research Monographs are prepared by the research divisions of

the National Institute on Drug Abuse and published by its Office of

Science. The primary objective of the series is to provide critical reviews

of research problem areas and techniques, the content of state-of-the-art

conferences, and integrative research reviews. Its dual publication

emphasis is rapid and targeted dissemination to the scientific and

professional community.

Editorial Advisors

MARTIN W. ADLER, Ph.D. MARY L. JACOBSON

Temple University School of Medicine National Federation of Parents for

Philadelphia, Pennsylvania Drug-Free Youth

Omaha, Nebraska

SYDNEY ARCHER, Ph.D.

Rensselaer Polytechnic Institute REESE T. JONES, M.D.

Troy, New York Langley Porter Neuropsychiatric

Institute

RICHARD E. BELLEVILLE, Ph.D. San Francisco, California

NB Associates, Health Sciences

Rockville, Maryland

KARST J. BESTEMAN

Alcohol and Drug Problems

Association of North America

Washington, D.C.

GILBERT J. BOTVIN, Ph.D.

Cornell University Medical College

New York, New York

JOSEPH V. BRADY, Ph.D.

The Johns Hopkins University School

of Medicine

Baltimore, Maryland

THEODORE J. CICERO, Ph.D.

Washington University School of

Medicine

St. Louis, Missouri

DENISE KANDEL, Ph.D.

College of Physicians and Surgeons

of Columbia University

New York, New York

HERBERT KLEBER, M.D.

Yale University School of Medicine

New Haven, Connecticut

RICHARD RUSSO

New Jersey State Department

of Health

Trenton, New Jersey

NIDA Research Monograph Series

CHARLES R. SCHUSTER, Ph.D.

Director, NIDA

THEODORE M. PINKERT, M.D., J.D.

Acting Associate Director for Science, NIDA

Parklawn Building, 5600 Fishers Lane, Rockville, Maryland 20857

ii
Testing for Abuse Liability of

Drugs in Humans

iii
ACKNOWLEDGMENT

This monograph is based upon papers and discussions from a conference

on Testing for Abuse Liability of Drugs in Humans which took place on

November 5-6, 1988, at ameetingof the committee on Problems of Drug

Dependence, at the Scanticon Conference Center in Princeton, New

Jersey. The conference was sponsored by the Committee on Problems of

Drug Dependence, Inc., the National Institute on Drug Abuse, the Food

and Drug Administration, and the Drug Enforcement Administration.

COPYRIGHT STATUS

The National Institute on Drug Abuse has obtained permission from the

copyright holders to reproduce certain previously published figures and

tables, as noted in the text. Some of these have been modified for use in

this monograph. Further reproduction of the copyrighted material is

permitted only as part of a reprinting of the entire publication or chapter.

For any other use, the copyright holder’s permission is required. All other

material in this volume except quoted passages from copyrighted sources

is in the public domain and maybe used or reproduced without permission

from the Institute or the authors. Citation of the source is appreciated.

The opinions expressed herein are the views of the author(s) and do not

necessarily reflect the official position of the National Institute on Drug

Abuse or any other part of the U.S. Department of Health and Human

Services.

The U.S. Government does not endorse or favor any specific commercial

product (or commodity, service, or company). Trade or proprietary

names (or company names) appearing in this publication are used only

because they are considered essential in the context of the studies

reported herein.

DHHS publication number (ADM) 89-1613

Alcohol, Drug Abuse, and Mental Health Administration

Printed 1989

NIDA Research Monographs are indexed in the Index Medicus. They are

selectively included in the coverage of American Statistics Index,

BioSciences Information Service, Chemical Abstracts, Current Contents,

Psychological Abstracts, and Psychopharmacology Abstracts.

iv
I .

1.

2.

3.

4.

CONTENTS

Foreward ix

Preface xiii

I NTRODUCTION

Testing and Abuse Liability of Drugs in Humans

Charles R. Schuster 1

The Necessity and Utility of Abuse Liability Evaluations

in Human Subjects: The FDA Perspective

Frank J. Vocci, Jr 7

The Role of Abuse Liability Testing in Drug

Control Procedures

Howard McClain, Jr. and Frank Sapienza 21

Historical Perspectives on the Use of Subjective Effects

Measures in Assessing the Abuse Potential of Drugs

Jerome H. Jaffe and Faith K. Jaffe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

II. DRUG IDENTIFICATION AND CLASSIFICATION

5.

6.

Human Abuse Liability Assessment by Measurement of

Subjective and Physiological Effects

Donald R. Jasinski and Jack E. Henningfield 73

Drug Discrimination: Methods for Drug Characterization

and Classification

George E. Bigelow and Kenzie L. Preston 101

v
III. ASSESSMENT OF THE REINFORCING PROPERTIES

7.

8.

9.

10.

Abuse Liability of Anxiolytics and Sedative/Hypnotics:

Methods Assessing the Likelihood of Abuse

John D. Roache and Roland R. Griffiths 123

Drug Self-Administration Procedures:

Alcohol and Marijuana

Nancy K. Mello 147

The Use of Choice Procedures for Assessing the

Reinforcing Properties of Drugs in Humans

Chris E. Johanson and Harriet de Wit 171

Relationship Between Self-Reported Drug Effects and

Their Reinforcing Effects: Studies with Stimulant Drugs

IV. EPIDEMIOLOGIC ASSESSMENT OF DRUG ABUSE

Marian W. Fischman 211

O F DRUGS

11. Case Reports and the Assessment of Drug Abuse

Liability

Edward C. Senay 231

12. United States Epidemiologic Data on Drug Use and

Abuse: How are They Relevant to Testing Abuse

Liability of Drugs?

James C. Anthony and Alison M. Trinkoff 241

13. Current Approaches to Measurements of Drug Use

and Abuse in Sweden

Ulf Bergman and David Lee 267

vi
V. EVALUATION OF THE ABUSE LIABILITY OF DRUGS

IN HUMANS: ISSUES AND FUTURE DIRECTIONS

14. Pharmacokinetic and Phartnacodynamic Drug Interactions:

Implications for Abuse Liability Testing

Edward M. Sellers, Usanda Busto, and

Howard L. Kaplan 287

15. Promising New Biologic and Behavioral Correlates

of the Reinforcing Properties of Drugs

Jack H. Mendelson, Nancy K. Mello, Scott E. Lukas,

Bryan T. Woods, and Siew K. Teoh 307

16. Drug Abuse Liability Testing: Human Subject Issues

Herbert D. Kleber 341

17. Issues in Human Drug Abuse Liability Testing:

Overview and Prospects for the Future

Joseph V. Brady 357

18. Conference Summary and Perspectives on Human

Drug Abuse Liability Testing

Mary Jeanne Kreek 371

Index 377

List of NIDA Research Monographs 393

vii

FOREWARD

Ladies and Gentlemen:

I take great pleasure in welcoming you to this important conference on

Testing for Abuse Liability of Drugs in Humans. I thank you all for

coming and participating in the conference. This unique conference is

sponsored by the Committee on Problems of Drug Dependence (CPDD),

the Drug Enforcement Administration (DEA), the Food and Drug

Administration (FDA) and the National Institute on Drug Abuse (NIDA).

I encourage you to participate in the discussions.

Speaking for CPDD, we are delighted to be co-sponsoring this conference

with these governmental agencies. This partnership between the public

and private sector is essential if we are going to solve the multiple

problems associated with the abuse of chemical substances.

There are a number of people to thank for organizing this excellent

meeting. First and foremost, I thank Drs. Marian W. Fischman and

Nancy K. Mello, who served as co-chairs of the committee who prepared

the scientific program and other aspects of the meeting. They, and each

member of the human testing committee of CPDD are to be congratulated

for putting together such an excellent meeting.

A debt of gratitude is also owed to Dr. Martin W. Adler, the executive

officer of CPDD and his fine staff who handled all of the logistical aspects

of the meeting. Finally, on behalf of CPDD, I thank the government

agencies who are sponsoring this conference with CPDD for all aspects

of their support. Their participation in the planning of the conference was

essential. Let me hasten to add our thanks to those pharmaceutical

companies who have supported CPDD financially this year. Your

generous contributions have been used to support this conference and

other work of CPDD.

ix
I want to spend just a few minutes talking about what CPDD is doing at

the present time and why this conference is such a vital portion of that

endeavor.

The major tenet of the CPDD today is the same as it has been throughout

its 60 years of existence. That is, the problems caused by drug dependence

and drug abuse will be alleviated only by the appropriate use of knowledge

generated from research. Clearly this includes all aspects of treatment,

prevention, clinical, basic and many types of research.

The three specific objectives of CPDD are: 1) the testing of the

dependence liability of drugs, 2) holding the best and most comprehensive

scientific meetings on this topic, and 3) serving in advisory and other

cooperative capacities with governmental agencies who also are concerned

with the abuse of chemical substances. This conference addresses each

of these specific objectives.

Testing for abuse potential and physical dependence liability

CPDD initiated its activity in the testing of dependence liability of

chemical substances about 50 years ago when it set up the monkey colony

at the University of Michigan. When the number of compounds exceeded

the facility at that institution, a second colony was established at the

Medical College of Virginia of Virginia Commonwealth University.

Initially, both of these colonies were supported only by the generous

contributions of the pharmaceutical industry. In recent years, as research

has become more expensive, additional funding from NIDA was necessary

to continue these tests in monkeys and to expand the testing to include

other species and other procedures.

CPDD has now responded to the need to expand its animal physical

dependence liability testing capabilities to include abused substances

other than opiates. Due to the excellent work of Dr. Theodore J. Cicero

and the drug testing committee, CPDD has established procedures to test

drugs of the stimulant or depressant type for their dependence liability.

The University of Chicago and Johns Hopkins University have joined the

other two institutions in carrying out these evaluations. Many standard

compounds were run through this elaborate testing profile and at this time

six compounds submitted from industry are being tested on a blind basis.

CPDD will serve as an “honest broker” for these tests as we have for years

for the testing of opioids.

The reason for initiating this meeting is to help us in our next phase of

testing compounds for dependence liability. We feel that CPDD should

x
develop methodologies for testing the abuse potential of compounds in

humans. Our subcommittee on human testing realized that such a

meeting was an essential step in our initiation of this important phase of

testing.

The second objective of CPDD is to sponsor important scientific meetings

in the area of drugs of abuse. The format of the annual meeting has been

changed to include symposia, plenary Lectures, and an increased number

of poster presentations. The publication of the proceedings of the

meetings is also being improved on a continual basis.

Although these changes did not receive unanimous support from all

members of CPDD, even the most doubtful members will not argue with

the excellence of the science at the last two meetings. This will continue

for the 1989 meeting in June. CPDD also has sponsored other meetings

including the Narcotic Agonist/Antagonist meeting in Innisbrook, Florida

in 1983, and a conference on Cocaine in 1986. This meeting on human

testing is a continuation of that activity.

The third objective of CPDD is to interact with governmental agencies at

the state, federal and international level. This takes many forms. For each

of the last two years, CPDD has testified before the appropriations

committees in both Houses of Congress for continued and increased

support for research in this important area. We feel that increased federal

funding for research helps researchers in academia, government and

industrial laboratories. On numerous other occasions, CPDD has met

with key congressional leaders and their staff. CPDD has tested numerous

compounds, written extensive review type reports, and sent representatives

to the World Health Organization meeting in recent years.

Although it is not a governmental agency, CPDD will meet with the

executive officer of AALAC, the accrediting group for laboratory

animals, with the objective of having CPDD representation on the

Advisory Board. This type of interaction is essential in the continuing

battle against those who are against the humane use of animals in

research. The above is not an exhaustive list of what CPDD is doing with

governmental and other agencies, but time does not allow me to mention

them all.

The best example of how CPDD is interacting with various governmental

agencies is this conference. I welcome you to it, I thank you for coming

and contributing to this important topic.

Chairman, CPDD

WILLIAM L. DEWEY, Ph.D.

xi

Preface

The Committee on Problems of Drug Dependence (CPDD) was established

in 1929, and is the oldest organization in the United States concerned with

the scientific study of drug dependence and drug abuse. The CPDD has

traditionally supported independent research laboratories to evaluate

opioids for abuse liability and dependence potential using established

methodologies in non-human research subjects. CPDD has also supported

research to identify compounds with opioid antagonist or agonistantagonist properties. More recently, similar standardized and objective

procedures have been used to study stimulants and depressants in nonhuman research subjects. It is now well established that primates will

self-administer most drugs that are abused by man and are a valuable

model for drug abuse liability testing.

After over half a century as a forum for the investigation and evaluation

of the effects of drugs of abuse, in 1983, the CPDD, under the leadership

of Dr. Joseph V. Brady, began to explore the possibility of extending its

program of pre-clinical drug testing and evaluation to human research

subjects. Dr. Charles O’Brien volunteered to chair a subcommittee on

Human Testing, and representatives of academia, industry and government

began to discuss strategies for implementation of a human testing program.

By 1985, with Dr. Mary Jeanne Kreek as chairperson of the CPDD and

Dr. Marian W. Fischman chairing the Human Testing Subcommittee,

this new initiative had assembled a network of investigators experienced

in drug assessment in humans. The long and continuing process of

identifying appropriate procedures, subject populations, and databases

which might be useful for evaluation of abuse liability and dependence

potential in humans had begun. Working toward this goal, the Human

Testing Subcommittee has determined that both outpatient testing facilities

and specialized inpatient research wards are available for drug abuse

liability and dependence potential studies. In many cases, drug abuse

xiii
liability can be evaluated concurrently with other safety and efficacy

measures. Standard self-report measures of drug effects can be extended

to include measures of learning and performance, autonomic responses,

drug preferences and motivational changes. Of course, all studies

conducted with human volunteers must be carried out in accordance with

the requirements of local Institutional Review Boards.

Currently, the involvement of the CPDD in the Human Testing Program

is mainly one of coordination. CPDD helps to identify the drugs to be

tested and supports the validation of established methodologies using

standard compounds to encourage cross-laboratory generality of test

procedures. In addition, the Committee consults on the development of

protocols appropriate for specific drugs, and functions in an advisory

capacity for those organizations requesting assistance. Finally, CPDD

maintains a directory of investigators experienced in research on abuse

liability and dependence potential testing in human research subjects.

In November 1988, the Committee on Problems of Drug Dependence, in

conjunction with the National Institute on Drug Abuse, the Food and

Drug Administration and the Drug Enforcement Administration sponsored

its first conference on Testing for Abuse Liability of Drugs in Humans.

This conference was organized by CPDD Human Testing Committee cochairs, Dr. Marian W. Fischman and Dr. Nancy K. Mello, with the

assistance of a planning committee consisting of Dr. Roland R. Griffiths,

Dr. Herbert D. Kleber, Dr. Jack H. Mendelson, and Dr. Edward C. Senay.

The main purpose of this conference was to disseminate information

about the methodologies now available for testing drugs in humans, the

range of data that can be obtained, and the conclusions about abuse liability

and dependence potential that can be drawn from such data. Contributors

were asked to critically assess current methods for evaluating drugs in

human subjects and to describe both the advantages and limitations of

each approach. This information permits identification of areas in which

further research and development are needed.

Approximately 80 representatives from industry, academia and

government gathered to discuss these issues and the results of this seminal

conference on human drug testing are included in this monograph. This

effort has been facilitated by the good working relationship among federal

government agencies, academic institutions involved in drug development

and research, and the pharmaceutical industry. The mutual interests of

these various groups have best been served through close professional

interactions, and the ultimate success of the CPDD drug testing initiative

with humans will require continued collaboration and cooperation. We

hope that this is just the first of a series of CPDD sponsored conferences

xiv
designed to analyze specific issues related to testingfordrug abuse liability

and dependence potential. The CPDD is committed to stimulating and

maintaining a dialog among the various organizations actively involved

in drug development, drug regulation and research on drug dependence

and drug abuse.

Marian W. Fischman, Ph.D.

Associate Professor

Department of Psychiatry and

Behavioral Sciences

The Johns Hopkins University

School of Medicine

Nancy K. Mello, Ph.D.

Professor of Psychology

(Neuroscience)

Harvard Medical School/

McLean Hospital

xv

CHAPTER 1

Testing and Abuse Liability of Drugs in Humans

Charles R. Schuster, Ph.D.

INTRODUCTION

I am very pleased to be able to participate in this conference. Until I

became the Director of NIDA, a great deal of my professional life was

devoted to the development of procedures to test the dependence potential

and abuse liability of drugs. (Schuster and Thompson 1969; Schuster and

Johanson, 1974; Schuster and Balster 1977; Woolverton and Schuster

1983). So, I come here not only as an interested government official and

as one of the co-sponsors of this meeting, but also as a scientist with a

great interest in this area.

The recently enacted 1988 Anti-Drug Abuse Act contains significant

new funds for NIDA research and specifically earmarks $10 million for

the area of drug development. Drug development refers not only to the

development of drugs to be used in the treatment of addiction to illicit

drugs, but also to the development of drugs that will satisfy medical

needs, yet will possess lower abuse liability and dependence potential

than do currently existing therapeutic drugs. We are very pleased to add

the $10 million to our already existing program of drug development, and

we look forward to the major advances in this area that this funding will

make possible. However, we need some help from industry as well as

from the laboratories who do abuse liability testing. From NIDA’s point

of view, the abuse liability program fits into two areas. It is both basic

research and prevention. With regard to the latter, it is obvious that

preventing drugs with high abuse liability from falling into the hands of

those who would abuse them is really primary prevention. To do this, it

is not necessarily the case that drugs with high abuse liability must be kept

off the market. Rather, their introduction into the market should be made

with full knowledge of their abuse potential and the assignment of

appropriate regulatory conditions. No less important is the basic research

aspect of abuse liability testing. Obviously, the opportunity to test many,

many drugs which differ in chemical structure and pharmacologic action

and to correlate these measures of dependence and abuse liability provides

insight into the basic mechanisms underlying these drug actions. Basic

1
science is also well served by these activities because understanding the

basic behavioral and biological mechanisms underlying dependence will

enhance our understanding of the neurobiology of mood and affect.

I was going to discuss briefly the history of the Committee on Problems

of Drug Dependence (CPDD) but fortunately that has already been covered

by others. You are all aware of the fact that CPDD has had an extensive

history in evaluation of drug dependence potential. I would recommend

that you read Nathan B. Eddy’s book (1973) which reviews this history

if you have not already done so. I took advantage of the opportunity to

come here today and reread that book, and I can say that I have learned

a lot from it. One incident that I have to mention concerns Drs. Small and

Eddy’s “grooming” of Dr. Himmelsbach to take charge of the research

activities at the Lexington Narcotics Farm. Dr. Himmelsbach, then a

young commissioned officer in the Public Health Service, was first sent

to work with Dr. Toraid Stollmann at Western Reserve University in the

development of a rat model of morphine addiction. Later, he was sent to

Michigan to study under Dr. Eddy to gain experience in controlled

pharmacological testing and training in the appropriate “research attitude.”

As I look around the audience today, I am pleased to see the number of

people who essentially had the same kind of rigorous science training in

an animal laboratory and then applied these same kinds of procedures,

philosophy, and experimental designs to the problem with which we are

dealing today, that is, the assessment of abuse liability in humans.

Obviously, a pattern of training that Dr. Eddy initiated has been found to

serve us well.

Dr. Eddy’s review of CPDD’s program to develop dependence free

analgesics is interesting also. The rationale for the search for dependence

free analgesic drugs under the Advisory Committee on Drug Addiction

of the National Research Council of 1929 rested on two points. Information

indicated that codeine was an effective analgesic with little addiction

liability compared to morphine. This suggested that other chemical

modifications of morphine might result in even less abuse liability. In

addition, a temporal correlation between the introduction of procaine

onto the market and a large decrease in the widespread abuse of cocaine

suggested that, should a synthetic substitute for morphine be found,

morphine addiction would also decrease. We now know that the

description of codeine’s abuse liability was based upon testing an

inadequate dose range and that the availability of synthetic replacements

for cocaine did not preclude the emergence of cocaine addiction at epidemic

rates in the 1970s. Nonetheless, these two observations, according to

Dr. Eddy, lead the NRC Committee on Drug Addiction to pursue the goal

of finding a dependence free analgesic.

2
GOALS OF ABUSE LIABILITY TESTING

Iatrogenic Addiction and Dependence

I would ask the question again, why should we evaluate drugs for their

abuse liability or their dependence potential? Obviously, one reason

relates to the basic science goals that are served by abuse liability testing

which I have already mentioned. In addition, there are two practical

reasons: (1) to avoid iatrogenic addiction and dependence, and (2) to

restrict the availability of new drugs for rediversion into the drug subculture.

However, is our level of concern about iatrogenic addiction or dependence

appropriate? Consider the work of Porter and Jick who reported that an

analysis of over 39,000 hospital records identified 11,382 hospitalized

patients who had been treated with various narcotics. Follow up on these

people over a period of 5 years or longer revealed only four cases of

iatrogenic addiction (Porter and Jick 1980). Clearly, fear of iatrogenic

addiction does not justify either the under-utilization or the avoidance of

the use of dependence-producing drugs for the treatment of patients’ pain

since iatrogenic addiction, at least in this study of patients given these

drugs in a hospital setting, was extremely low.

Amphetamines: Another drug that we associate with abuse but for

which there is little evidence of iatrogenic dependence is amphetamine.

The first studies that I ask you to consider are old and come from Chauncey

Leake’s book (1958). At the time when it was written in 1958, he cited

several clinical studies in which amphetamines were given daily for years

with no sign of habituation or dependence. One hundred seventy-five

patients were exposed to 25 mg a day of amphetamine for four years for

therapeutic purposes and showed no signs of habituation or addiction.

Other studies of doses of up to 45 mg a day used for at least nine months

concluded that there was no evidence of habituation or iatrogenic addiction

in these patients (Leake 1958). More recently, several members in the

audience such as Drs. Bigelow and Griffiths (1980) allowed patients,

who were being treated for obesity, to take as many as six 5 mg damphetamine tablets per day. They followed drug consumption over a

period of four weeks. The total number of amphetamine tablets that were

available over the four week period was 168, yet people averaged only 1.8

to 1.9 tablets a day, a fraction of the number available. Our assumption

would be that if these people had become dependent we would have seen

an increase in their consumption of the drug and, in fact, over the 4 week

period, the number of tablets taken each day was never more than half

those available and went down over time. I think that the potential for

iatrogenic dependence on opiates and amphetamines when they are used

under appropriate circumstances is less than we might realize.

3
Benzodiazepines: Many people have concluded that iatrogenic

dependence to benzodiazepines is possible even at therapeutic doses.

These data are complex, and I will not attempt to review them here.

Nevertheless, I would say that given the numbers of people who have

been exposed to the benzodiazepines, the incidence of iatrogenic

dependence is still relatively low. While testing for dependence potential

in order to avoid iatrogenic addiction is obviously of importance, I think

we should not overstress it since the incidence of iatrogenic dependence

and addiction at least with narcotics and amphetamines appears to be low.

Restriction of Drug Availability

The second reason we do abuse liability testing is because we want to

restrict the availability of drugs to appropriate patients and not let them

get into the hands of the drug using subculture. Rediversion of drugs

should concern us for several reasons. For example, physicians and

pharmacists are concerned about stocking and storing drugs that have

high abuse liability and dependence potential because of potential theft

and robbery. There are many drug stores that will not stock narcotics for

this reason. However, regulations that decrease the opportunity for drug

diversion may also increase cost and decrease availability to patients.

Furthermore, the use of a drug that is scheduled because of its dependence

potential or addiction liability may stigmatize patients who have to take

it. I have seen an illustration of this where an individual was taking

pentazocine and getting effective pain relief. The family became concemed

that the patient might become addicted when they found out that

pentazocine was being combined with an antihistamine and administered

intravenously in the drug subculture. This type of stigmatization could

be avoided if we had an analgesic that was free of abuse liability. Not only

would such a drug do a great deal to decrease illicit use, but more

importantly, it would allow patients pain control without stigmatization,

IMPORTANCE OF DEFINING POPULATIONS FOR TESTING

The various applications of abuse liability testing require researchers to

consider the nature of the population represented in their studies and the

nature of the population to whom the results can be applied. If researchers

are interested in iatrogenic addiction, then they should be testing drugs

in the appropriate patient population because this is the group who will

be exposed therapeutically. You cannot use the members of the drug

using subculture and find that they will use the drug and then assume that

patients will become dependent on the drug. On the other hand, if you are

interested in whether or not the drug, if it were available, would be used

4
by the drug using subculture, then obviously you want to go to abusers

of similar drugs to carry out your studies. Thus, for example, if you are

interested in whether anew benzodiazepine has more or less abuse liability

than those currently available, you should test it in people who are currently

misusing benzodiazepines.

If you want to study the issue of vulnerability to drug abuse, i.e., are there

characteristics about people that make them more or less susceptible to

the reinforcing or abuse potential of drugs, then you would have to have

a heterogeneous population. In many instances, we use a normal population

to determine those who do and do not find the drug sufficiently reinforcing

to continue to use or abuse it. In any case, the nature of your question and

the application you wish to make of your answer should determine the

nature of your subject population.

FACTORS CONTRIBUTING TO RATES OF DRUG ABUSE IN

THE GENERAL POPULATION

The final thing I want to talk about is the issue of what variables or factors

modulate whether or not abuse liability is actually realized. Animal and

human screening procedures have identified dozens of narcotics that

appear to have high abuse liability, yet there is relatively little abuse of

them. Obviously, a number of factors influence whether or not a drug will

be used illicitly. One factor is potency: drugs in a laboratory can be given

in large quantities, but the drug using subculture does not want to carry

suitcases of the drugs around in order to get high; it is impractical. On the

other hand, drugs such as the superfentanyls, which are so potent that very

tiny amounts can result in lethal overdosage, are also a problem because

the drug using subculture may not be equipped to do the necessary dilutions

to achieve a desired effect. Solubility is another factor if a drug is going

to be used intravenously. The more difficult the drug is to solubilize, the

less attractive it is to street users. As we have learned from crack and

cocaine, if a drug can be smoked, it has a high probability of abuse. Thus,

route of administration is clearly a factor.

Environmental factors must be considered as well. Social milieus, such

as those of the 60s and 70s in which drug experimentation was considered

a normal part of growing up, exposed a great proportion of the population

to illicit drugs. Drugs that individuals considered desirable continue to

be used and abused. Other social/behavioral factors include peer pressure

and the association between drug use and role models. Cost of drugs is

also a factor in whether or not a drug is widely abused.

5
SUMMARY

In summary, there are a number of factors to be considered in abuse

liability testing such as the purpose of the testing and its potential

applications that determine which subject population we should employ.

Furthermore, we should not expect to see a perfect correlation between

abuse liability testing and the actual abuse of these drugs because there

are many factors that will modulate or modify whether or not abuse

liability becomes activated and the abuse of any specific drug becomes

a social problem.

REFERENCES

Bigelow, G.E.; Griffiths, R.R.; Liebson, I.A.; and Kalisazak, J.E. Double-blind

evaluation of reinforcing and anorectic actions of weight control

medications. Arch Gen Psychiat 37:1018-1023, 1980.

Eddy, N.B. The National Research Council Involvement in the Opiate Problem.

1928-1971. Washington, D.C.: National Academy of Sciences, 1973.

Leake, C.D. The Amphetamines: Their Actions and Uses. Springfield, IL:

Charles C. Thomas Publishers, 1958. 167 pp.

Porter, J., and Jick, H. Addiction is rare in inpatients treated with narcotics. N

Eng J Med 302(2):123, 1980.

Schuster, C.R., and Balster, R.L. Discriminative stimulus properties of drugs. In:

Thompson, T., and Dews, P.B., eds. Advances in Behavioral

Pharmacology vol. 1. New York: Academic Press. 1977, pp. 85-138.

Schuster, C.R., and Johanson, C.E. The use of animal models for the study of

drug abuse. In: Gibbons, R.J.; Israel, Y .; Kalant, H.; Popham, R.E.;

Schmidt, W.; and Smart, R.G., eds. Recent Advances in Alcohol and

Drug Problems vol. 1. New York: Wiley and Sons, 1974, pp. 1-31.

Schuster, C.R., and Thompson, T. Self-administration of and behavioral

dependenceonclrugs. An Rev Pharmac 9:483-502, 1969.

Woolverton, W.L., and Schuster, C.R. Behavioral and pharmacological aspects

of opioid dependence: Mixed agonist-antagonists. Pharmacol Rev 35:33-

52, 1983.

AUTHOR

Charles R. Schuster, Ph.D.

Director

National Institute on Drug Abuse

5600 Fishers Lane

Rockville, Maryland 20857

6
CHAPTER 2

The Necessity and Utility of Abuse Liability

Evaluations in Human Subjects:

The FDA Perspective

Frank J. Vocci, Jr., Ph.D.

INTRODUCTION

Assessments of the abuse potential of psychoactive drugs in preclinical

and clinical studies are used in regulatory decision making processes

under the Controlled Substances Act (CSA) and the Federal Food, Drug,

and Cosmetic Act (FD & C Act). The involvement of the Secretary of

Health and Human Services in the evaluation of drugs of abuse is mandated

in section 201 (b) of the CSA. Further, in the New Drug and Antibiotic

(NDA) regulations (21 CFR 314.50 (d) (5) (vii)), the Food and Drug

Administration (FDA) has codified the requirement for clinical studies of

abuse potential and requires the pharmaceutical sponsor to submit

proposals for scheduling under the CSA. However, FDA recognizes that

there are drugs of abuse that will not be pursued for marketing by the

pharmaceutical industry. In certain cases, the toxicological profile of a

compound may preclude clinical testing (e.g., MDMA) or compounds of

more limited interest may be evaluated for drug scheduling using data

solely from preclinical studies (e.g., p-fluorofentanyl).

In the case of drugs that are being pursued for marketing or are amenable

to study in human subjects and of scientific, medical, orregulatory interest,

preclinical data may be inadequate for decisions that must be made under

both the CSA and The FD&C Act. Preclinical data assessment can suggest

the following conclusions: a drug can appear to have a lesser, equal, or

greater abuse potential than an appropriate prototype; additionally, a

drug may have an equivocal or conflicting (e.g., species-specific) profile.

Further, the validity of a preclinical assessment may be reviewed on the

basis of pharmacokinetic differences (rates of absorption, metabolism,

excretion and “pro-drugs” which can be metabolized qualitatively and

quantitatively differently) and pharmacodynamic differences (subtle shifts

in receptor subpopulations across species and/or shifts in receptor

selectivity) between animal and human populations. Even in the case of

7
valid preclinical data, there are limitations to the feasibility and

interpretation of certain drugs/dosage forms and our ability to make fine

discriminations in abuse potential from preclinical data.

Thus, clinical studies are needed for the following scientific reasons: to

validate the conclusions of either lesser or greater abuse potential from

preclinical data; to evaluate the psychopharmacology of drugs in human

populations in situations where the preclinical data are equivocal or speciesspecific; to evaluate the onset, peak, and duration of subjective effects as

a function of dose and route of administration; to relate the degree of

overlap between the therapeutic dose range and the range of doses

producing subjective effects; to evaluate thegeneralizability of drug timing

in different human subject populations; and to evaluate the effects of

drugs on inner mental life (e.g., cognitive processes including memory/

amnesia, and affective changes). Clinical studies are also needed in the

case of a sponsor’s claim of the following: reduced or no abuse potential;

reduced abuse potential by combining with an antagonist/abuse deterrent;

and lack of additive or potentiative effects with alcohol.

Other situations necessitating clinical studies include when a dosage

form is not amenable to study in preclinical populations (e.g., drug in

chewing gum) and in the case of new drug classes (e.g., inverse

benzodiazepine receptor agonists). Finally, efficacy and safety of potential

agents for treatments of drug abuse/dependence must be validated in pilot

clinical studies. Data generated from the types of clinical studies mentioned

above can be used for CSA scheduling purposes and drug labeling issues

under the FD&C Act.

FDA’S REGULATORY RESPONSIBILITIES REGARDING

DRUG ABUSE

I have been asked to describe FDA’s view on human abuse liability

testing. But before I get into this topic, I would like to define FDA’s

responsibilities in the area of drug abuse. The involvement of the Secretary

of Health and Human Services in the evaluation of drugs of abuse is

mandated in section 201 (b) of the CSA. FDA, in concert with the National

Institute on Drug Abuse (NIDA), has been given the responsibility for the

assessment of abuse potential and dependence capacity of psychoactive

drugs and the necessity and propriety of drug scheduling under the

Controlled Substances Act (CSA). Further, in the New Drug and Antibiotic

(NDA) regulations (21 CFR 314.50 (d) (5) (vii)), FDA has codified the

requirement for clinical studies of abuse potential and requires the

pharmaceutical sponsor to submit proposals for scheduling under the

8
CSA. FDA regulates the clinical investigation of drugs of abuse and

products which may alter the abuse potential of a product through the

Investigational New Drug (IND) process. The regulation of clinical

studies includes clinical pharmacology studies which demonstrate the

therapeutic utility of a drug, basic clinical research issues involved in

defining the neurobiology of a drug of abuse, and studies which are aimed

at defining the abuse potential of a drug. FDA also has the responsibility

for the determinationof safety and efficacy of psychoactive drug products

and their directions for use for drug products marketed in the U.S.

Statements regarding the abuse potential of a drug and other related

pharmacological properties can be found in the CLINICAL PHARMACOLOGY,

WARNINGS, DRUG ABUSE AND DEPENDENCE, DRUG INTERACTIONS, and

possibly DRUG OVERDOSE sections of the product labeling.

As stated above, FDA has codified the requirement for clinical studies of

abuse potential for drugs developed for marketing. This requirement

evolved from the general policy that the ultimate model for the

determination of drug effects in man is man. This basic tenet has held

across all drug classes and would be the same for drugs of abuse. In fact,

the Guideline for the Format and Content of the Clinical Section of New

Drug Applications states that if a sponsor does not perform (clinical)

studies of abuse potential of a drug which is chemically or

pharmacologically similar to a known drug of abuse, an explanation

should be given as to why it was unnecessary to perform such studies.

RELATIVE CONTRIBUTIONS OF CLINICAL AND PRECLINICAL TESTING FOR ABUSE POTENTIAL

Since the field of drug abuse research has both preclinical and clinical

studies, I would like to give you some insight into how we perceive the

relative contributions of preclinical and clinical testing for the

determination of abuse potential.

Preclinical studies have an important role in the determination of abuse

liability of a substance. A variety of test systems are used to look for

similarities and differences between a test substance and a standard. For

example, radioligand binding experiments, neurochemistry experiments

involving release or uptake of neurotransmitters, in vitro smooth muscle

preparations, pharmacological studies (e.g., locomotor activity, rotarod

testing, and antinociception testing), and certain toxicology studies (e.g.,

isolated versus aggregate lethality studies) can and are used to make

inferences about the abuse potential of a drug. Additionally, behavioral

9
pharmacology studies are employed to define the stimulus generalization

properties, the reinforcing capacity, the pattern of drug intake under various

conditions, and the substitution capacity of a test drug in physical

dependence paradigms. From a general toxicological standpoint,

preclinical studies which define the acute lethality and subacute toxicity

support the relative safety of administration of a psychoactive compound

to man. It should be remembered that this is especially important in the

field of drug abuse testing as the range of doses administered to volunteer

populations is often several multiples of the recommended therapeutic

dose range. Thus, the acute toxicity of a drug and its potential reversibility

are issues that affect human drug testing in general and human abuse

liability assessment in particular. Moreover, as these data are often

generated before clinical studies, preclinical data are used for hypothesis

generation. During the development of a drug product, preclinical studies

used for hypothesis generation will support four possible outcomes. These

outcomes are shown in table 1. The first possible outcome is that the

abuse potential of a drug is equivalent to a prototypic agonist. In the case

of obvious pharmacological equivalence the drug would not need any

Table 1. Possible outcomes from preclinical studies regarding abuse

potential of a drug under development

CASE OUTCOME

# l Test drug is equivalent in abuse potential to a prototypic

agonist

#2 Test drug has a lesser abuse potential than a prototypical

agonist

#3 Test drug has a greater abuse potential than a prototypical

agonist

#4 Data on test drug are conflicting with respect to abuse

potential of a prototypic agonist

further testing for the determination of scheduling unless the firm

developing the drug did not accept the preclinical findings. In that case,

it is their prerogative to perform clinical studies that substantiate their

claim of a lesser abuse potential. The second and third cases, that is

involving the situations in which a drug appears to have a greater or lesser

abuse potential than a prototype, should be followed up by clinical studies

that test the appropriate hypothesis. The fourth case, namely where the

preclinical data are equivocal or conflicting (e.g., species-specific effects),

10
also requires clinical studies to determine the abuse liability of the substance

in man.

I will give examples of each type of possible outcome. The first situation

canarisewhenanopioidagonist issubmitted to the Committee on Problems

of Drug Dependence (CPDD) testing program. Academic and industry

medicinal chemists continue to submit compounds for evaluation in this

test system. If a substance is determined to be a full morphine-like

agonist, no further testing is necessary to determine the abuse potential

of the substance. A second example of this type of outcome can arise

when afentanyl analog is tested. If the analog shows full agonist activity,

no further testing is necessary for appropriate regulatory action.

An example of the second case, i.e., a drug with a lesser abuse potential,

would be buspirone. Although all the preclinical data suggested a lack

of sedative-hypnotic type activity, it should be noted that FDA asked the

sponsor to conduct clinical psychopharmacological studies to substantiate

the lack of reinforcing capacity (Cole et al., 1982: Griffith et al., 1986)

and lack of interaction with ethanol. Also please note that two clinical

studies were performed to determine and validate the lack of reinforcing

subjective effects of this compound.

Anexampleof a drug withpossiblygreaterabusepotential than a prototype

was suggested by the differential rate of self-administration of midazolam

versus diazepam in the baboon (Griffiths et al., 198 1). In fact, midazolam

response rates approached those seen with cocaine and pentobarbital.

The robust self-administration of midazolam, also seen with triazolam,

was suggested to be due to the rapid elimination rates of these drugs

(Griffiths and Lukas 1982). The clinical abuse potential of this drug

compared to diazepam is still an open issue.

The fourth type of outcome i.e., equivocal or conflicting results, can be

illustrated by the data on butorphanol. In the rat, butorphanol

administration occasioned responding to both a morphine-like

discriminative stimulus and also to a cyclazocine stimulus (Holtzman

1985). In the spinal dog preparation, butorphanol did not suppress

morphine abstinence (Martin et al., 1976). In the squirrel monkey,

butorphanol partially generalized to morphine (Holtzman 1985).

Butorphanol did not suppress morphine withdrawal signs in dependent

rhesus monkeys undergoing withdrawal (Swain et al., 1973). However,

butorphanol was self-administered in rhesus monkeys, being similar to

pentazocine in this regard (Woods 1977). Thus, the preclinical data

suggested a drug with both morphine-like and nonmorphine-like

properties.

11
One possible interpretation of these data is that there are interspecies

differences in the types of opioid receptor subtypes with which the drug

interacts. Another possibility is that the intrinsic efficacy of the drug for

each opioid subreceptor type may change from species to species. The

question was whether butorphanol would be perceived to be morphinelike or more like pentazocine in man. Thus, it can be seen that conflicting

or difficult to interpret preclinical data necessitate evaluation of the abuse

potential of a compound in man. Administration of butorphanol to human

post-addicts produced the following morphine-like effects: positive doseresponse effect on opiate signs and symptoms, and subjects’ liking and

observers’ liking scales. However, the drug also failed to produce a

significant score on the Morphine-Benzedrine Group subscale. Unlike

morphine, butorphanol produced dose-related increases in the

Pentobarbital Chlorpromazine Alcohol General (PCAG) and Lysergic

Acid Diethylamide (LSD) subscales of the Addiction Research Center

Inventory (ARCI) (Jasinski et al., 1975). A follow-up study by these

same investigators compared butorphanol to pentazocine, cyclazocine,

and morphine. The observations of elevated scores on the LSD and

PCAG subscales were confirmed for butorphanol. In this regard it was

like pentazocine and cyclazocine and unlike morphine. Butorphanol,

cyclazocine, and pentazocine produced a different cluster of responses

than morphine on the symptoms and signs categories for “sleepy,”

“drunken,” “nervous,” and “barbiturate-like.” A chronic dosing study in

post-addicts noted that an 8 mg S.C. dose of butorphanol was consistently

identified as a barbiturate (170/210 possible identifications). The liking

scores from the chronic dosing study showed butorphanol did not produce

elevated scores in liking whereas historical data from the same laboratory

showed somewhat dose-related elevated liking scores for 30, 120, and

240 mg. of morphine per day (Jasinski et al., 1976). The finding of a

pentazocine-like effect of butorphanol was confirmed by Preston et al.

(1987), who reported that butorphanol was identified as pentazocine by

post-addicts who were trained to discriminate hydromorphone from

pentazocine and saline.

There are several situations in which preclinical data will suffice for the

determination of the necessity of drug scheduling under the CSA. The

first has already been mentioned: i.e., the case where a full agonist is

shown to be equivalent in abuse potential to a prototype. Also in the case

of a “street” drug, preclinical data showing a generalization to morphine,

PCP, or amphetamine in concert with other pharmacological and

behavioral data will suffice for drug scheduling under the CSA. In part

this is because the recognition of a potential for abuse will necessitate that

the drug be placed into Schedule I. Thus, a fine discrimination of abuse

potential may not be necessary. Finally, it may be unethical to test a drug

12
of abuse in a human population due to a lack of preclinical toxicity data

or a disturbing finding associated with administration of the drug in

animals (e.g., MDMA). In this instance, preclinical data will suffice for

the determination of drug scheduling under the CSA.

There are several considerations which must be kept in mind in the

extrapolation of preclinical data to man. It must be appreciated that

interpretation of preclinical data must consider biological and

pharmacological differences between animal species and man. Biological

differences between animals and man include a higher rate of metabolism

of xenobiotic compounds in animal species. This generally produces a

more rapid excretion of compounds that results in a shorter duration of

action of a drug in infrahuman species. Table 2 illustrates the point about

Table 2. Diazepam terminal plasma elimination half-lives in several

species

Species Half-life(hours)

Rat 1.1

Guinea pig 2.4

Rabbit 2.7

Dog 7.6

Man 32.9

Data abstracted from Klotz et al., 1976

differences in plasma elimination half-lives for diazepam (Klotz et al.,

1976). Additionally, qualitative differences in drug metabolism are

possible. Subtle shifts in receptor subpopulations across species or in

intrinsic efficacy of a drug towards receptor subpopulations may cause

problems in data interpretation and extrapolation. For example, a drug

may be a partial agonist in one species at a receptor subtype and an

antagonist at the same receptor subtype in another species. Other possible

differences in the estimation of abuse potential could arise in the situation

of “pro-drugs”; i.e., substances which must be metabolized to active

metabolitesbefore attaining pharmacological activity. If a species lacked

the necessary enzymatic machinery or simply did not biotransform the

substance the same as man, a significant discrepancy in the abuse potential

13
of the substance could result. An example of such a drug would be

tilidine, an opioid agonist. The drug produced mild dependence after 47

days of administration in rats. In morphine dependent rhesus monkeys,

parenterally administered tilidine did not demonstrate either agonist or

antagonist properties. In man, tilidine was 1/8-1/10 as potent orally and

1/22 as potent parenterally as morphine in producing subjective effects

and miosis (Jasinski and Preston 1986).

From the preceding discussion, it can be seen that one cannot possibly

answer all the questions about the abuse potential of a drug from preclinical

studies. Thus, clinical studies are necessary from a scientific standpoint.

Clinical evaluation of abuse potential is also necessary in some

circumstances from both practical and regulatory standpoints. From the

practical aspect of testing, it may not be possible to test the exact dosage

form in an appropriate animal model. Thus, while the reinforcing capacity

of nicotine may be established (Henningfield et al., 1985), the issue before

FDA might be the abuse potential of a chewing gum containing nicotine.

It is obviously not possible to determine the abuse potential of this dosage

form in an animal model. The same type of issue arises in considering the

problem of comparing an oral versus a smoked dosage form of a product

or other dosage forms like sublingual or buccal delivery systems or

transdermal patches. Similarly, dosage forms of abusable substances

which are controlled release or delayed release dosage forms should be

evaluated in human populations. From the regulatory viewpoint, it is

often difficult to make the fine distinctions required for scheduling drugs

under the CSA from animal data. Our advisory committees appear to

prefer human data for regulatory decision making. Moreover, labeling

claims from an industry sponsor, such as a low or insignificant abuse

potential or lack of interaction with ethanol, will only be allowed if there

is clinical evidence to support the claim.

Drug combinations are a special case from the regulatory standpoint.

FDA recognizes that it is possible to add an ingredient to a dosage form

to make it less abusable. This has been formalized in the codified policy

stated in 21 CFR 300.50 (a)(2) which states that two or more drugs may

be combined in a single dosage form when one component is added to

minimize the potential for abuse of the principal ingredient. An example

of this policy was the approval of pentazocine-naloxone combination in

response to the T’s and B’s problem of the late 1970s and early 1980s

(Senay 1985).

Combinations of psychoactive drugs are studied in both preclinical and

clinical models. Although it is possible to determine whether a second

14
drug has an additive, potentiative, or antagonistic effect in preclinical

modes, the clinical models offer additional information. Moreover, the

controlled evaluation of combinations of drugs of abuse allows an

evaluation of the basis of changing abuse patterns that are observed or

reported. Thus, the study of an additive or “boosting” effect of a second

drug on the “high” produced by the first drug can be determined in an

appropriate population. For example, it was reported by several

investigators that methadone maintenance patients were abusing

benzodiazepines for the purpose of a heightened psychic effect (Woody

et al., 1975; Kleber and Gold, 1978). Preston et al. (1984) examined the

interaction of diazepam and methadone (150 percent of maintenance

dose) and 40 mg of diazepam produced an increase in opioid subjective

effects greater than that produced by either drug alone, Additionally, the

subjects more frequently identified the combinations as benzodiazepine/

barbiturate-like. Thus, it is possible to validate a new abuse pattern in a

study of the combination’s effects on subjective states.

Drug combinations of an agonist and an antagonist also yield valuable

information about the relative onsets, degree of blockade, and durations

of action of such a combination. If an analgesic were being developed for

marketing in combination with an antagonist, clinical studies in appropriate

populations would be necessary to substantiate the effect of the antagonist

on the combination with respect to both efficacy and abuse potential.

Such an approach was used by Nutt and Jasinski (1974) in determining

the effects of naloxoneonthe effects of orally and parenterally administered

methadone.

Determination of subjective effects, changes in mood states, drug liking,

drug preference, discriminative stimulus properties, and other

psychopharmacological ratings serve as the first principle for comparison

of the similarities and differences between a test drug and a standard. The

primary analysis of the rating scales takes into account the dose-response

characteristics of the test drug and the reliability of production of effects.

In this manner, one can make inferences about the intrinsic efficacy of the

drug (agonist, partial agonist, antagonist) and, in the case of opioid agonist/

antagonists, the relative efficacy of a drug for subreceptor types. Thus,

drug effects which vary with the dose of drug administered (e.g.,

butorphanol (Jasinski et al., 1975, 1976) and nalbuphine (Jasinski and

Mansky 1972)) can be determined through this type of clinical study. The

time action curve for the production of subjective effects can also be

determined from such studies.

Onset of subjective effects is another variable in the determination of

abuse potential that appears to have face validity. Subjects consistently

15
prefer diazepam to oxazepam; the reason given is the more rapid onset of

diazepam (Griffiths et al., 1984). Moreover, “pro-drugs,” such as

halazepam, also have a delayed onset (2-3 hours) and lower peak effects

than diazepam (Jaffe et al., 1983).

A third principle in the clinical evaluation of abuse potential is the degree

of overlap of the proposed therapeutic dose range and the doses which

reliably produce subjective effects. An important consideration in the

determination of abuse potential is what multiple of a standard therapeutic

dose needs to be taken to reliably produce a desired state. Obviously,

drugs which produce a desired state with a high degree of overlap of the

therapeutic dose may have a high potential for abuse. Conversely, a drug

which requires several multiples of the therapeutic dose to achieve a

desired effect maybe considered less desirable, and therefore less abusable.

This principle was employed in the decision to decontrol loperamide. It

was shown that a 60 mg dose of loperamide (30 times the usual clinical

dose) produced some noticeable drug effect in 44 percent of the subjects

(Jaffe et al., 1980). Only one of nine subjects identified the drug as

“dope.”

Another major variable in the determination of abuse potential is the

generalizability of “drug preference” in different subject populations.

For example, in the determination of the abuse potential of diazepam,

several investigators have carried out a series of studies to determine the

degree of diazepam preference to placebo in volunteers (Johanson and

Uhlenhuth 1980), young adults versus older adults (de Wit et al., 1985),

anxious volunteers (de Wit et al., 1986), anxious patients being treated for

anxiety (de Wit et al., 1987), and sedative-hypnotic abusers (Griffiths et

al., 1980). The restriction of liking to populations with prior abuse histories

suggests that the drug would have a more limited appeal than one that

produced universal liking. It must be kept in mind, however, that this

difference may be analogous to the differences in appeal between

amphetamines and opiates. Thus, differences of this type are not a

guarantee of a lack of abuse potential.

Other effects or consequences of drug intake that are amenable to study

in human populations and can be related to both the therapeutic dose

range and the dose range producing subjective effects include cognitive

function, memory, presence or absence of hallucinations, psychomotor

impairment, judgment about the level of intoxication or impairment,

interactive effects with ethanol, and adverse effects such as behavioral

disturbances and/or drug-induced psychiatric states; e.g., confusional

states, drug-induced psychosis.

16
Two pharmacological properties of many drugs of abuse, that is tolerance

and dependence, have not yet been addressed. The NDA regulations (21

CFR 314.50 (d)(5)(v)) state that an integrated summary of the studies

demonstrating effectiveness should be written. The guidelines which

accompany the regulations amplify on this section with respect to tolerance

and dependence. The guidelines state that clinical studies of chronic drug

effects should be analyzed for persistence of effectiveness, tolerance, and

withdrawal effects. It is recognized that this approach may answer

questions about the incidence of tolerance and physical dependence in

the therapeutic dose range if the study has sufficient statistical power and

the appropriate variables are being measured. Although studies of physical

dependence in post-addict populations can theoretically still be carried

out, I am unaware of any study of this type being performed since the

Addiction Research Center left Lexington, Kentucky in 1976.

A field closely related to the assessment of abuse potential in human

subjects is the development of agents to treat various types of drug

dependence. In these types of studies, measures of physical dependence

may be a primary variable. The efficacy and acceptability of induction

regimens, dose ratios of the test and standard drugs, and patient

acceptability can be studies in moderately small clinical trials. We have

called these types of trials “pharmacological efficacy studies.”

At this point, I would like to comment on an issue of internal state versus

behavior as possible measures of drug efficacy in the treatment of drug

dependence. Drug craving and drug seeking behavior are two other

important components of the definition of psychological dependence.

Although it is possible to construct scales which measure drug craving,

changes in drug craving produced by an experimental agent are insufficient

for the determination of the effectiveness to treat a drug dependence

disorder. A reduction in craving must be accompanied by a reduction in

illicit drug intake for the determination of efficacy. Operational variables

such as reduced drug intake or cessation of intake are considered more

persuasive than an effect on a more subjective variable such as craving.

Moreover, the acceptance of a less than absolute reduction in drug intake

as an acceptable efficacy variable may be limited to the opioids and

alcohol dependence. For nicotine dependence, we have determined that

a pharmacological agent should increase the quit rate.

Clinical studies of the abuse potential and dependence capacity of a new

drug can be used for the following purposes: confirmation or negation of

hypotheses developed from preclinical studies; determination of multiple

psychopharmacological variables and their relationship to/overlap with

the therapeutic dose range; determination of the onset, peak and duration

1 7
of effects in relation to the therapeutic dose range and the supra-therapeutic

dose range; determination of changes in psychopharmacological effects

as a function of dose, route of administration, and multiple doses (tolerance

or accumulation); assessment of drug combinations for alterations in

abuse potential; confirmation/refutation of purported claims in the product

labeling; assessment of efficacy of treatment of physical dependence;

assessment of statements in various sections of the product’s labeling;

and the necessity and propriety of scheduling under the CSA.

REFERENCES

Cole, J.O.; Orzack, M.H.; Beake, B.; Bird, M.; and Bar, T.Y. Assessment of the

abuse liability of buspirone in recreational sedative users. J Clin Psychiat

43:69-75, 1982.

DeWit, H.; McCracken, S.M.; Uhlenhuth, E.H.; and Johanson, C.E. Diazepam

preference in subjects seeking treatment for anxiety. In: Harris, L.S., ed.

Problems of Drug Dependence, 1986. National Institute on Drug Abuse

Research Monograph No. 76. DHEW Pub. No. (ADM) 87-1508.

Washington, D.C.: Supt. of Docs., U.S. Govt. Print. Off., 1987, pp. 248-

254.

DeWit, H.; Uhlenhuth, E.H.; Hedeker, D.; McCracken, S.G.; and Johanson, C.E.

Lack of preference for diazepam in normal volunteers. Arch Gen Psychiat

43:533-541, 1986.

DeWit, H.; Uhlenhuth, E.H.; and Johanson, C.E. Drug preference in normal

volunteers: Effects of age and time of day. Psychopharmacology 87:865-

869, 1985.

Griffith, J.D.; Jasinski. D.R.; Casten, G.P.; and McKinney, G.R. Investigation of

the abuse liability of buspirone in alcohol-dependent patients. Am J Med

80:30-35, 1986.

Griffiths, R.R.; Bigelow, G.E.; Liebson, I.; and Kaliszak, J.E. Drug preference in

humans: Double-blind choice comparison of pentobarbital, diazepam, and

placebo. J Pharmacol Exp Ther 215:649-661, 1980.

Griffiths, R.R.; Lukas, S.E.; Bradford, L.D.; Brady, J.V.; and Snell, J.D. Self

injection of barbiturates and benzodiazepines in the baboon.

Psychopharmacology 75:101-109, 1981.

Griffiths, R.R.; McLeod, D.R.; Bigelow, G.E.; Liebson, I.A.; Roache, J.D.; and

Nowowieski, P. Comparison of diazepam and oxazepam: Preference,

liking, and extent of abuse. J Pharmacol Exp Ther 229:501-508, 1984.

Holtzman, S.G. Drug discrimination studies. Drug Alcohol Depend 14:263-282,

1985.

Jaffe, J.H.; Ciraulo, D.A., Nies, A.; Dixon, R.B.; and Monroe, L. Abuse potential

of halazepam and of diazepam in patients recently treated for acute

alcohol withdrawal. Clin Pharmacol Ther 34:620-630, 1983.

1 8
Jaffe, J.H.; Kanzler, M.; and Green, J. Abuse potential of loperamide. Clin

Pharmacol Ther 28:812-819, 1980.

Jasinski, D.R.; Griffith, J.D.; Pevnick, J.S.; and Clark, S.C. Progress report on

studies from the Clinical Pharmacology Section of the Addiction Research

Center. Reported to the Committee on Problems of Drug Dependence,

1975, pp. 121-161.

Jasinski, D.R., and Mansky, P.A. Evaluation of nalbuphine for abuse potential.

Clin Pharmacol Ther 13:78-90, 1972.

Jasinski, D.R.; Pevnick, J.S.; Griffith, J.D.; Gorodetzky, C.W.; and Cone, E.J.

Progress report on studies from the Clinical Pharmacology Section of the

Addiction Research Center. Reported to the Committee on Problems of

Drug Dependence, 1976, pp. 112-148.

Jasinski, D.R., and Preston, K.L. Evaluation of tilidine for morphine-like

subjective effects and euphoria. Drug Alcohol Depend 18:273-292, 1986.

Johanson, C.E., and Uhlenhuth, E.H. Drug preference and mood in humans.

Diazepam. Psychopharmacology 71:269-273, 1980.

Kleber, H.D., and Gold, M.S. Use of psychotropic drugs in the treatment of

methadone maintained narcotic addicts. An NY Acad Sci 311:81-98,

1978.

Klotz, U.; Antonin, K.H.; and Bieck, P.R. Pharmacokinetics and plasma binding

of diazepam in man, dog, rabbit, guinea pig, and rat. J Pharmacol Exp

Ther 199:67-73, 1976.

Lukas, S.E., and Griffiths, R.R. Comparison of triazolam and diazepam selfadministration by the baboon. Pharmacologist 24:1542, 1982.

Preston, K.L.; Bigelow, G.; Bickel, W.; and Liebson, I. Drug discrimination in

human post-addicts: Agonist/antagonist opioids. In: Harris, L.S., ed.

Problems of Drug Dependence, 1987. National Institute on Drug Abuse

Research Monograph No. 81. DHHS Pub. No. (ADM) 88-1564.

Washington, DC.: Supt. of Docs., U.S. Govt. Print. Off., 1988, pp. 209-

215.

Preston, K.L.; Griffiths, R.R.; Stitzer, M.L.; Bigelow, G.E.; and Liebson, I.A.

Diazepam and methadone interactions in methadone maintenance. Clin

Pharmacol Ther 36:534-541, 1984.

Senay, E.C. Clinical experience with T’s and B’s. Drug Alcohol Depend 14:305,

1985.

Swain, H.H.; Villareal, J.E.; and Seevers, M.H. Evaluation of new compounds

for morphine-like physical dependence in the rhesus monkey. Reported to

the Committee on Problems of Drug Dependence, 1973, pp. 693.

Woods, J.H. Narcotic-reinforced responding: A rapid screening procedure.

Reported to the Committee on Problems of Drug Dependence, 1977, pp.

421-437.

Woody, G.E.; Mintz, J.; O’Hare, K.; O’Brien, C.P.; Greenstein, R.A.; and

Hargrove, E. Diazepam use by patients in a methadone clinic- how

serious a problem? J Psychedelic Drugs 7:373-379, 1975.

19
AUTHOR

Frank J. Vocci, Jr., Ph.D.

Chief, Drug Abuse Staff

Division of Neurophamacological Drug Products

Office of Drug Evaluation I

Center for Drug Evaluation and Research

Food and Drug Administration

5600 Fishers Lane

Rockville, Maryland 20857

20
CHAPTER 3

The Role of Abuse Liability Testing in

Drug Control Procedures

Howard McClain, Jr.

Frank Sapienza

INTRODUCTION

The Comprehensive Drug Abuse Prevention and Control Act, commonly

referred to as the Controlled Substances Act (CSA), was passed in 1970

to minimize the quantity of abusable substances available to those who

are likely to abuse them and to provide for the legitimate medical, scientific

and industrial needs for these substances in the United States. The Drug

Enforcement Administration (DEA) is an agency within the Department

of Justice and is primarily responsible for the administration and

enforcement of the provisions of the CSA.

DEA had an operating budget of $490 million and a criminal investigative

staff of 1,950 special agents in fiscal year (FY) 1987. DEA criminal

investigations resulted in the arrest of more than 21,000 major drug

violators and the conviction of more than 12,000 arrestees in FY 1987.

During this time period DEA removed over 350 kilograms of heroin,

35,000 kilograms of cocaine, 632,000 kilograms of marijuana and more

than 88 million dosage units of other controlled stimulants, depressants,

hallucinogens and narcotics from the illicit market. DEA also seized 682

clandestine laboratories synthesizing controlled substances. Themajority

of these laboratories were producing the central nervous system stimulants

methamphetamine or amphetamine. Assets totalling over $500 million

were also seized in FY 1987.

Both legitimately produced drugs and clandestinely manufactured

substances were included in the original list of substances controlled

under the CSA. Congress recognized that “Many of the drugs included

(under the CSA)...have a useful and legitimate medical purpose and are

necessary to maintain the health and general welfare of the American

people.” [21 U.S.C. 801(1)] Congress also found that, “The illegal

21
importation, manufacture, distribution and possession and improper use

of controlled substances have a substantial and detrimental effect on the

health and general welfare of the American people.” [21 U.S.C. 801(2)]

In consideration of the above, Congress made a determination that despite

the legitimate medical need for certain substances, controls on their

availability are necessary to protect the general health and well-being of

the American people. For this reason a “closed system” of distribution

was set up under the CSA for those who handle legitimately produced

controlled substances. Such a system is aimed at reducing the diversion

of legitimately produced pharmaceutical products into the illicit market

and into the hands of drug abusers without disrupting the legitimate

supply of controlled substances to those who have a bona fide need for

them.

One of the key features of this closed distribution system is the registration

by DEA of all manufacturers, distributors, practitioners and other persons

who handle controlled substances in their legitimate businesses and

professions (21 U.S.C. 822). Controls imposed by the CSA on DEA

registrants include security standards (21 U.S.C. 821), production quotas

(21 U.S.C. 826), order forms (21 U.S.C. 828), recordkeeping and reporting

requirements (21 U.S.C. 827), prescription refill limits (21 U.S.C. 829),

and import/export requirements (21 U.S.C. 952-959). Detailed regulations

regarding these provisions of the law are found in Title 21 of the Code of

Federal Regulations Part 1300 To End. The CSA provides civil,

administrative and criminal penalties for those who fail to comply with

these provisions of the CSA.

Currently there are more than 770,000 CSA registrants, the majority of

whom (680,000) are practitioners, who are regulated by the diversion

program at DEA. Investigations of registrants by DEA’s 263 diversion

investigators in FY 1987 resulted in more than 320 registrants surrendering

their DEA registrations, the arrest of more than 75 major violators and the

seizure of more than $2.2 million in assets.

DRUG CONTROL PROCEDURES

Both the criminal and regulatory provisions of the CSA apply only to

specifically designated chemicals. When the CSA was passed in 1970 it

included a list of controlled substances placed into one of five schedules

based upon the abuse potential, accepted medical use and safety and

physical and psychological dependence liabilities of each substance (21

U.S.C. 812). Regulatory controls and criminal penalties also vary

according to these schedules. In passing the CSA, Congress realized that

22
new clinically useful drugs with abuse potential would be developed by

the pharmaceutical industry and that enterprising clandestine laboratory

operators would also synthesize noncontrolled substances with abuse

potential solely for abuse purposes. A critical feature of the CSA is the

authority granted to agencies of the executive branch of the Federal

government to determine which substances should be controlled,

rescheduled or removed from control. Several procedures for the control

of substances which create or have the potential to create significant

abuse problems have been established under the CSA and its amendments.

Traditional scheduling pursuant to 21 U.S.C. 811(a), (b) and (c) and 2 1

U.S.C. 812, emergency scheduling [21 U.S.C. 811(h)], the controlled

substance analogue provision (21 U.S.C. 813), theschedulingofimmediate

precursors [21 U.S.C. 811 (e)] and control actions required by international

treaty obligations [21 U.S.C. 811(d)] are the specific procedures to

administratively control or decontrol substances under the CSA. The

term control also includes transferring substances between schedules [21

U.S.C. 802(5)].

The CSA provides roles for both the law enforcement and scientific and

medical communities in making drug scheduling decisions pursuant to

the traditional scheduling procedures. The Attorney General, who has

delegated his authority under this statute to the Administrator of DEA,

(28 CFR 0.100) and represents the law enforcement community, has the

ultimate authority for the decision as to whether or not a drug should be

controlled under this provision of the CSA and in which schedule. The

DEA Administrator’s decision, however, must be based on all available

evidence and can be made only after a scientific and medical evaluation

of that data is received by DEA from the Secretary of the Department of

Health and Human Services (DHHS) (formerly the Department of Health,

Education and Welfare), who is the Federal govemment’s representative

of the scientific and medical community. Recommendations of the

Secretary of DHHS regarding scientific and medical aspects of scheduling

are binding on DEA. If the Secretary of DHHS recommends that a

substance not be controlled, the DEA Administrator may not control that

substance [21 U.S.C. 811 (b)].

Traditional scheduling actions must involve “rulemaking proceedings on

the record after opportunity for a hearing.” Such rulemaking procedures

under the CSA are governed by the Administrative Procedure Act (5

U.S.C.551-559). These procedures insure that interested and affected

parties have an opportunity to express their views and to participate in the

scheduling process by commenting on proposed scheduling actions or

through participation in administrative hearings. Traditional scheduling

actions are subject to judicial review by Federal appellate courts.

23
THE NEED FOR DATA

It is readily apparent that there is a critical need for scientifically sound,

legally defensible and timely data relevant to each substance considered

for placement into one of the five schedules of the CSA. None of the

control mechanisms or criminal sanctions of the CSA are applicable to a

substance unless that substance is properly scheduled under the CSA.

Each of the procedures for controlling drugs requires gathering and

evaluating relevant data before a scheduling decision can be made.

Additionally, under each of the scheduling provisions of the CSA, DEA

has the responsibility for defending the government’s control actions in

administrative hearings, Federal district and appellate courts and criminal

proceedings. From the initial characterization of a newly encountered

substance in forensic and preclinical pharmacology laboratories to

questions about the relative physical dependence liability of an agonistantagonist analgesic in humans to testimony at a criminal trial regarding

whether an unstudied fentanyl analogue meets the criteria for a controlled

substance analogue, DEA must rely on objective, accurate, scientifically

derived and properly interpreted data.

Critical to the most efficient determination of whether a substance should

be controlled or not and in which schedule is the timeliness of abuse and

abuse liability data. This is particularly important for substances which

have potential clinical utility and are in the marketing approval process.

The Secretary of DHHS is required to submit information to DEA relevant

to the scheduling of a substance if, at the time a new drug application

(NDA) is submitted for a drug having a stimulant, depressant or

hallucinogenic effect on the central nervous system, it appears that the

substance has an abuse potential [21 U.S.C. 811(f)]. Scheduling

determinations under the CSA for newly marketed substances without a

history of actual abuse must be based on their abuse potential, their

similarity to other substances and experiences with these substances in

other countries if the substances are marketed there. The more data

available and considered prior to the marketing of such drugs, the better

the scheduling decisions. Decisions based on comprehensive data will

ultimately be less costly to government, the affected industry and the

public. Economic costs will be reduced but more importantly, the

likelihood of individual or social injury, harm and criminal behavior will

also be significantly decreased.

Inadequate data available when a drug is nearing the end of the marketing

approval process makes it difficult for governmental authorities to make

rational and timely scheduling decisions. These decisions can affect the

24
drug’s availability as a legitimate medicine. The government can adopt

a “wait and see” attitude toward the scheduling of the substance and allow

it to be initially marketed in a noncontrolled status with subsequent review.

This may result in unnecessary harm or injuries to individuals or the

community if the substance is abused and produces deleterious effects.

On the other hand, regulatory authoritiies can make a decision on whether

to control a substance or not based on incomplete or equivocal data. Such

decisions are more likely to be reversed after additional data is obtained

or challenged in lengthy and costly administrative and legal proceedings.

Such proceedings may delay the introduction of therapeutically useful

drugs to the market or result in unnecessary harm to the public until the

relevant data is developed or obtained. In extreme cases, the absence or

incorrect interpretation of abuse and dependence liability data before a

drug is introduced into the marketplace can ultimately result in the drug’s

removal from the market. Methaqualone is an example of such a worst

case scenario.

METHAQUALONE CONTROL HISTORY

Methaqualone was initially marketed in the United States in 1965 as a

noncontrolled sedative hypnotic amidst unsupported claims that it did not

produce barbiturate-type physical dependence (Inaba et al., 1973; Anon.

1966). Medical use of methaqualone in the United States increased

dramatically from 1968 totheearly 1970s (a 1500 percent increase between

1968 and 1973) when it was promoted as an effective daytime sedative

and nighttime sleep aid without the disadvantages of the barbiturates

(BNDD 1973).

Many of methaqualone’s potentially harmful effects, including its abuse

and dependence liabilities were however, reported in the literature outside

the United States. In the 1960s methaqualone was introduced into the

pharmaceutical market in many European and other countries and, in the

decade following its introduction, methaqualoneachievedmuch notoriety

as a drug of abuse (Falco 1976). Abuse of methaqualone in France, Italy,

Sweden, Argentina, Norway, Ireland and Australia was reported during

the 1960s (Falco 1976). Epidemic-like outbreaks of methaqualone abuse

were also reported in Japan, Germany and Great Britain (Falco 1976;

Madden 1966; Kato 1969; Ibe 1966).

In the United States, abuse of methaqualone was reported shortly after it

wasfirstmarketed. Bytheearly 1970s methaqualone abuse was increasing

in a manner and at a rate paralleling that of amphetamine in the 1960s

(BNDD 1973). At the same time, reports of methaqualone’s dependence

25
producing liability and the accompanying dangers of withdrawal were

becoming more prevalent both in the United States and elsewhere (Falco

1976; Inaba et al., 1973). After gathering and reviewing the relevant data

and after receiving a scheduling recommendation from the Secretary of

DHHS, in a notice published in the Federal Register on April 6, 1973,

DEA (at that time BNDD) proposed to place methaqualone into Schedule

II of the CSA (38FR9170). Interestedpartiesrequested ahearingclaiming

that while methaqualone had a high abuse potential, it did not produce

severe physical or psychological dependence, a requirement for placing

a substance into Schedule II of the CSA. A hearing was granted, evidence

heard and a final decision was reached by the DEA Administrator to place

methaqualone into Schedule II of the CSA effective October 4, 1973 (38

FR 27501).

Despite the tight controls of Schedule II, methaqualone diversion and

abuse continued and increased. Several states (notably Georgia, Florida,

New Jersey, Connecticut, Illinois, Mississippi, North Carolina and Texas)

took additional actions to prevent the use (legitimate or other) of

methaqualone (House Rpt. 1983). DEA lowered manufacturing quotas

and increased enforcement activities regarding methaqualone but

availability and abuse continued. Emergency room mentions reported by

the Drug Abuse Warning Network (DAWN) increased 154 percent during

the period 1978-1980 (Haislip 1983). Due to the widespread abuse of

methaqualone and the public health risks associated with this abuse,

Congress, in 1984, passed legislation (Public Law 98-329) whichordered

DEA to transfer methaqualone from Schedule II to Schedule I of the CSA

and ordered the Secretary of DHHS to withdraw marketing approval for

methaqualone. These two actions were completed and methaqualone

was removed from the market in the United States and placed into Schedule

I of the CSA (49 FR 33870; 49 FR 36441). Methaqualone’s widespread

availability and abuse were not abated until it was removed from the

market and placed into Schedule I of the CSA despite the most stringent

controls of the CSA for marketed products. Had all the data regarding the

hazards of methaqualone’s use and abuse been acknowledged and properly

evaluated prior to its introduction into the United States market and had

it been scheduled accordingly at that time, early controls may have

prevented the ensuing widespread availability, popularity and abuse which

when uncurtailed led to the removal of this substance from the legitimate

market.

26
EFFECTS OF CONTROL

The control status of a substance often effects how it is perceived by

health care professionals as well as the general public. As evidenced by

the methaqualone situation, perceptions of the abusability of a substance

are slow to change if that substance is first marketed as an uncontrolled

substance. Dextropropoxyphene, pentazocine and the benzodiazepines,

diazepam and chlordiazepoxide are other substances which were first

marketed as noncontrolled substances. Human experience with each of

these drugs established that they had abuse and dependence liabilities

warranting control under the CSA. Control of pentazocine,

dextropropoxyphene, diazepam and chlordiazepoxide did not immediately

alter the perception of the abuse and dependence potentials of these

substances by physicians and patients.

No pharmaceutical firm wants to market a substance without assessing

all potential forms of toxicity or adverse effects. Yet pharmaceutical

firms may market new drugs without a resolution of their abuse potential

or dependence-producing liability. Clearly, abuse potential and physical

and psychological dependence liabilities are types of adverse effects

which lead to behavioral and other toxicities. Some drugs, nonetheless

may be promoted as safe, nonaddicting or less abusable alternatives to

other controlled substances in similar therapeutic categories before

conclusive scientific evidence is available to support such claims. Other

abusable substances, such as MDMA, even though not marketed, are

claimed to be safe, without a high potential for abuse and promoted for

human use prior to the completion of even minimal preclinical studies

(Greer 1983). Extensive efforts have been made to keep some of these

substances uncontrolled. If appropriate testing, surveillance, evaluation

and interpretation of data have been completed and such claims are

warranted then no harm is done. On the other hand, however, if appropriate

testing, surveillance, evaluation and interpretation are not done or if

significant information is available but ignored, as in the cases of

methaqualone and MDMA for example, the consequences can be serious.

Control actions (which include adding to, deleting from and transferring

substances between schedules) under any of the provisions of the CSA

must follow rigid administrative and legal procedures and be predicated

upon scientifically valid and legally defensible data. The procedures and

the nature and quantity of supporting data are dependent on the type of

control action. In evaluating each substance for control under the CSA,

DEA must keep in mind its mandate to limit the availability and supply

of drugs to the illicit market without interrupting the supply of legitimate

drugs to those who have a bona fide need for them. DEA must weigh the

27
ramifications of control of a substance on those who have a legitimate

need for them against the need for restrictions on the availablity of a

substance which causes harm to the public health and safety.

There are some who claim that national and international control

(scheduling) of drugs has a negative impact on drug development and

marketing and the use of pharmacologically active agents in the practice

of medicine. There is no question that scheduling a substance under the

CSA, or one of the international conventions, imposes additional

requirements on those who handle these substances. DEA registration,

quotas, recordkeeping, security, dispensing limitations, import/export

requirements, etc., add varying levels of work and cost to manufacturers,

distributors and dispensers of controlled substances. The economic burden

is often passed to the consumer. For legitimate users of Schedule II

through V controlled drugs, however, these burdens often are no more

than minor inconveniences, particularly when compared to the benefits

derived from them in the form of decreased public health and safety risks.

For those who wish to work with Schedule I substances, especially if

human studies are to be conducted, there are more stringent requirements

(e.g., research protocol approval). In Grinspoon v. Drug Enforcement

Administration, 828 F.2d 881(1st Cir. 1987), the Court of Appeals stated

that, “From our review of the CSA, we can only conclude that Congress

had already weighed the costs and benefits of legitimate research on

dangerous drugs and has determined, in a categorical manner, that if the

three Schedule I criteria are satisfied [see 21 U.S.C. 812 (b)(1)], then the

substance should be subject to Schedule I controls even if this action will

create administrative and other burdens for researchers.” This statement

by the Court of Appeals highlights the importance of obtaining and properly

evaluating data regarding the three criteria for placing a substance into

the appropriate schedule of the CSA. Despite the stringent controls of

Schedule I, there have been several substances which have been moved

from Schedule I into Schedule II when they were approved for marketing

and the criteria for Schedule II were satisfied. Alfentanil, sufentanil and

a dronabinol product (Marinol) are recent examples (52 FR 2516; 49 FR

22074; 51 FR 17476).

Scheduling, in general, has been successful in reducing the diversion of

legitimately produced drugs to the illicit market (Jaffe 1985). One need

only look at the decrease in the abuse problem involving legitimately

produced amphetamines and barbiturates over the past years. Therapeutic

agents are brought to the market based on a determination of their safety

and efficacy by the Food and Drug Administration (FDA). If a product

is therapeutically useful and particularly if it offers an advantage over

other products indicated for the same medical condition, it will be utilized

28
whether or not it is scheduled. Codeine, the benzodiazepines,

dextropropoxyphene, oxycodone and phenobarbital are among the most

often prescribed drugs despite their abuse potential and control status

under the CSA (Anon. 1987). In 1987 alone there were more than 85

million prescriptions written for the benzodiazepines. Drug scheduling

also encourages the development of therapeutically useful substances

without abuse or dependence-producing liabilities, a worthwhile goal

regardless of CSA controls. The non-steroidal anti-inflammatory

analgesics are recent examples.

The following description of the various scheduling provisions of the

CSA attempts to delineate the kinds of data which are necessary and

useful in determining whether or not a substance should be controlled

under the CSA.

TRADITIONAL SCHEDULING

Traditional scheduling according to 21 U.S.C. 811(a-c) and 812 has been

the procedure most commonly used by DEA to add, delete or transfer

substances to, from or between the five schedules of the CSA. Unlike the

emergency scheduling and controlled substance analogue provisions of

the CSA, this procedure may be used for marketed as well as nonmarketed,

investigational and clandestinely manufactured substances. Traditional

scheduling must follow the Administrative Procedure Act regarding

rulemaking proceedings, “on the record with an opportunity for hearing.”

This allows for interested parties to have their views considered either by

comment or during an administrative hearing with judicial review available

afterwards. Traditional scheduling involves the collection of all types of

relevant data by DEA, a scientific and medical evaluation of that data by

DHHS, an independent evaluation by DEA and specific findings by DEA

regarding the relative abuse potential, accepted medical use and safety,

and physical and psychological dependence potentials of the substance

under review. Traditional scheduling actions may be initiated by DEA

on its own, at the request of DHHS or at the request of any interested

party. DEA most often initiates actions on clandestinely produced

substances found in the illicit drug traffic. DHHS requests DEA to initiate

scheduling actions for substances which are being introduced into the

marketplace. Examples of other interested parties include pharmaceutical

firms who want to change the scheduling status of one of their products

or public interest groups. Traditional scheduling actions include the

decontrol of substances, some of which were captured under the CSA

because of their derivation from opium or opium alkaloids (e.g., naloxone

and nalmefene)(39 FR 44392 and 36 FR 19116; 50 FR 45815). Other

29
non-opium derivatives (e.g., loperamide and dextrorphan) were

decontrolled when data became available to show that these substances

did not meet the criteria for control under the CSA (47 FR 49840; 41 FR

43401).

Both DEA and DHHS must consider the following eight factors listed in

21 U.S.C. 811(c) in making evaluations and scheduling recommendations

for each substance under consideration:

(1) Its actual or relative potential for abuse.

The term potential for abuse, although not specifically defined in the CSA

is found in the House Report 91-1444 and has the following meaning

when applied to a substance with a stimulant or depressant effect on the

central nervous system or hallucinogenic effect:

(a) Evidence that individuals are taking it in amounts sufficient to

create a hazard to their health or to the safety of other individuals

or the community; OR

(b) Significant diversion from legitimate channels; OR

(c) Individuals are taking it on their own initiative rather than on the

medical advice of a licensed practitioner or other qualified health

professional; OR

(d) The drug is so related in its action to a drug already listed as having

a potential for abuse to make it likely that the drug will have the

same potential for abuse, thus making it reasonable to assume that

(a), (b), and/or (c) above will occur (House Rpt. 1970).

Data regarding actual abuse, clandestine manufacture, trafficking and

diversion from legitimate channels as well as preclinical and clinical

abuse liability studies are considered under this factor. Specific

information, animal or human, whether from controlled experiments or

general human experience, which could be used to determine or predict

the abuse potential of a substance is evaluated by DEA and DHHS. It is

important to note that this factor includes the modifier “relative” when

describing abuse potential. This means that the abuse potential of a new

substance should be compared to that of a substance with a known abuse

potential. Comparisons are usually made to prototypic drugs such as

morphine (narcotic), LSD (hallucinogen), dextroamphetamine (stimulant)

or one of the barbiturates (depressant). It is essential, therefore, that

abuse liability studies contain a quantitative as well as a qualitative

component. The specific findings required by 21 U.S.C. 812 and necessary

to schedule a substance under the CSA also require a determination of

relative abuse potential.

30
Thus it is important to characterize a substance not only as having an

abuse potential but also whether its abuse potential is high, moderate or

low relative to substances with known high, moderate or low abuse

potentials. Determinations of this sort are complicated by such testing

variables as dose, route of administration, acute or chronic use, species

and set and setting, but nonetheless are necessary. Further, if a substance

behaves somewhat differently than a prototypic drug in animal tests this

may not mean that it does not have an equivalent or otherwise significant

abuse potential. For example, 3,4-methylenedioxyamphetamine (MDA),

a Schedule I substance with a known high abuse potential, is recognized

as bothd-amphetamine-like and DOM-like by rats trained to discriminate

these drugs from saline (Glennon and Young 1984). The drug, 3,4-

Methylenedioxymethamphetamine (MDMA), also in Schedule I and

having a high abuse potential, is recognized only as d-amphetamine-like

in the same tests (Glennon and Young 1984; Glennon et al, 1982). The

drug, 3,4-Methylenedioxy-N-ethylamphetamine (MDE; EVE) and 3,4-

methylenedioxy-N-hydroxyamphetamine (N-hydroxy-MDA) in rodent

drug discrimination studies with d-amphetamine and DOM as training

drugs, do not generalize to either d-amphetamine or DOM (Glennon et

al., 1988). Based on this information alone it would appear that MDE and

N-hydroxy-MDA are neither amphetamine-like stimulants nor DOMlike hallucinogens. These studies alone would further suggest that MDA,

MDMA, MDE and N-hydroxy-MDA have different abuse potentials.

However, further studies with MDMA as the training drug, show that

both MDE and N-hydroxy-MDA produce MDMA appropriate responding

(Glennon 1988). Additionally, the substances tested thus far (MDA,

MDMA and MDE) are self-administered by primates trained to selfadminister cocaine (Grifflths et al., 1976, 1988; Lamb and Griffiths 1987;

Beardsley et al., 1986). It has also been reported that in humans, MDA,

MDMA, MDE and N-hydroxy-MDA exhibit a similar

psychopharmacological profile (Braun et al., 1980). Further all four

substances are clandestinely produced, distributed and abused in

significant quantities. It appears from these and other data that all four

substances have equivalent potentials for abuse.

(2) Scientific evidence of its pharmacological effects.

The best available knowledge of the pharmacology of the substance is

considered under this factor. The CSA classifies controlled substances

as stimulants, depressants, hallucinogens and narcotics. The pharmacology

of each substance is examined to determine whether it fits one or more of

the above pharmacological categories. The more points of comparison

between the subject drug and prototypic comparison drugs that are

available the better.

31
(3) The state of current scientific knowledge regarding the substance.

Scientific data other than the pharmacology of a substance are considered

under this factor. Chemical and physical properties of a substance which

may influence whether or not or to what degree a substance may be

abused are examined. Thesyntheticpathway, including ease of synthesis,

availability of precursors, yield and expected impurities, solubility, salt

forms, isomers and medical and other uses are examples of the types of

information examined. The chemical and physical properties and the

likelihood of clandestine synthesis affect the determination of a substance’s

abuse potential. If a substance is not water soluble, it is not likely to be

injected; if the synthesis of a substance requires hard to find precursors,

elaborate equipment or complex techniques, it is less likely to be

clandestinely synthesized.

(4) Its history and current pattern of abuse.

It is important to know how a substance is abused, under what

circumstances, and the social, economic, and demographic characteristics

of the population abusing the substance. The history of the substance’s

legitimate use and abuse should also be considered. DEA must also assess

the social significance and economic impact of any control actions.

(5) The scope, duration and significance of abuse.

Whether abuse of a substance is an isolated instance in one location or a

widespread recurring phenomenon is necessary information when trying

to determine whether or not a substance should be controlled under the

CSA. The problem, or potential problem, with a substance must be large

or pervasive enough for DEA to determine that Federal control under the

CSA is warranted. All states have controlled substances laws, most of

which are patterned after the Federal CSA. States may schedule substances

in response to Federal scheduling or independent of DEA actions. DEA

must determine if control measures taken at the state level are sufficient

or if Federal intervention is warranted. DEA is not required to wait until

an abuse problem reaches large proportions or is prevalent across the

country (House Rpt. 1970). The significance of the abuse of a new

substance in a few areas may be indicative of future widespread abuse;

DEA must make this evaluation based on available data. The seriousness

and potential spread of the clandestine synthesis, distribution and abuse

of fentanyl and meperidine analogues, potent narcotic substances, were

sufficient to prompt DEA to control them under the CSA even though

they had been identified in only a few areas.

32
There have been suggestions that the control status of glutethimide be

evaluated by DEA. Glutethimide is currently in Schedule III of the CSA

and is abused in combination with codeine (“Loads,” “Fours and Dors”)

by significant populations in certain areas. A number of states with

problems have already placed glutethimide into Schedule II. DEA must

determine whether the state response is adequate or whether the problem

is widespread and significant enough for the Federal government to initiate

action. Reliable data, particularly from human experiences with

glutethimide, is critical to a wise scheduling decision.

(6) What, if any, risk there is to the public health.

The risk to the public health by a substance may manifest itself in many

ways. Abuse of drugs may affect the physical or psychological functioning

of the individual abuser; it may have disrupting effects on the abuser’s

family, friends and society in general. Abuse of certain drugs leads to

violent behavior, endangering others; abuse may be associated with

criminal activities; the effects of some drugs on psychomotor functioning,

and thus on driving, have been well documented.

Data examined under this factor range from preclinical toxicity test results

to postmarketing adverse reaction data in humans. DEA reviews data

from crime laboratory chemists, forensic toxicologists, medical examiners,

poison control centers, medical emergency rooms, drug treatment centers,

and the scientific and medical literature. It is important that adverse health

effects be reported either in the published literature or directly to the

responsible government agencies (FDA, DEA and NIDA) so that this

data is available when scheduling decisions are being made.

(7) Its psychic or physiological dependence liability.

The ability of a substance to produce physical or psychological dependence

in users is one of the more important factors for DEA (and DHHS) to

address in determining whether or not a substance should be scheduled

under the CSA. This is particularly true for substances which either are

marketed or are being investigated for marketing. In order for a substance

to be placed into Schedules II through V, it must be determined that the

substance is capable of producing a degree of physical or psychological

dependence. Physical or psychological dependence liability is one of the

three specific criteria which must be satisfied for a substance to be placed

into Schedules II through V. As evidenced by the history of methaqualone

scheduling and supported by similar experiences (with the benzodiazepines, some agonist-antagonist analgesics and other substances),

33
it is this finding which is the most difficult to establish and is often

challenged. This specific finding is not necessary for contolling substances

without accepted medical use in Schedule I but it is a factor that nonetheless,

must be considered.

Others will address the specific means for determining the physical and

psychological dependence liability of substances. The essential point,

however, is that not only must appropriate preclinical or clinical testing

and/or postmarketing surveillance be conducted but that the observations

of these studies and experiences must be evaluated carefully and

objectively.

(8) Whether the substance is an immediate precursor of a substance

already controlled.

The CSA provides for the control of immediate precursors of controlled

substances in the same or higher numbered schedule as the controlled

substance of which it is an immediate precursor [21 U.S.C. 811(e)]. The

term “immediate precursor” is defined in the CSA [21 U.S.C. 802(22)]

to mean a substance:

(A) which the Attorney General has found to be and by

regulation designated as being the principal compound

used, or produced primarily for use, in the manufacture

of a controlled substance;

(B) which is an immediate chemical intermediary used or

likely to be used in the manufacture of such controlled

substance; and

(C) the control of which is necessary to prevent, curtail,

or limit the manufacture of such controlled substance.

Administrative control of immediate precursors may proceed without

regard to the procedural requirements of 21 U.S.C. 811(a) and (b) and

without the involvement of DHHS. The control of precursors of immediate

precursors is prohibited by the CSA [21 U.S.C. 811(e)]. Substances

administratively controlled specifically because they are immediate

precursors include the phencyclidine precursors, 1-

piperidinocyclohexanecarbonitrile (PCC) and 1-phenylcyclohexylamine

(43 FR 21324) and the amphetamine/methamphetamine precursor

phenytacetone (P-2-P) (44 FR 71822).

Once these eight factors are evaluated by DHHS and DEA and a scheduling

recommendation is received from the Secretary of DHHS, the DEA

Administrator determines whether the available data regarding the

34
substance under review can support the findings required by 21 U.S.C.

812 for any of the five schedules. The findings required by 21 U.S.C.

812(a) are as follows:

(1) Schedule I.

(A) The drug or other substance has a high potential for abuse.

(B) The drug or other substance has no currently accepted medical

use in treatment in the United States.

(C) There is a lack of accepted safety for use of the drug or other

substance under medical supervision.

(2) Schedule II.

(A) The drug or other substance has a high potential for abuse.

(B) The drug or other substance has a currently accepted medical

use in treatment in the United States or a currently accepted

medical use with severe restrictions.

(C) Abuse of the drug or other substance may lead to severe

psychological or physical dependence.

(3) Schedule III.

(A The drug or other substance has a potential for abuse less than

the drugs or other substances in Schedules I and Il.

(B) The drug or other substance has a currently accepted medical

use in treatment in the United States.

(C) Abuse of the drug or other substance may lead to moderate or

low physical dependence or high psychological dependence.

(4) Schedule IV.

(A) The drug or other substance has a low potential for abuse

relative to the drugs or other substances in Schedule III.

(B) The drug or other substance has a currently accepted medical

use in treatment in the United States.

(C) Abuse of the drug or other substance may lead to limited

physical dependence or psychological dependence relative to

the drugs or other substances in Schedule III.

(5) Schedule V.

(A) The drug or other substance has a low potential for abuse

relative to the drugs or other substances in Schedule IV.

(B) The drug or other substance has a currently accepted medical

use in treatment in the United States.

(C) Abuse of the drug or other substance may lead to limited

physical dependence or psychological dependence relative to

the drugs or other substances in Schedule IV.

If the available data regarding the substance under review does not support

the required findings for control in one of the five schedules of the CSA,

that substance is not controlled at that time. The substance may remain

35
under scheduling review pending receipt of more data and a new evaluation

by DEA and DHHS may occur at a later date. If the DEA Administrator

determines that a substance meets the criteria for control in one of the five

schedules under the CSA or that it should be decontrolled or transferred

into another schedule, a proposal to do so is published in the Federal

Register. Opportunities for comments or hearings are provided. If there

are no hearing requests a final order is published in the Federal Register

and the control action becomes final. Relevant comments must be

considered by DEA and addressed in the final order. If there is a request

for a hearing on relevant matters, one is held before an Administrative

Law Judge (ALJ) who makes recommendations to the DEA Administrator.

The Administrator then considers the entire record, including the

recommendations of the ALJ, and publishes his decision as a final rule in

the Federal Register. The DEA Administrator is not required to follow

the recommendations of the ALJ. The decision of the Administrator can

be reviewed by appellate courts at the request of interested parties. The

recent cases of buprenorphine and MDMA are examples of the entire

scheduling process from initial proposal to place the substances under the

CSA through administrative hearings and appellate review. Buprenorphine

was proposed for control in Schedule V of the CSA on September 20,

1982 and the effective date of final control was February 28, 1985 (50 FR

8 104). MDMA was proposed for Schedule I control on July 27, 1984 and

the effective date of final control was March 23.1988 (53 FR 5156). In

both cases the process took several years to complete.

EMERGENCY SCHEDULING

The comprehensive Crime Control Act of 1984 (Public Law 98-473)

which became effective on October 12, 1984, amended the CSA to provide

DEA with emergency scheduling authority [21 U.S.C. 811(h)].

Specifically DEA has been given authority to place a substance into

Schedule I of the CSA for a period of one year (with a possible six month

extension) in certain situations without going through the traditional

scheduling procedure outlined above. A substance may be temporarily

controlled only if the DEA Administrator finds that such scheduling is

necessary to avoid an imminent hazard to the public safety. The emergency

scheduling provision may only be applied to substances which are not

approved for marketing or are exempted for investigational use by FDA

under the Federal Food, Drug and Cosmetic Act [21 U.S.C. 811(h)]. The

Secretary of DHHS, although not required to evaluate substances

considered for emergency control by DEA, must be notified of DEA’s

intention to invoke its emergency scheduling authority, and DEA must

36
take into consideration any comments by the Secretary, particularly those

relating to the marketing status of the substances. The emergency

scheduling authority was given to DEA in an effort to streamline the

scheduling process in response to the growing problem of controlled

substance analogues (“designer drugs”).

DEA is required to consider three of the eight factors in 21 U.S.C. 811 (c)

in making a determination as to whether a substance should be temporarily

placed into Schedule I of the CSA pursuant to the emergency scheduling

provisions. These factors are (1) the history and current pattern of abuse,

(2) the scope, duration and significance of abuse, and (3) the risk to the

public health. DEA has used its emergency scheduling authority on six

occasions since April 1985 to temporarily place 16 substances into

Schedule I. There were ten analogues of the potent narcotic analgesic

fentanyl: (1) 3-methylfentanyl (N-[3-methyl-1-(2-phenylethyl)-4-

piperidyl]-N-phenylpropanamide), (2) acetyl-alpha-methylfentanyl (N-

[1-(1-methyl-2-phenylethyl)-4-piperidyl]-N-phenylacetamide), (3) betahydroxyfentanyl (N-[1-(2-hydroxy-2-phenylethyl)-4-piperidyl]-Nphenylpropanamide), (4) beta-hydroxy-3-methylfentanyl (N-[1-(2-

hydroxy-2-phenylethyl)-3-methyl-4-piperidyl]-N-phenylpropanamide),

(5) para-fluorofentanyl (N-(4-fluorophenyl)-N-[1-(2-phenylethyl)-4-

piperidyl]propanamide), (6) thiofentanyl (N-phenyl-N-[1-(2-thienyl)

ethyl-4-piperidinyl]-propanamide), (7) 3-methylthiofentanyl (N-[(3-

methyl-1-(2-phenyl) ethyl-4-piperidyl]-N-phenylpropanamide), (8)

alpha-methylthiofentanyl (N-[1-methyl-2-(2-phenyl) ethyl-4-piperidyl]-

N-phenylpropanamide), (9) benzylfentanyl (N-[1-benzyl-4-piperidyl]-

N-phenylpropanamide) and (10) thenylfentanyl (N-[1-(2-thenyl)methyl4-piperidyl]-N-phenylpropanamide); two analogues of the narcotic

analgesic meperidine: (1) MPPP (1-methyl-4-phenyl-4-

propionoxypiperidine) and (2) PEPAP (l -(2-phenethyl)-4-phenyl-4-

acetoxypiperidine); three analogues of the hallucinogenic amphetamine

MDA: (1) MDMA (3,4-methylenedioxy-N-methylamphetamine), (2)

MDE (3,4-methylenedioxy-N-ethylamphetamine) and (3) N-hydroxyMDA (3,4-methylenedioxy-N-hydroxyamphetamine); and 4-

methylaminorex (2-amino-4-methyl-5-phenyl-2-oxazoline), an

amphetamine-like substance. These substances were emergency scheduled

based on their appearance in the illicit market, their similarity in chemical

structure to that of controlled substances and the likelihood that they

would produce pharmacological effects similar to those of prototypic

Schedule I or II substances. Often there is no biological data available

prior to the emergency control of illicitly produced and abused substances.

Therefore, information derived from structure-activity relationship

considerations plays an important role in emergency scheduling.

37
In order to keep an emergency scheduled substance in Schedule I, DEA

must initiate traditional scheduling procedures for that substance during

the one year period in which it is emergency controlled and complete the

action before the expiration of 18 months. The time limitations of

emergency scheduling underscore the need for timely abuse liability data

and the need to determine the most efficient tests to provide the data

necessary to make permanent scheduling decisions. During the one year

temporary scheduling period, DEA must acquire sufficient data to make

a determination as to whether or not the emergency scheduled substance

should remain under the CSA. Often the substances have never been

studied nor are they available for study. DEA, as soon as possible after

identifying a newly abused substance, provides for the synthesis of this

substance for analytical reference standards and biological testing. Only

then can the appropriate pharmacological and abuse liability tests be

conducted. Thus far two of the substances which were temporarily

controlled (benzylfentanyl and thenylfentanyl) were not permanently

controlled when studies did not provide evidence that they had an abuse

potential. Both of these substances were found in street samples with

other fentanyl analogues and were most likely unreacted intermediates in

the synthesis of the target fentanyl analogues. Eleven of the temporarily

controlled substances are now permanently controlled; three substances

have been proposed for permanent control and one was emergency

scheduled only recently.

CONTROLLED SUBSTANCE ANALOGUES

Despite the emergency scheduling authority granted to DEA, clandestine

laboratory operators continued to synthesize new analogues of controlled

substances faster than DEA could schedule them. The CSA was again

amended in October 1986 by enactment of the Controlled Substance

Analogue Enforcement Act as part of the Anti-Drug Abuse Act of 1986.

This law provides for controlled substance analogues to be treated as

Schedule I substances to the extent that they are intended for human

consumption (21 U.S.C. 813). A controlled substance analogue is defined

as a substance which (1) has a chemical structure substantially similar to

that of a controlled substance in Schedules I or II; (2) has a stimulant,

depressant or hallucinogenic effect on the central nervous system that is

substantially similar to or greater than that of a controlled substance in

Schedules I or II; or (3) a particular person represents or intends to have

a stimulant, depressant or hallucinogenic effect substantially similar to or

greater than that of a controlled substance in Schedules I or II [21 U.S.C.

802(32)]. The term controlled substance analogue does not include

controlled substances, drugs with approved new drug applications or

38
with respect to a particular person, any substance for which an exemption

is in effect for investigational use, for that person, under section 505 of

the Federal Food, Drug and Cosmetic Act.

This amendment to the CSA provides a means to prosecute those who

attempt to circumvent existing drug laws by manufacturing anddistributing

substances with chemical structures which are only slightly different

from those of controlled substances and which are likely to retain the

psychoactive properties of the parent compounds. There is no list of

controlled substance analogues. Expert testimony may be heard in each

criminal trial to determine if a substance meets the criteria for a controlled

substance analogue. Structure-activity relationships, although no

substitute for actual biological data, form an important element in

determining whether or not a substance is a controlled substance analogue.

Points of pharmacological similarity or dissimilarity are used whenever

they are available. If the same controlled substance analogue is encountered

in the illicit drug traffic with some frequency, DEA may initiate the

emergency or traditional scheduling provisions of the CSA, dependent

upon the type and quantity of available data. To date this provision of the

CSA has been successfully used on several occasions to convict individuals

who have manufactured or distributed analogues of controlled substances.

Unlike traditional scheduling which provides for an administrative hearing

procedure and judicial review prior to the inclusion of a substance under

the CSA, whether or not a substance is a controlled substance analogue

under the CSA is often challenged in criminal trials. Once a substance

is scheduled under the CSA there is little debate as to whether that substance

is classified as a controlled substance. Individuals who are prosecuted for

the manufacture or distribution of a controlled substance analogue can

force the prosecution to prove on each occasion to a judge and/or jury that

a substance meets the criteria for inclusion under the term controlled

substance analogue. The responsibility falls on DEA to advise attorneys

whether or not a particular substance falls within the definition of a

controlled substance analogue. Subsequently DEA staff or others may

provide expert testimony regarding these matters.

INTERNATIONAL TREATY OBLIGATIONS

The United States is a party to two international drug control treaties, the

Single Convention on Narcotic Drugs, 1961 and the Convention on

Psychotropic Substances, 1971. The Single Convention is responsible

for the international control of narcotics which, by definition, includes

marijuana and cocaine. The Psychotropic Convention is responsible for

39
the international control of stimulants, depressants and hallucinogens.

The CSA requires that DEA must control narcotic substances scheduled

under the Single Convention in the most appropriate CSA schedule to

carry out the obligations of the United States under the treaty. Scheduling

under these circumstances is done without regard to the findings and

procedures required for traditional scheduling[21 U.S.C. 811 (d)(1)]. If

a substance is internationally controlled under the Psychotropic

Convention, the CSA provides an elaborate set of procedures in accordance

with the traditional scheduling process to control that substance under the

CSA [21 U.S.C. 811 (d)(2)-(5)].

Prior to the review of substances by the World Health Organization for

possible international control, DEA, along with other Federal agencies,

industry groups and others, provide whatever data are available regarding

the abuse, abuse potential, trafficking and diversion of the substances to

be reviewed.

CONCLUSION

Human abuse liability testing is one of the means available to scientists

to attempt to assess the likelihood that a psychoactive drug will be abused.

Results of abuse liability studies coupled with other pharmacological

tests and evidence of actual abuse, clandestine manufacture, distribution

and diversion of a psychoactive substance provide DEA and DHHS with

the information necessary to make informed scheduling decisions under

the CSA. DEA urges that some form of abuse liability testing become

part of the standard premarketing testing performed on drugsacting

on the central nervous system. Such testing should be conducted as

soon as practical in the drug development process and the results made

available to the appropriate regulatory authorities. Further, DEA urges

that existing abuse or abuse liability data from other countries or

data on related substances be made available and considered prior

to the marketing of new drug products. Only if scientifically valid and

legally defensible data is generated, made available, considered and

objectively evaluated in a timely manner, can the most effective measures

be taken to ensure that the general health and welfare of the American

public is protected. Such scheduling decisions will enable DEA to limit

the availability of new abusable substances to those likely to abuse them

while providing for the legitimate need for these substances in the United

States.

40
REFERENCES

Anonymous. Quaalude and Insomnia. The Med Letter 8(8):29-30, 1966.

Anonymous. A new record: antibiotics account for 7 of the 10 top new generic

prescriptions. Pharmacy Times 32-40, April 1987.

Beardsley, P.M.; Balster, R.L.; and Harris, L.S. Self administration of

methylenedioxymethamphetamine (MDMA) by rhesus monkeys. Drug

Alcohol Depend 18:148-156, 1986.

Braun, U.; Shulgin, A.T.; and Braun, G. Study of the central nervous system

activity and analgesia of the N-substituted analogs of the amphetamine

derivative 3,4-methylenedioxyphenylisopropylamine. Arneim Forsch

30:825-830, 1980.

Bureau of Narcotics and Dangerous Drugs (BNDD). Control recommendation for

methaqualone March 1973.

Controlled Substances Act. 21 U.S.C. 801 et seq, 1970.

Falco, M. Methaqualone misuse: Foreign experience and United States drug

control policy. Int J Addict 11(4):597-610, 1976.

Glennon, R.A. Personal communication, 1988.

Glennon, R.A., and Young, R. Further investigation of the discriminative stimulus

properties of MDA. Pharmacol Biochem Behav 20:501-505, 1984.

Glennon, R.A.; Young, R.; Rosecrans, J.A. and Anderson, G.M. Discriminative

stimulus properties of MDA analogs. Biol Psychiatry 17(7):807-814,

1982.

Glennon, R.A.; Yousif, M.; and Patrick, G. Stimulus properties of 1-(3,4-

methylenedioxy)-2-aminopropane (MDA) analogs. Phar Biochem Behav

29:443-449, 1988.

Greer, G. MDMA: a new psychotropic compound and its effects in humans.

George Greer copyright, 1983.

Griffiths, R.R.; Brady, J.V.; Ator, N.A.; and Sannerud, C.A. Self-administration

of d,l-N-ethyl-3,4-methylenedioxyamphetamine hydrochloride (MDE).

manuscript in preparation, 1988.

Griffiths, R.R.; Winger, G.; Brady, J.V.; and Snell, J.D. Comparison of behavior

maintained by infusion of eight phenethylamines in baboons.

Psychopharm 50:251-258, 1976.

Haislip, G.R. Testimony before the Subcommittee on Health and the

Environment. October 3, 1983.

House of Representatives Report No. 91-1444. Comprehensive Drug Abuse

Prevention and Control Act of 1970. September 10, 1970.

House of Representatives Report No. 98-534. Rescheduling of methaqualone.

November 10, 1983.

House of Representatives Report No. 98-835. Dangerous Drug Diversion Control

Act of 1984. June 12, 1984.

Ibe, K. Acute methaqualone poisoning I. Statistics, literature survey and case

histories. Arch Toxik 21:179-198, 1965 (translated).

Inaba, D.S.; Gay, G.R.; Newmeyer, J.A.; and Whitehead, C. Methaqualone abuse.

JAMA 224(11):1505-1509, 1973.

Jaffe, J.H. Impact of scheduling on the practice of medicine and biomedical

research. Drug Alcohol Depend 14:403-418, 1985.

41
Katz, M. An epidemiological analysis of the fluctuation of drug dependence in

Japan. Int J Addict 4:591-621, 1969.

Lamb, R.J. and Griffiths, R.R. Self-injection of dl-3,4-

methylenedioxymethamphetamine (MDMA) in the baboon. Psychopharm

91:268-272, 1987.

Madden, J.S. Dependency on methaqualone hydrochloride (Melsedin). Br Med J

(corresp.) 1:676, 1966.

AUTHORS

Howard McClain, Jr.

Chief, Drug Control Section

Office of Diversion Control

Drug Enforcement Administration

1405 I Street, NW

Washington, D.C. 20537

Frank L. Sapienza

Drug Control Section

Office of Diversion Control

Drug Enforcement Administration

1405 I Street, NW

Washington, D.C. 20537

42
CHAPTER 4

Historical Perspectives on the Use of Subjective

Effects Measures in Assessing the

Abuse Potential of Drugs

Jerome H. Jaffe, M.D.

Faith K. Jaffe, B.A.

INTRODUCTION

This overview of the history of the use of subjective effects measures in

the assessment of abuse potential of drugs will touch upon two related

themes: 1) subjective responses to psychoactive drugs and the idea that

responses are linked to the likelihood of nonmedical drug use; and 2)

systematic measurement of subjective responses to drugs and the prediction

of the likelihood that a drug will be abused within the current legal meaning

of the term. We would like, at the outset, to acknowledge our debt to

several major sources. These include Terry and Pellens (1928), Corti

(1932), Beecher (1959), Holmstedt and Liljestrand (1963), Lewin (1964),

Holmstedt (1967), Caldwell (1970), Eddy (1973), Musto (1973), Brecher

(1972), Byck (1974), Jasinski (1977), Berridge and Edwards (1981),

Kramer (1980, 1981), and Siegel (1984). Hardly more than a sampling,

these sources provide fascinating historical, anecdotal, and scientific

reading relevant to the topic of this conference.

EARLY DESCRIPTIONS OF SUBJECTIVE EFFECTS OF

SOME WELL KNOWN DRUGS OF ABUSE

Descriptions of the subjective effects of many naturally occurring drugs

can be found in the earliest writings of civilization. The acute subjective

effects of wine and the effects of chronic intoxication are well described

in the Old Testament. Both the Greek and Roman pantheons had gods of

wine and drinking, and the literature of both cultures contains detailed

descriptions of drunkenness. Homer (circa 500 B.C.E.) tells us, in The

Odvssev, of the wonderful effects of the drug, nepenthes, that Helen

mixed with the wine of her guests so that they might feel less saddened

43
by the absence of Ulysses and the loss of loved ones. Although other

translators have been less specific for our purposes, Fitzgerald uses these

words:

But now it entered Helen’s mind

to drop into the wine that they were drinking

an anodyne, mild magic of forgetfulness.

Whoever drank this mixture in the wine bowl

would be incapable of tears that daythough he should lose mother and father both,

The opiate of Zeus’s daughter bore this canny power.

Homer, The Odyssey IV, 219-228.

Lewin (1964), the noted psychopharmacologist, concluded that nepenthes

could be no drug other than opium, but Moreau (1845, translation, 1973)

appears to accept the view that nepenthes was Cannabis Indica. Whatever

the drug, Homer expressed little concern that nepenthes would come to

be used on a regular basis.

The Greek historian, Herodotus (486-406 B.C.E.), may have been the

first observer to describe for us the effects of hemp (cannabis), when he

reported that the Scythians threw hemp seeds on hot rocks, inhaled the

vapors, then danced, sang, and generally seemed quite joyous. However,

Herodotus made no comment on the possibility of abuse or misuse.

Although the definition of drug abuse has varied greatly over the years

and across cultures, concern that the subjective effects of a drug would

lead to misuse are not of recent origin.

Alcohol

For much of recorded history, only in the case of alcohol was there a clear

recognition that drug use could lead to excessive drug use. Descriptions

of the effects of alcohol, as well as admonitions to use the drug in

moderation are found throughout the non-medical literature, from the

Bible through Shakespeare, as well as in the writings of 17th, 18th, and

19th century men of medicine.

Writing in the early 1800s, Benjamin Rush expressed the belief that

“ardent” (distilled) spirits were frequently associated with drunkenness.

He advised against their use (although he saw no harm in naturally

fermented drinks). Rush also provided a lively description of the subjective

44
and behavioral effects of ardent spirits during intoxication, but it is not

clear that he ever carried out a study of alcohol.

Tobacco

One of the earliest written descriptions of the effects of tobacco smoking

was provided by Bartolomeode las Casas, who accompanied the Spanish

explorers to the New World in the early 1500s. Interestingly, this is one

of the few instances in which a description of subjective effects and

concerns about repetitive use and inability to cease drug use are provided

by the same observer:

The herb which the Indians inhale is rolled up like a sort of

bundle in a dried leaf . . . They then light one end of it and

draw in the smoke at the other; the effect is a certain

drowsiness of the whole body accompanied by a species of

intoxication, in which state they declare that they no longer

feel any sense of fatigue. The . . . tobaccos, as they call them,

have been adopted also by the settlers in this region; I have

seen many Spaniards in the island of Hispaniola who used

them and who, when reproached for such a disgusting habit,

replied that they found it impossible to give it up.

Corti 1932, p. 32.

When tobacco was first introduced into Europe, its use engendered

considerable resistance and, in some cases, extreme sanctions. Almost

from the start, critics linked its subjective effects to its capacity to produce

addiction - an irresistable urge to continue to use it. One such critic was

James I of England who, in 1604, wrote with scathing scepticism about

the reported useful effects of tobacco:

. . . what greater absurdities can there bee, than to say that one

cure shall serve for divers, nay, contrarious sortes of diseases?

. . . It helpes all sorts of Agues. It makes a man sober that was

drunke. It refreshes a weary man, and yet makes a man

hungry. Being taken when they goe to bed, it makes one

sleepe soundly, and yet being taken when a man is sleepie

and drowsie, it will, as they say, awake his braine, and quicken

his understanding . . . many in this kingdome have had such

a continuall use of taking this unsavorie smoke, as now they

are not able to forbeare the same, no more than an olde

drunkard can abide to be long sober, without falling into an

45
uncurable weaknesse and evill constitution . . . to take a

custome in anything that cannot be left againe, is most

harmfull to the people of any land.

Corti 1932, pp. 79-80.

Opium

While recognition of opioid dependence probably came after recognition

of dependence on alcohol and tobacco, its remarkable persistence has

given it a special place among the addictions. It may also have so special

a place because the withdrawal syndrome associated with cessation is

dramatic, distressing and so reproducible that, once pointed out, its relation

to drug use and cessation has rarely been questioned.

In 1700, an English pharmacist, John Jones, published The Mysteries of

Opium Reveal’d. Although he recognized the danger of “long and lavish

use,” and of discontinuation after such excess, his treatise was largely

laudatory. He believed that most of the problems encountered with opium

were due to impurities. John Jones is frequently given credit for linking

the persistence of opium use to the withdrawal syndrome that follows

cessation, a link that is rarely questioned. He proposed a method of gradual

dose reduction to ease the severity of withdrawal (Kramer 1980, 1981).

In a dubious tribute to his early insight, opiate addicts continued to describe

the severity of their habit as the size of their “Jones” well past the middle

of the 20th century.

During the next several decades, the use of opium was widely

recommended and used for diverse disorders. During these years its

capacity to alter mood and elevate the spirits became generally well

known. However, according to Kramer (1981), at least one observer

expressed considerable concern. In 1763, John Awsiter, apothecary to

Greenwich Hospital wrote An Essay on the Effects of Opium Considered

as a Poison. In it he expressed the concern that if the pleasure-giving

properties of the drug were to become well known, there would be

widespread habituation, which would be a general misfortune.

Thus by the mid-18th century, two views of opium addiction had been put

forth: people continue to use the drug because of the distress of withdrawal,

or people use it repeatedly to experience its pleasure-giving effects.

By the turn of the 19th century, direct experimentation had begun to

replace clinical observation. Weber, experimenting on himself, may have

been among the first to describe the subjective effects of opium. Seturner,

46
best known for his isolation of morphine from opium in 1805, was also

the first to describe the subjective effects of morphine which he

administered to himself and his students (Kramer 1980).

Inhalants

Another milestone in the history of studying the subjective effects of

drugs is the work of Humphrey Davy. In 1800, Davy wrote a 600 page

book in which he provided detailed descriptions of the effects of nitrous

oxide, which he took himself and administered to friends, students and

colleagues. The poet, Robert Southey said, after one of Davy’s nitrous

oxide parties, that the highest possible heaven must have an atmosphere

of nitrous oxide (Brecher 1972). If it occurred to Davy that some day in

the future, some people would be concerned about the misuse of nitrous

oxide or other inhalants, he did not emphasize the point.

Cannabis

J.-J. Moreau de Tours (1845) carried out extensive research on hashish.

He took it himself and he subsequently recruited his students as subjects,

but generally he had more success in recruiting his artistic friends than his

scientific associates. Holmstedt (1967) writes that Moreau’s methodology

was meticulous and that he is justly viewed as the grandfather of

psychopharmacology. Although he did not employ placebos or doubleblind methodology, he did use a range of dosages and his descriptions of

the effects of hashish, and particularly of its euphoric effects, are still

worth reading today. He also experimented with opium andthebelladonna

alkaloids, using similar methodology and subject material. In his writing

he reviews the literature on the effects of other psychoactive drugs, quoting

extensively from Davy’s work on nitrous oxide. Moreau was familiar

with general concepts of alcohol and opium dependence, and was also

aware that addiction to hashish was common among the Moslems, and

that some chronic users developed a state of chronic apathy. Nevertheless,

he believed that cannabis might have important therapeutic actions.

He compared the risk of hashish dependence to the risk of alcoholism and

believed that in both cases the risks did not argue for prohibiting the

proper utilization of the substances (Moreau, translation 1973).

Cocaine

Freud’s review of cocaine in 1884, Uber Coca, is by any criterion a

landmark in the history of measuring the subjective effects of drugs and

47
attempting to predict their abuse potential. In the tradition of Davy,

Seturner, and Moreau, Freud carried out experiments on himself, friends,

and colleagues. He reported that cocaine produces an “exhiliration and

lasting euphoria, which does not differ in any way from the normal euphoria

of a healthy person.” He also described its effects on fatigue, hunger, and

need for sleep. Freud was well aware of the notion of drug dependence,

but expressed the view that, used in moderation, even over long periods,

cocaine would not have detrimental effects on the body. Freud speculated

that the drug might have uses in the treatment of melancholia, and citing

American work as a precedent, he advocated the use of cocaine in the

treatment of morphine addicts. He considered, but minimized, the

possibility that such treatment would merely substitute one addiction for

another, expressing the view that cocaine use would be only temporary

(see Byck 1974).

Reaction to Freud’s paper came rapidly. In a review published in 1885,

Louis Lewin, the great toxicologist, stated that cocaine was contraindicated

in morphine withdrawal. He emphasized that it is the distinct variety of

euphoria produced by opiates which the opiate user seeks and that

administering cocaine simply produces a double addiction, similar to

what is seen when opiate users drink chloroform or ether (see Caldwell

1970). This was followed in 1888, by Erlenmeyer’s scathing rebuttal to

Freud’s advocacy of cocaine, in which he reported 13 cases of iatrogenic

cocaine addiction in morphine addicts (Berridge and Edwards 1981).

Hallucinogens

No survey of research on subjective effects of drugs could omit some

mention of the work of Emil Kraepelin, or Louis Lewin or Arthur Heffter.

Kraepelin’s systematic investigations included work on the psychic effects

of morphine, alcohol, paraldehyde, ether, amyl nitrite, as well as other

drugs. Holmstedt and Liljestrand (1963) credit Kraepelin with publishing,

in 1892, the first scholarly account of the effects of drugs on mental

function.

Lewin carried out studies in a number of areas, including chronic

morphinism, in the 1870s. Both Lewin and Heffter independently studied

the subjective effects of mescaline in the 1890s.

Hefftercarriedout heroic studies using himself as a subject. He is described

as a stolid, somewhat boring lecturer. It is not too surprising that he

experienced little of the mystery that others have described in connection

48
with these agents. His view of abuse potential of hallucinogens is summed

as follows:

...Weir Mitchell and Ellis believe that peyote (mescal) will

also become popular amongst cultured people as an

intoxicating drug. I think that this is unlikely because the

results which I obtained on myself show that the side-effects

are so pronounced that they considerably spoil the appreciation

of the beautiful visual images.

Holmstedt and Liljestrand, 1963.

Amphetamines

Until about 1932, when amphetamine (synthesizedin 1877) was introduced

into medicine as a drug for treatment of nasal congestion, cocaine occupied

a unique place as an abusable stimulant. By 1935, the utility of

amphetamines in narcolepsy, as well as some of its CNS stimulant effects,

had been recognized. By the early 1940s, its euphorigenic and mood

altering effects were also well recognized. Nathanson (1937) carried out

a study of amphetamine remarkable for its sophistication. It involved 40

outpatients who were “suffering” from nervous exhaustion and 55 young

normal individuals who were given 20 mg of amphetamine and 25

comparable normals who were given placebo. The study involved the use

of self-rating questionnaires. The most frequent effect in normal subjects

wasasenseof well-beingandexhilaration, lessened fatigue, andincreased

talkativeness, energy and capacity for work. Those who got placebo did

not report such effects. Nathanson believed that the drug would have

wide therapeutic utility and might also be useful in preparing an individual

for unusual expenditures of physical or mental energy. He cautioned that

wider and longer experience is needed to consider the question of

habituation and tolerance.

SUBJECTIVE EFFECTS AND THE EVOLUTION OF

FORMAL SCREENING FOR ABUSE POTENTIAL

Prior to the turn of the 20th century, the problem of addiction to opiates,

cocaine, alcohol, and certain sedatives was well recognized, but in most

countries there were no specific statutes regulating availability of such

49
drugs. Assessments of drugs were generally informal, designed todevelop

information for use by the profession and the public. The passage of

international treaties controlling opium and cocaine, and subsequent

passage of the Harrison Act in the United States, did not result in any

immediate change in that situation. However, the development of formal

programs for assessing the effects of drugs in order to predict their abuse

potential, was a by-product of a deliberate effort to produce non-addictive

substitutes for the various uses of morphine and related opiates. The

effort was based on the assumption that oral codeine had a lower abuse

liability than morphine, but was nevertheless a useful analgesic. This

suggested that analgesic actions could be separated from the actions

linked to abuse and dependence. In 1929, a committee of the National

Academy of Science National Research Council, the Committee on Drug

Addiction, formulated a strategy aimed at the development of nonaddicting

therapeutic substitutes for morphine. As part of the strategy, two research

units were formed, a chemical unit at the University of Virginia, and a

pharmacological unit at the University of Michigan. These units worked

in collaboration with a clinical research unit established within the United

States Public Health Service, which in 1929 had been given responsibility

for care of federal prisoners who were opiate addicts. A key figure in the

development of the strategy and workings of the committee was Nathan

Eddy. This program resulted in the development of a number of chemical

entities which then needed to be evaluated by methods that were themselves

still evolving.

As an opiate derivative, dihydromorphinone (Dilaudid) was controlled

by federal laws at the time of its clinical introduction into the United

States. But, it was reported to be a nonaddicting substitute for morphine.

Eddy, in 1933, and King and coworkers, in 1935, reported that it produced

and sustained physical dependence and had, therefore, addiction liability.

Jasinski (1977) states that these were the “first evaluations of an agent

primarily for the purpose of providing information important to the public

health.” Desomorphine, which had been prepared by Small at the chemical

unit at the University of Virginia as part of the National Academy of

Sciences program, did not produce physical dependence in monkeys (at

least at the dosages used). Himmelsbach, however, demonstrated that the

drug had morphinelike actions in morphine-dependent addicts and in

nonaddict patients with chronic pain. On the basis of these findings, the

Committee on Drug Addiction recommended, in 1935, that production or

sale of desomorphine be prohibited in the United States. According to

Jasinski (1977), this was the first instance in which “addiction liability”

was a factor in the decision for narcotics control. However, it is worth

50
noting that the conclusions about dihydromorphinone and desomorphine

were based exclusivelyon their capacity to suppress physical dependence,

and not on their subjective or euphorigenic effects.

Meperidine, a chemical moeity unrelated to the opiate molecule, was

initially synthesized in Germany and discovered to have analgesic actions.

It was believed to have no addiction liability and was introduced into the

United States in 1940. However, Himmelsbach (1942, 1943) reported

that meperidine had an addiction liability similar to that of morphine.

Since it was not an opiate, new legislation was required to include

meperidine and its derivatives under the legal controls which applied to

the opiates. Himmelsbach’s conclusions about meperidine (Demerol)

did not rely upon an assessment of its subjective effects, but, as with

desomorphine, were based primarily on its capacity to suppress physical

dependence. He did note in passing that patients “liked the effects of

Demerol [which] were described as being like ‘Nembutol or Cocaine”’

(Himmelsbach 1943, p.6).

Although Himmelsbach tended to ignore those drug responses that could

not be “measured,” other researchers continued not only to take note of

subjective responses, but to draw reasonably informed and sensible

inferences from those responses. However, the methodology for such

assessments had not yet reached current levels of sophistication. In a

classic paper entitled, “A study of the analgesia, subjective depression

and euphoria produced by morphine, heroine, dilaudid, and codeine in

the normal human subject,” Seevers and Pfeiffer (1936) gave detailed

descriptions of their method for measuring analgesic thresholds using

von Frey hairs, but their method for assessing subjective effects presented

in its entirety is as follows: “During and following the experiment, the

subject was asked to describe the subjective sensations resulting from the

action of the drug.” It should be noted, however, that the overall

methodology of the study was otherwise relatively modem, and although

placebos were not used, they did employ double-blind methodology and

several drug dose levels.

Seevers and Pfeiffer (1936) reported that not one of their eight subjects

“chosen for maturity and mental stability” because of the “remote

possibility of addiction” evinced the slightest desire for repetition, rather

“a hearty dislike for the procedure was generally expressed.”

Although Seevers’ and Pfeiffer’s subjects did not wish to repeat the

experience, neither did they necessarily find the effects of the drugs

51
unpleasant. When asked to report on euphoria (defined as akin to the

stimulation ordinarily present during the first stages of alcohol

intoxication), their subjects reported that heroin, morphine and dilaudid,

in that order, produced the most pleasurable sensations, while very little

euphoria was produced by codeine. Heroin was by far the most pleasant,

and also produced the fewest adverse side effects. Seevers and Pfeiffer

(1936) observed that “these very qualities which accord it first place,

likewise render it most dangerous from the standpoint of addiction, since

its action is rapid and intense, side actions are few, and euphoria often

supplants subjective depression” (Seevers and Pfeiffer 1936, p. 184).

(Curiously, these subjects, in contrast to confirmed addicts, reported that

euphoria was less pronounced after intravenous than after subcutaneous

administration, a difference which Seevers and Pfeiffer attributed to the

effects of addiction and tolerance.)

These statements, which asserted that the addictive potential of opiates

was directly related to their euphorigenic effects, were paraphrased in

several standard pharmacology textbooks well into the 1950s (Lasagna

et al., 1955; von Felsinger et al., 1955) and probably contributed to the

widespread practice of underprescribing opiates for pain.

The following year, Seevers et al. (1937) reported on the subjective effects

of three commonly used anesthetic gases. A significant finding was

described as follows:

. . . In nearly every instance, and with all agents, the subjects

described what was termed the initial “jolt” which occurred

one to three minutes after the first inhalation of concentrations

high enough to produce significant analgesia. The

promptness of occurrence of this intense subjective reaction

following the use of these three agents is (a) cyclopropane,

(b) nitrous oxide, (c) ethylene. Some subjects interpreted

the sensation as an impending loss of consciousness and

others in terms of euphoria. The maximum sensation usually

lasts ten seconds to one minute and gradually becomes less

pronounced, although the same concentration of the gas is

continuously being inhaled. The time of this reaction did not

in any instance coincide with the period of maximum

analgesia. It is possible that the reaction is coincident with

the time at which a high concentration of the agent first

penetrates the nerve cell. It is interesting that the same general

52
type of reaction occurs after the intravenous injection of the

opiates and the time relationships are approximately the

same.

Seevers et al., 1937, p. 296.

It is, perhaps, an index of the relatively low level of public concern with

drug abuse during this period that, despite these observations, there is no

comment made on the possibility that these gases might someday be

misused.

Up to this point, the process of assessing abuse potential continued to be

based largely on Himmelsbach’s original perspective that the habitforming properties of opiates were due to and best predicted by their

capacity to produce physical dependence. Not only did Himmelsbach

give little weight to the subjective effects produced by the drugs being

evaluated, but in his evaluation of physical dependence even subjective

reports were largely ignored and only “measurable signs” were included

in his method of rating the intensity of physical dependence. The major

techniques used by the Lexington group well into the late 1940s, were

direct induction of physical dependence, and substitution tests using either

multiple or single doses of the test substance in subjects already dependent

on morphine.

Some measure of the relative importance given at that time to the

assessment of subjective effects may be inferred from the contents of a

1945 paper by Wikler, Goodell and Wolff titled, “The effects of analgesics

on sensations other than pain.” The drugs given included morphine,

codeine, alcohol, aspirin, and a barbiturate; the study measured smell,

hearing, touch, and vibration, but there was not a single comment on the

subjective effects produced by any of the five drugs studied. A 1946

paper from the Lexington group (Williams et al., 1946) on marijuana and

pyrahexyl compound contained a detailed description of effects on

temperature, pulse, caloric intake, sleep, EEG, memory and even time

estimation, but there were only three lines noting that exhilaration and

euphoria were followed by general lassitude. The study used an observer’s

behavioral rating scale in which one dimension was mood; no mention is

made of scales with which subjects could systematically report their own

moods and feelings.

It was only after Isbell assumed leadership of the clinical research unit at

Lexington that an effort was made to systematically measure some

reflection of the subjective effects produced by the drugs being evaluated

53
by the laboratory. In 1947, Isbell and coworkers studied the addiction

potential of methadone, another synthetic analgesic first developed in

Germany, which had been introduced into the United States in 1945. In

their evaluation of the effects of single doses of methadone, Isbell and

coworkers (1948) concluded that it induced morphine-like physical

dependence and suppressed morphine withdrawal, and that methadone

was, therefore, a drug that should be controlled under narcotics laws.

However, in these studies, they also concluded that it had euphorigenic

effects similar to those of morphine, but the method by which they drew

this inference was rather informal.

In a 1948 paper, Isbell stated that the pleasurable effects of drugs lead to

their repeated use even before the development of physical dependence,

and that detecting andmeasuringeuphoria was a critical aspect of assessing

addiction liablity. He then described some of the behaviors which later

became part of the standard method at Lexington for assessing opioidlike

euphorigenic actions of drugs:

...The method used is simple: Single doses of the drug under

test are administered to former morphine addicts, and the

subjects are unobtrusively watched for a period of 6h or

more by specially trained observers. For our purposes,

euphoria is defined as a series of effects similar to those

produced by morphine. These effects are: increased

talkativeness, boasting, greater ease in the experimental

situation, expression of satisfaction with the effects of the

drug, requests for increased doses of the drug, increased

motor activity, and, with larger doses, slurring of speech,

motor ataxia, and evidence of marked sedation. As many

experiments are done as are necessary to reach a clear-cut

conclusion. The observations are controlled by administering

30 mg of morphine to the same subjects on other occasions.

Initially, small subcutaneous doses of the drug under test are

used, and if no untoward toxic effects are observed, the

dosage is increased progressively in subsequent experiments

until evidence of euphoria, roughly equivalent to that

produced by 30 mg of morphine, is detected, or, if no evidence

of euphoria is detected, the dosage is elevated until further

increases would be regarded as dangerous. If euphoria is

detected, blind experiments are arranged in which neither

54
the subject nor the observer are aware whether the drug

given was morphine or the compound under test. Finally,

various doses of the drug are administered intravenously.

Isbell 1948.

At this time, therefore, the emphasis remained on behaviors that observers

could measure, rather than on systematic methods for obtaining reports

from the subjects themselves.

Up to this point, the work on subjective effects of drugs had focused

largely on opiate-like drugs. It is important to recognize that under the

existing United States legislationonly opiates and their surrogates, cocaine,

and (since 1937) cannabis were subject to special regulations. However,

it was clearly recognized that these were not the only categories of drugs

subject to abuse, or associated with physical dependence. Habitual use

and withdrawal syndromes associated with barbiturate use were well

recognized in the German medical literature in the 1920s, but the problem

was less well appreciated in the American literature. In the introduction

to their review, “Addiction to Analgesics and Barbiturates,” Isbell and

Fraser (1950) were able to state that a review of the literature on sedative

dependence had not previously been done. Similarly, reports of

amphetamine addiction began to appear in the medical literature in the

1940s.

At this time, the Food and Drug Administration (FDA) could require that

information about the habit-forming properties of drugs be included in

package inserts, but this fell far short of formal control of sale and

manufacture. It was not until the passage of the Drug Control Amendments

of 1965, that any governmental agency could regulate the manner in

which sedatives, anxiolytics, stimulants (other than cocaine), and

hallucinogens could be manufactured, sold or dispensed.

THE BLOSSOMINGS OF METHODOLOGY

The early moves by the Lexington group toward systematic assessment

of subjective effects came just at the beginning of what we now recognize

as the great flowering of psychopharmacological research. We would not

wish to characterize that period as Golden Age, since it might imply that

the present era was not even more vigorous and vibrant; but, it would not

be inappropriate to point to the years between 1950 and 1970 as the

tumultuous adolescence that leads into a mature and productive adulthood.

55
A number of confluent streams nourished a growing interest in methods

for assessing subjective effects. Not the least of these was the number of

new psychoactive drugs available for research and being introduced into

clinical medicine (which, in those years, were often interchangeable

concepts). The agents included new psychoactive drugs: nonbarbiturate

sedatives, analgesic agents, stimulants, as well as the more exotic LSD

and related compounds. By 1954, this stream had been joined by new

drugs for treating psychiatric disorders: chlorpromazine, reserpine and

meprobamate. In 1955, Himwich gave an address to the Society for

Biologic Psychiatry in which he stated that his title, Prospects in

Psvchopharmacology, could not have been chosen three years previously

because the word did not exist. [Actually, Macht had used the term

“psychopharmacology” in 1920, as had Thorner in 1935 (Caldwell 1970).]

Still another major contribution to the evolution of measurement was the

work of Beecher and his colleagues at Harvard who deliberately set out

to develop a laboratory for the measurement of subjective effects, for

which they received a small grant from the Committee on Addictions in

1948. In a 1952 review, Beecher laid out the important principles for the

systematic assessment of subjective effects; these included the use of the

double-blind technique, placebo controls, randomization of drug

presentation, appropriate choice of subjects (i.e., patients with illness or

normal subjects), appropriate dosage levels, and sensitive methods that

could detect drug action and increments in dose.

This was a time of rapid transition in the assessment of the abuse liability

of drugs. In their 1950 review, Isbell and Fraser pointed out that definitions

of addiction that equate it with physical dependence or make dependence

the central feature are undesirable. They clearly endorsed Kolb’s

perspective that the critical issue is the capacity of the drug to produce

pleasurable effects in a susceptible individual. While not disavowing the

emphasis that Himmelsbach had placed on testing for physical dependence

and on using only objective measures (i.e., ignoring what the subjects

reported), the views of Isbell and Fraser were a further reaffirmation of

Isbell’s interest in euphoria expressed in his papers of 1947 and 1948.

But the assessment methods at Lexington did not immediately catch up

with the shifting philosophical orientation. Fraser and Isbell wrote a paper

comparing the reactions of postaddicts and normals to morphine. It

described effectsonpupils, body temperature and respiration, but contained

not a word on subjective effects. (Another evidence of bygone days: the

paper was submitted to the Journal of Phamacology and Experimental

Therapeutics on May 19, 1952 and appeared in August 1952.) If another

paper was published on the subjective experiences of these subjects, we

were unable to find it.

56
One of the classic studies carried out by the Harvard group compared the

effects of morphine, heroin, and amphetamine in normal volunteers,

postaddicts at Lexington, and chronically ill patients (Lasagna et al.,

1955; von Felsinger et al., 1955). The study is noteworthy for a number

of findings, but two stand out. First, in contrast to the “postaddicts” who

liked the effects of morphine and heroin (experienced euphoria), the

majority of normal volunteers found those drugs dysphoric. The normal

volunteers did experience mood elevation and pleasant feelings after

amphetamine. Second, this appears to have been the first study that used

self-rating scales to measure the subjective effects of opiate drugs. The

idea that the subjective response to a drug depended on the history and

personality of the individual had been postulated and described previously

by a number of workers (e.g., Kolb 1925; Lindemann and Malamud

1932), but not with the kind of supporting data found in these classic

papers.

It is not clear if or why there was reluctance to utilize in some systematic

way the verbal reports of the subjects at Lexington, but there was apparently

an exchange of correspondence on the question, in 1956, between Beecher

and Wikler. Beecher comments,

There is a very great and understandable desire on the part

of many people for objective indicators of subjective

phenomena. Wikler hopes to find such in operational devices

...[W]ithout intheleast minimizing the importance of work

in the areas mentioned, one wonders whether it is likely that

the elaborate electronic methods referred to, however, will

be any more helpful in measuring and understanding

subjective responses than in the tail flick of a rat. . . . A

cooperative statement by the subject must take first rank as

an indication of the existence of a subjective response or of

change in it.

Beecher 1959, p. 57.

However, in 1956, Isbell and colleagues at the Addiction Research Center

(ARC) published a paper on LSD-25 which made use of psychiatric

interviews and of a questionnaire that had been developed by Abramson

and coworkers the previous year. In 1957, Kometsky and his coworkers

used this questionnaire to measure subjective effects of four drugs,

including LSD and meperidine, in normal volunteers. However, these

measures were not utilized in assessing dependence or abuse liability.

57
In 1961, a paper by Fraser and coworkers appeared that, as far as we can

tell, represented the first use of the “single dose questionnaire for opiates,”

designed to evaluate quantitatively the attitude of opiate addicts toward

opiate drugs and to find out what symptoms were experienced. The

questionnaire had items to be completed by the observers (covering the

behaviors mentioned by Isbell in 1948), but subjects were also asked,

“Do you feel the medicine?”; to select from a list which drug they thought

the test drug was most like; which of a number of sensations, (e.g., drive,

sleepy, relaxed), they felt; and how much they liked the drug (Fraser et

al., 1961).

By 1963, Hill and coworkers developed and published the Addiction

Research Center Inventory (ARCI) containing several scales that were

empirically demonstrated to be sensitive to the effects of a number of

abused and non-abused drugs.

In recognizing the importance of subjective (euphorigenic) effects of

drugs of abuse, in contrast to Himmelsbach’s emphasis on physical

dependence and measurable signs, Isbell was “rediscovering” the views

of Lawrence Kolb, who had pioneered the U.S. Public Health Service’s

work in studying addicts. In 1925, Kolb, then at the U.S. Public Health

Service Hygienic Laboratory in Washington, D.C. wrote:

. . . in referring to the mental pleasure of opium, a distinction

should be made between the pleasure that is merely reflex

following relief from anxiety and pain and the pleasure that

results from raising an individual above his usual emotional

plane... normal as well as abnormal persons may receive the

first kind of pleasure, while only in rare instances, if at all,

does any one except the emotionally unstable, the

psychopath, or the neurotic receive the latter. The first, . . .

may be termed negative pleasure; the second a relief from

conditions that are more or less permanent or fundamental,

may be termed positive pleasure. In persons who at first

receive positive pleasure from an opiate and because of it

continue the use of the drug until it becomes a physical

necessity, the degree of the feeling wanes as more and more

of the drug becomes necessary to satisfy the craving of

physical addiction and to maintain comfort. It is the hope of

reviving the pleasure in its original intensity that impels

some psychopathic addicts gradually to increase the dose or

58
to inject morphine or heroin directly into their veins . . .

Amounts that at first gave unusual effects are then necessary

to maintain what to an addict is normal functioning and to

ward off discomfort . . . This is a poor substitute for the sense

of ease and relief that the drug at first gave from the conflicts

and tensions that are fundamental with the psychopath. It

thus happens that the drug, taken in the beginning because

of its power to raise an inferior individual above his normal

level, must be taken in the end to keep him from sinking

below it and to relieve conditions that the drug itself has

produced.

Kolb, 1925, pg. 699.

Kolb was not certain whether opiates could induce euphoria in normal

individuals who did not have some special psychic vulnerability. He was

astute in recording the experiences of opiate addicts and it is remarkable

how closely these experiences are reflected in items that are now routinely

used in scales that measure the subjective effects of opioids:

The expressions that addicts make use of in describing their

sensations illustrate better than anything else the mental

pleasure that opium gives abnormal persons. At the same

time they show the neurotic basis of addiction by indicating

emotional conflicts or feelings of inadequacy, the relief from

which is expressed as pleasure. The following are some of

the common statements made:

“It makes my troubles roll off my mind.”

“I do not have a care in the world.”

“It is exhilirating and soothing.”

“You do not care for anything and you feel happy.”

“You have a contented feeling and nothing worries you.”

“It stimulates you and makes you forget, so you don’t care

about anything.”

“It makes you drowsy and feel normal.”

“It causes exhiliration and a feeling of comfort.”

“A deadening, pleasurable effect.”

59
There is a remarkable similarity between these statements and the items

which make up the MBG scale of the ARCI.

Kolb went on to state:

In addition to the mental pleasure produced by opium, some

addicts receive a pleasurable physical thrill of short duration

and varying intensity immediately following an injection of

morphine or heroin . . . Most of them describe it as a feeling

of warmth that quickly spreads through the abdomen

following an injection . . . Striving for a repetition of it naturally

leads to larger doses.

Kolb, 1925, p. 702.

It is worth noting that Kolb’s 1925 descriptions of the subjective effects

of cocaine were as perceptive as his descriptions of the effects of opioids.

Still other influences on methodology were major technical advances in

behavioral pharmacology. In the early 1960s Weeks, Schuster and

Thompson; and Yanagita, Deneau and Seevers (see Schuster and

Thompson 1969) independently developed techniques that allowed

animals to self-administer drugs by the intravenous route. It was rather

quickly shown that animals would self-administer opioids as well as

other drugs at doses that were unlikely to be associated with significant

physical dependence. Such findings further served to shift attention from

measuring withdrawal syndromes to understanding the reinforcing effects

of drugs and the relationship of these effects to abuse potential.

At this juncture, the early 1960s, events outside of science also began to

influence the evolution of methodology. The United States was beginning

to recognize that the non-medical use of drugs was becoming more

widespread, and that the drugs being used were more diverse than at any

time previously. There was widespread concern with growing use of

marijuana, new concern with the much publicized use of LSD and

psilocybin, as well as a belated recognition of the abuse of amphetamines

and of barbiturates and non-barbiturate sedatives. Many states had

regulated barbiturates, but without authority to control manufacture or

shipments, widespread misuse persisted. These concerns led to the passage

of the Drug Control Amendments of 1965 which gave FDA the authority

to control the use of barbiturates, amphetamines and any drugs that the

Secretary of Health, Education and Welfare (HEW) designates as subject

to abuse (aimed at hallucinogens). However, even after the passage of

these amendments, which by legislation specifically included the

barbiturates and amphetamines, there remained considerable controversy

60
about which of the newer non-barbiturate sedatives ought to be regulated

and what evidence of abuse potential was sufficient to justify regulation.

Pharmaceutical firms that produced drugs like meprobamate and diazepam

engaged in extended litigation to maintain an uncontrolled status for their

products.

The Drug Control Amendments were short-lived. In response to the

continued increase in the incidence of illicit drug use, and associated

crime and social deviance, the federal government proposed new

legislation. It was aimed at reducing the seeming chaos of interminable

litigation over regulation of specific drugs under the Drug Control

Amendments and the administrative confusion inherent in having two

departments responsible for controlling drugs of abuse (HEW for

barbiturates and amphetamines and hallucinogens and Justice for control

of opiates, cocaine and cannabis). The new law, the Controlled Substances

Act of 1970, shifted all enforcement to the Justice Department. However,

the law made provision for scientific input on the issue of which drugs

would require control, and, in an important precedent, recognized different

degrees of risk which required different degrees of control. It also attempted

to lay out specific objectives and criteria for judging the degree of risk of

abuse. The assumption underlying this Act was that it was possible to

obtain through research the kind of information needed to decide on what

level of control was appropriate for any given psychoactive agent.

The legislation provided a further impetus to the development of

methodology to assess the “abuse liability” of new psychoactive agents.

For the most part, the core approach of most researchers was to determine

the degree to which a new compound had properties comparable to one

which was already judged to require control, i.e., was already included in

one of the five schedules of the Controlled Substances Act. However, the

legislation did not clarify in any way how different aspects of a drug’s

action should be weighed in reaching an overall judgement on the degree

of abuse liability or addiction potential of a given drug.

The problem of amphetamine illustrates this point. Cases described as

addiction to amphetamines began appearing in the U.S. medical literature

as early as 1940. Yet, in a classic review of the amphetamines in 1966,

Kalant could still write:

Although a great deal has been written about whether or not

amphetamines are addictive drugs, there is as yet no

consensus on this very important point. This has been due

partly to lack of well-documented evidence, but to a far

greater extent to the disagreement over what constitutes

61
addiction. The crux of the disagreement has been whether or

not amphetimines(sic), when consumed chronically, produce

physical dependence as manifested by the presence of clearcut withdrawal symptoms and, therefore, strong craving.

Thus, authors who have based their judgment almost

exclusively on the question of physical dependence have

argued that amphetamines do not produce addiction. Other

authors, who have attached greater importance to such factors

as compulsion to continue to take the drugs, development of

tolerance, and harmful effects, have drawn the opposite

conclusion . . . in the pertinent literature value judgments are

clearly implicit, to the effect that addiction, if proven, would

condemn these drugs as bad, whereas a verdict of habituation,

dependence, or abuse would largely exonerate the drugs but

condemn the habitues, dependents, or abusers. The

discussion therefore seems to hinge on the identity of the

culprit: the drug or its user . . .

Kalant 1966, p. 77.

Kalant was, in one sense, restating the arguments of Isbell and Fraser

(1950).

Despite knowledge of what we now refer to as the post World War II

epidemic of amphetamine addiction in Japan, many workers continued

to make a clear-cut withdrawal syndrome the sine qua non for defining

addiction. Again, we see the ghost of John Jones arguing with his

countryman and fellow pharmacist, John Awsiter. There appears to be

something exceedingly seductive about the very idea of identifying some

measurable withdrawal syndrome and attributing to this syndrome the

entire responsibility for the dependence process, (or at least the bulk of

the responsibility). Implicit in this seductive idea is the perspective that

drugs that induce only subjective changes, but not physical dependence,

represent lesser hazards for those who use them and for society as a

whole.

The same issues can be identified when we consider the history of assessing

the abuse liability of sedatives and anxiolytics. The initial studies of

barbiturate drugs by Isbell et al. (1950) and Fraser et al. (1954) focused

on the effects of chronic intoxication and the barbiturate withdrawal

syndrome. The descriptions of the effects of chronic intoxication remain

classics, but it was not until a decade later that Martin et al. (1962, 1974)

used questionnaires to demonstrate that non-tolerant opiate addicts “liked”

62
the effects of pentobarbital. But studies also showed that not all varieties

of liking are the same; i.e., the subjective effects of barbiturates although

“liked” were distinct from those of opiates and were distinct from the

subjective effects of LSD and cannabis-like drugs as well (Hill et al.,

1963; Haertzen 1966). Studies at the ARC also showed that phenobarbital,

which was known to induce physical dependence and suppress withdrawal

from short-acting barbiturates was far less potent than pentobarbital in

inducing euphoria, as measured by the ARCI.

The relatively low abuse potential of phenobarbital, which had been

available for more than 60 years, led a panel of experts to conclude, in

1969, that direct addiction studies alone could not predict abuse potential,

but that other tests, such as the capacity of single doses to induce euphoria,

might be needed (Fraser and Jasinski 1977). Such assessment would

presumably result in a judgement that shorter-acting barbiturates, such as

pentobarbital, which induces both acute subjective effects and physical

dependence, require more regulation than phenobarbital, which is

associated primarily with physical dependence.

However reasonable these principles may be, problems have arisen in

their application to the regulation of the more than twenty available

benzodiazepine congeners, agents which differ widely in terms of their

acute subjective effects and pharmacokinetic properties (and, therefore,

the onset and intensity of their withdrawal syndromes). Given their

currency, these issues are probably best excluded from an historical review.

EUPHORIA’S PRIMACY DOUBTED

The notion that euphorigenic effects can usefully predict abuse liability,

has been criticized by some workers because it has not explained enough

and because it has diverted attention from other important scientific

questions. These criticisms have been succinctly expressed by Peter Dews.

. . . it was supposed that the prediction of addiction liability

was essentially equivalent to prediction of euphorigenic

power. As with most self-evident ideas, the mere matter of

there being essentially no evidence in favor of it, and much

against it, had little effect on its acceptance. Addicts did not

talk much of exquisite pleasure, even when words were put

in their mouths; mostly they talk of no more than a transient

63
thrill. The types of effects caused by heroin, alcohol,

amphetamines, and tobacco smoking are so grossly different

that no one has ever identified a common factor in the effects

of all the drugs, euphoria, that causes them all to be abused.

The effects of tobacco smoking are ordinarily so subtle that

a CNS effect is not detectable, yet smoking is as compulsive

a habit as any.

The euphoria notion has been disposed of many times and

few here today would subscribe explicitly to a simple

euphoria theory of drug abuse. We know too much about the

enormous role of external circumstances in determining

whether an individual will take drugs or not, and if so, which

drugs, for us to try to pin all the responsibility for abuse on

an intrinsic euphoriant property of the drug...

Dews 1977, p.75.

THE STRUGGLE UNRESOLVED

The ghost of John Jones may still haunt the dwelling places of government

and academia. Let us consider the case of buprenorphine. This is a

fascinating drug derived from thebaine and closely resembling etorphine,

one of the most potent opioids known. Buprenorphine is a potent analgesic.

At early stages of testing, it appeared to produce little physical dependence

in rats and monkeys; it did so in the dog; and it also suppressed morphine

abstinence. It is self-administered by animals trained to inject opioids.

Properly given, it can substitute for morphine in subjects maintained on

low doses of morphine, and it can induce morphine-like euphoria. Despite

these properties, buprenorphiie has been available in a number of countries

for several years with no controls other than the need for a physician’s

prescription. But for an appeal by the Drug Enforcement Administration

(DEA), the drug would have also been made available in the United

States without being subject to controls under the Controlled Substances

Act.

What considerations went into the various administrative and regulatory

decisions? Buprenorphine was tested for its abuse potential at the

Addiction Research Center at Lexington in 1975 and 1976 and the results

were published by Jasinski et al. in 1978. It was believed to be a partial

Mu agonist because, in the dog, single doses exhibited ceiling effects, and

64
could, under some circumstances, precipitate abstinence. Buprenorphine

was given subcutaneously in doses up to 2 mg to 14 postaddicts.

In single doses, buprenorphine produced typical

morphinelike effects. Subjects and observers identified it

predominantly as an opiate . . . it was a “euphoriant” as

indicated by the significant scores on scales that measure

euphoria - ‘liking’ and morphine-“Benzedrine” group

(MBG) scale scores.

Jasinski et al., 1978.

Its effects appear to persist longer than those of morphine, similar to what

is observed with methadone. Relative to morphine, it appeared to be more

potent in constricting pupils than in inducing subjective effects. In the

doses used (up to 2.0 mg) ceiling effects were not demonstrated. In a

direct addiction study where dosage was 8 mg/day, five subjects and

observers identified the drug as morphine-like. Only three subjects

completed the double blind withdrawal component of the 58 day study.

As compared with data previously gathered by Fraser et al. (1961), the

Himmelsbach scores for these subjects exceeded placebo levels, peaking

on the 15th day of the withdrawal. For the first 10 days, the withdrawal

scores were significantly smaller than scores observed with other subjects

previously withdrawn from morphine, cyclazocine, nalbuphine,

pentazocine, or butorphanol. On day 14, two of the three subjects

experienced typical signs and symptoms of morphine withdrawal.

Morphine was given to alleviate withdrawal on days 15 to 20. It was

concluded that abrupt buprenorphine withdrawal (which could not be

precipitated with up to 4 mg of naloxone) was associated with mild

withdrawal of delayed onset. A study of the morphine blockade in five

subjects indicated that, after chronic treatment, buprenorphine attenuates

the effects of up to 120 mg doses of morphine, an effect which persists

for at least 30 hours after buprenorphine administration. (It should be

noted that a similar “blockade” of the effects of injected opioids was

reported for subjects maintained on 80 to 100 mg of methadone by Dole

and Nyswander in 1965).

For reasons not entirely clear, the conclusions drawn from the data were

that buprenorphine produced morphine-like euphorigenic effects which

would not exceed those of a 20 to 30 mg parenteral dose of morphine, and

that given the relatively delayed and mild abstinence syndrome (which

might be expected to be less intense than from maximal doses of codeine

or propoxyphene), buprenorphine was “judged to have a significantly

65
lesser abuse potential than codeine or propoxyphene.” Since it is not easy

to argue that an effect equivalent to 20 to 30 mg of parenteral morphine

would not have some abuse potential in susceptible populations, the

lesser abuse potential predicted for buprenorphine must rest largely upon

other grounds. In this case, these grounds would appear to be either its

status as a partial Mu agonist, or its delayed and attenuated morphine-like

withdrawal syndrome.

In making this complex judgement, we encounter again these two central

notions about the nature of drug abuse and dependence: the euphoric or

reinforcing effects vs the avoidance of withdrawal; John Jones vs John

Awsiter; Lawrence Kolb vs Clifton Himmelsbach. The conclusion about

the lower abuse potential of buprenorphine is probably true - for patients

being treated for pain. However, in the past few years, there have been

reports from several countries of the misuse of buprenorphine by heroin

addicts. (see O’Connor et al., 1988).

The marketplace, and the behavior of susceptible populations - the gold

standard against which all of laboratory predictions must be measured -

now seems to be telling us that John Awsiter and Lawrence Kolb were

probably closer to the mark: that provided a drug is not toxic, significant

opioidlike subjective effects, rather than severity of physical dependence,

is the better predictor of potential for misuse by certain vulnerable

populations.

Admittedly, as has always been the case, such a conclusion makes it more

difficult to draw the distinction between moral failure and medical disorder,

between sin and self-medication.

Perhaps the problem is that we have been trying to answer a question that

cannot be answered in the way that it is framed. It may be that John Jones

and John Awsiter are both right with respect to the risk for different

populations. For the patient who is given a drug for therapeutic purposes

- whether an analgesic or an anxiolytic, the euphorigenic effects may pose

little hazard, but the capacity of the drug to engender a form of physical

dependence with an aversive withdrawal syndrome may very well lead

to a perpetuation of drug use beyond the time when it is medically indicated.

On the other hand, for those with a predisposition to seek drug-induced

mood change, (a group that needs to be further defined), especially the

state which we loosely describe as “euphoria,” it is the capacity of a drug

to induce such change that predicts its misuse when it becomes available

to those individuals. To try to average these two distinct categories of risk

66
leads both to an overestimation of risk for some and an underestimation

of risk for others. If we add still another criterion to estimate abuse potential,

such as the capacity of the drug to cause problems when ingested for

suicidal or homicidal purposes, we risk the creationof a rating that conveys

no meaning at all with respect to problems of drug dependence and abuse.

In an historical review, however, weshouldnote that, in nineteenth century

England, the use of opiates for such purposes was an important reason

given for the effort to restrict their availability, a reason which antedated

widespread concern about its habitual or “stimulant” use (Berridge and

Edwards 1981).

CONCLUSIONS

How far have we come in the 3,000 or so years since the sages of the Bible

warned us that the pleasurable effects of wine could lead us into excessive

use, mischief and misfortune? If we measure progress by methodological

sophistication, we have made great strides. We have learned to use

placebos, to select appropriate populations for study, to control for

sequence of drug-administration, and for expectations on the part of both

subjects and observers, to use a range of doses, to frame our questions

carefully, to develop reliable scales, to use appropriate statistical analyses,

and to be cautious in extrapolating our findings only to populations similar

to our subjects. However, if we measure progress by how far we have

come in understanding just how drugs induce euphoria, or why the use of

euphorigenic drugs so often leads to abuse, especially in certain susceptible

individuals, our progress has been modest. We now know that a wide

range of pharmacological agents can induce euphoria or generally pleasant

subjective states in humans, and that several animal species will selfadminister drugs that people tell us induce euphoria; that is, the same

drugs are reinforcers. (Among the obvious discrepancies in this domain

are those cases where animals do not self-administer a drug, such as

cannabis, which in humans produces euphoria with considerable

reliability.) We are also learning that in laboratories certain individuals

will continue to self-administer drugs at dose levels which do not result

in self-reported subjective changes.

We also know that there is more than one kind of physical dependence.

To some degree, we are now beginning to appreciate that, as

counterintuitive as it may seem to some, physical dependence in its broadest

sense is not the same as drug dependence, and that only some withdrawal

67
syndromes are associated with intense drug seeking behavior - a point

that one of us has tried to make without a great deal of success for more

than 20 years (Jaffe 1965, 1985). In researching this paper, we discovered

that these same points had been made by Isbell and Fraser in their 1950

review.

It may be that it is our own need to be able to point to some visible,

concrete measurement of altered body function associated with intense,

repetitive drug-using behavior that leads us again and again to place great

emphasis on withdrawal syndromes. Whether we do this so that we can

more easily explain the behavior to those who see it in moral (rather than

behavioral, biological or medical) terms, or we do it because we really do

not trust the findings from studies of subjective effects, is not clear.

New definitions of drug dependence included in the American Psychiatric

Association’s Diagnostic and Statistical Manual of Mental Disorders,

third edition, revised (DSM-III-R) have attempted to correct the balance

by emphasizing the notion that drug dependence varies in intensity, and

that it is best defined by the behaviors that people exhibit and the degree

to which the drugs control behavior, rather than the degree to which they

experience withdrawal symptoms when the drugs are stopped. On the

whole we are probably now reasonably advanced in our capacity to predict

from our laboratory studies which drugs will be abused (at least by some)

if they were to become widely available.

Where we may have made the least progress is in our methods for

integrating all the knowledge we can generate about any given drug and

translating it consistently into control policies that balance the public’s

need for the drug as a therapeutic agent against the risks that some members

of that public may misuse it.

REFERENCES

Abramson, H.A.; Jarvik, M.E.; Kaufman, M.R.; Kometsky, C.; Levine, A.; and

Wagner, M. LSD-25. I. Physiological and perceptual response. J Psychol

39:3-60, 1955.

Beecher, H.K. Experimental pharmacology and measurement of the subjective

response. Science 116:157- 162, 1952.

Beecher, H.K. Measurement of Subjective Responses. New York, Oxford

University Press, 1959.

Berridge, V.. and Edwards, G. Opium and the People. London: Allen Lane, 1981.

Brecher, E.M. Licit and Illicit Drugs. Boston: Little, Brown and Company, 1972.

68
Byck, R., ed. Cocaine Papers by Sigmund Freud. New York: Stonehill, 1974.

Caldwell, A.E. Origins of Psychopharmacology. From CPZ to LSD. Springfield:

Charles C. Thomas, 1970.

Corti, E. A History of Smoking. New York: Harcourt Brace & Company, 1932.

Dews, P. Remarks. In: Thompson, T., and Unna, K.R., eds. Predicting

Dependence Liability of Stimulant and Depressant Drugs. Baltimore:

University Park Press, 1977, pp. 75-79.

Dole, V.P., and Nyswander, M.E. A medical treatment for diacetylmorphine

(heroin) addiction. JAMA 193:646-650, 1965.

Eddy, N.B. Dilaudid (dihydromorphinone hydrochloride). JAMA 100:1033, 1933.

Eddy, N.B. The National Research Council Involvement in the Opium Problem.

National Academy of Sciences, Washington, D.C., 1973.

Fraser, H.F., and Isbell, H. Comparative effects of 20 mg of morphine sulfate on

non-addicts and former morphine addicts. J Pharmacol Exp Ther 105:498-

502, 1952.

Fraser, H.F.; Isbell, H.; Eisenman, A.J.; Wikler, A.; and Pescor, F.T. Chronic

barbiturate intoxication. Further studies. Arch Intern Med 94:34-41, 1954.

Fraser, H.F., and Jasinski, D.R. The assessment of abuse potentiality of sedative/

hypnotics (depressants). In: Martin, W.R., ed. Handbook of Experimental

Pharmacology. Drug Addiction I. Morphine. Sedative/Hypnotic and

Alcohol Dependence. New York: Springer Verlag. 1977, pp. 590-612.

Fraser, H.F.; VanHom, G.D.; Martin, W.R.; Wolbach, A.B.; and Isbell, H.

Methods for evaluating addiction liability. (A) “Attitude” of opiate addicts

toward opiate-like drugs. (B) A short-term “direct” addiction test. J

Pharmacol Exp Ther 133:371-387, 1961.

Haertzen, C.A. Development of scales based on patterns of drug effects, using the

Addiction Research Center Inventory (ARCI). Psychol Rep 18:163-194,

1966.

Hill, H.E.; Haertzen, C.A.; Wolbach, A.B., Jr.; and Miner, E.J. The Addiction

Research Center Inventory: Appendix I. Items comprising empirical scales

for seven drugs. II. Items which do not differentiate placebo from any drug

condition. Psychopharmacologia (Berlin) 4:184-205, 1963.

Himmelsbach, C.K. Clinical studies of drug addiction. Physical dependence,

withdrawal and recovery. Arch Int Med 69:766-772, 1942.

Himmelsbach, C.K. Further studies of the addiction liability of Demerol. J

Pharmacol Exp Ther 79:5-9, 1943.

Holmstedt, B. Historical survey. In: Efron, D.H.; Holmstedt, B.; and Kline, N.S.,

eds. Ethnopharmacologic Search for Psychoactive Drugs. 1967. PHS Publ.

No. 1645. Washington, D.C.; Supt. of Docs., U.S. Govt. Print. Off., 1967.

pp. 3-32.

Holmstedt, B., and Liljestrand, G., eds. Readings in Pharmacology. New York:

The Macmillan Company, 1963.

Homer. The Odyssey, translated by R. Fitzgerald. New York: Doubleday, 1963.

Isbell, H. Methods and results of studying experimental human addiction to the

newer synthetic analgesics. Ann NY Acad Sci 51:108-122. 1948.

69
Isbell, H.; Altschul, S.; Kometsky, C.H.; Eisenman, A.J.; Flanary, H.G.; and

Fraser, H.F. Chronic barbiturate intoxication. An experimental study. Arch

Neurol Psychiat 64:1-28, 1950.

Isbell, H.; Belleville, R.E.; Fraser, H.F.; Wikler, A.; and Logan, C.R. Studies on

lysergic acid diethylamide (LDS-25). AMA Arch Neurol Psychiat 76:468-

478, 1956.

Isbell, H.; Eisenman, A.J.; Wikler, A.; and Frank, K. The effects of single doses

of 6-dimethylamino-4-4-diphenyl- 3-heptanone (amidone, methadon, or

10820) on human subjects. J Pharmacol Exp Ther 92:83-89, 1948.

Isbell, H., and Fraser, H.F. Addiction to analgesics and barbiturates. J Pharmacol

Exp Ther 99:355-397, 1950.

Isbell, H.; Wikler, A.; Eddy, N.B.; Wilson, J.H.; and Moran, C.F. Tolerance and

addiction liability of 6-dimethylamine-4-4-diphenyl-heptanone-3

(methadon). JAMA 135:888-894, 1947.

Jaffe, J.H. Drug addiction and drug abuse. In: Goodman, L.S., and Gilman, A.,

eds. The Pharmacological Basis of Therapeutics. New York: Macmillan,

1965, pp. 285-311.

Jaffe, J.H. Drug addiction and drug abuse. In: Gilman, A.G.; Goodman, L.S.;

Rall, T.W.; and Murad, F., eds. Goodman and Gilman's The

Pharmacological Basis of Therapeutics. New York: Macmillan, 1985, pp.

532-581.

Jasinski, D.R. Assessment of the abuse potentiality of morphinelike drugs

(methods used in man). In: Martin, W.R., ed. Handbook of Experimental

Pharmacology, Drug Addiction I. Morphine, Sedative/Hypnotic and

Alcohol Dependence. New York: Springer Verlag. 1977, pp. 197-258.

Jasinski, D.R.; Pevnick, J.S.; and Griffith, J.D. Human pharmacology and abuse

potential of the analgesic buprenorphine. Arch Gen Psychiatry 35:501-

516, 1978.

Kalant, O.J. The Amphetamines. Springfield: Charles C. Thomas, 1966.

King, M.R.; Himmelsbach, C.K.; and Sanders, R.S. Dilaudid

(dihydromorphinone). A review of the literature and a study of its

addiction properties. Publ Hlth Rep Suppl 113, 1935.

Kolb, L. Pleasure and deterioration from narcotic addiction. Mental Hygiene

IX(4):699-724, 1925.

Kometsky, C.; Humphries, O.; and Evarts, E.V. Comparison of psychological

effects of certain centrally acting drugs in man. Arch Neurol Psychiat

77:318-324, 1957.

Kramer, J.C. The opiates: Two centuries of scientific study. J Psychedelic Drugs

12(2):89-103, 1980

Kramer, J.C. The metapsychology of opium. J Psychedelic Drugs 13(1):71-79,

1981.

Lasagna, L.; von Felsinger, J.M.; and Beecher, H.K. Drug-induced mood changes

in man. 1. Observations on healthy subjects, chronically ill patients, and

“postaddicts”. JAMA 157: 1006-1020, 1955.

Lewin, L. Phantastica, Narcotic and Stimulating Drugs. New York: E.P. Dutton &

Company, Inc., 1964.

70
Lindemann, E., and Malamud, W. Experimental analysis of the

psychopathological effects of intoxicating drugs. Am J Psychiat 13:853-

881, 1932.

Martin, W.R.; Fraser, H.F.; and Isbell, H. A comparison of the effects of

intramuscularly administered pentobarbital sodium and morphine sulfate

in man. Fed Proc 21:326, 1962.

Martin, W.R.; Thompson, W.O.; and Fraser, H.F. Comparison of graded single

intramuscular doses of morphine and pentobarbital in man. Clin

Pharmacol Ther 15:623-630, 1974.

Moreau, J.-J. Hashish and Mental Illness (Trans.). New York: Raven Press, 1973

Musto, D. The American Disease. New Haven: Yale University Press, 1973.

Nathanson, M.H. The central action of beta-aminopropylbenzene (Benzedrine).

JAMA 108:528-531, 1937.

O’Connor, J.J.; Moloney, E.; Travers, R.; and Campbell, A. Buprenorphine abuse

among opiate addicts. Brit J Addict 83:1085-1087, 1988.

Rush, B. An inquiry into the effects of ardent spirits upon the human body and

mind. In: Excerpts from the Writings of Benjamin Rush. M.D., provided

by Merck Sharp & Dohme, 1976.

Schuster, C.R., and Thompson, T. Self administration of and behavioral

dependence on drugs. Ann Rev Pharmacol 9:483-502,1969.

Seevers, M.H.; Bennett, J.H.; and Reinardy, E.W. The analgesia produced by

nitrous oxide, ethylene and cyclopropane in the normal human subject. J

Pharmacol Exp Ther 59:291-300, 1937.

Seevers, M.H., and Pfeiffer, C. A study of the analgesia, subjective depression,

and euphoria produced by morphine, heroine, dilaudid and codeine in the

normal human subject. J Pharmacol Exp Ther 56:166-187, 1936.

Siegel, R.K. The natural history of hallucinogens. In: Jacobs, B.L., ed. Central

Nervous System Pharmacology. Hallucinogens: Neurochemical.

Behavioral. and Clinical Perspectives. New York: Raven Press, 1984,

pp. l-17.

Terry, C.E., and Pellens, M. The Opium Problem. New York: Bureau of Social

Hygiene, Inc., 1928.

von Felsinger, J.M.; Lasagna, L.; and Beecher, H.K. Drug-induced mood changes

in man. 2. Personality and reactions to drugs. JAMA 157: 1113-1119,

1955.

Wikler, A.; Goodell, H.; and Wolff, H.G. Studies on pain. The effects of analgesic

agents on sensations other than pain. J Pharmacol 83:294-299, 1945.

Williams, E.G.; Himmelsbach. C.K.; Wilder, A.; Ruble, D.C.; and Lloyd, B.J., Jr.

Studies on marihuana and pyrahexyl compound. Public Health Reports

61(29):1059-1083, 1946.

71
AUTHORS

Jerome H. Jaffe, M.D.

Director

Addiction Research Center

National Institute on Drug Abuse

P.O. Box 5180

Baltimore Maryland 21224

Faith K. Jaffe

218 Beech View Court

Baltimore, Maryland 21204

72
CHAPTER 5

Human Abuse Liability Assessment by Measurement

of Subjective and Physiological Effects

Donald R. Jasinski, M.D.

Jack E. Henningfield, Ph.D.

INTRODUCTION

For nearly three decades, measurement of subjective and physiologic

drug effects has been the cornerstone of abuse liability testing of new

chemicals or new formulations considered for use in therapeutics. The

purpose of this paper is to describe this testing strategy. While it is not

within the scope of the chapter to thoroughly review the historical

development of subjective effects assessment procedures (see Jaffe and

Jaffe, in this volume, for such a review), knowledge of certain antecedents

is critical to understanding the rational basis for conducting this type of

abuse liability testing as well as for appropriate interpretation of data.

The underlying principles of using subjective and physiologic response

measures to predict abuse liability of substances evolved from basic

research into the addictive process with opioids. These principles are (1)

that subjective effects can be quantitatively assessed, (2) that subjective

responses to drug administration can often be used to predict the reinforcing

actions of drugs, and (3) that subjective and physiologic responses

following drug administration reflect specific drug-induced alterations

in human brain and body function (see discussions in Jasinski 1977;

Schuster et al., 1981; USDHHS 1988).

Several strategies are used to predict if a drug will readily sustain patterns

of abuse. These include studies designed primarily to assess tolerance,

physical dependence, discriminative effects, and reinforcing efficacy,

utilizing both animal and human subjects (see other chapters in this volume,

Goldberg and Hoffmeister 1971; Thompson and Unna 1977; Thompson

and Johanson 1981; Brady and Lukas 1984; Bozarth 1987; USDHHS

1988). Studies of subjective and physiologic effects provide data which

are complementary to the data obtained from the aforementioned study

strategies. Taken together, these various strategies of evaluation provide

a more thorough characterization of a drug. The confidence in decisions

73
regarding abuse liability is increased when convergent results are obtained

using several such methodologies.

The present chapter focuses on the methods to evaluate the efficacy of

drugs in the production of transient alterations in self-reported mood,

feeling, thinking, and perception, which lead to their self-administration;

that is, subjective drug effects. Certain physiologic drug effects that are

often used in such studies will also be discussed.

BACKGROUND

The production of certain subjective effects essentially defines dependence

producing drugs and sets them apart from other drugs and food; drugs

that produce such effects are sometimes termed “psychoactive,”

“psychotropic” or ‘behaviorally active;” the effects are often referred to

as “psychoactive,” “interoceptive,” “subjective,” “psychic,” or “selfreported” (President’s Advisory Commission on Narcotic and Drug Abuse

1963; WHO 1981; USDHHS, 1988). Dependence producing drugs are

chemicals that can readily control behavior by a variety of potential

mechanisms (Thompson and Schuster 1968; USDHHS 1988). For

example, they may serve as positive reinforcers by virtue of direct actions

in the central nervous system, they may produce desirable changes in

mood and feeling, they may relieve dysphoric mood states, they may

alleviate pain and other physical ailments, their administration may

facilitate performance which may otherwise have suffered due to fatigue

or stress, and repeated administration can lead to a state of physical

dependence whereby abstinence is accompanied by an increased

propensity to take the drug. Similarly, the potential abuse liability of

drugs can be assessed by a variety of procedures. However, until at least

the 1970s, in human subjects, quantification of subjective effects was the

only validated method of testing for the likelihood that use of a drug

would lead to addictive patterns of use. Since then, drug self-administration

and drug discrimination testing strategies developed using animals as

subjects (e.g., Thompson and Unna 1977) have been incorporated into

human abuse liability testing studies (Bozarth 1987; USDHHS 1988).

The theoretical basis for the assessment of subjective drug effects had

been understood early in the twentieth century. For example, in the

1920s, Lewin had observed that it was the “phantastica” (i.e., “subjective”)

effects of substances that lead to their habitual use (Lewin 1931).

Practically useful methods for evaluating such effects did not emerge

until the behavioral sciences themselves had become sufficiently

sophisticated in the 1930s and 1940s. Prior to this tune, dependence

74
producing drugs were identified primarily on the basis of retrospective

observations of their effects in clinical and social settings.

The systematic assessment of subjective drug effects was essentially an

extension of the methods developed to assess physiologic actions of

drugs. By the late 1940s, several drug dependence researchers had

recognized that physical dependence potential testing was of limited

value in predicting the likelihood that behavioral dependence would

develop following exposure to a given drug (Isbell 1948; Isbell and Vogel

1948). These researchers used observational techniques to infer

interoceptive drug effects. “Euphoria” was the designated label for such

effects; drugs producing such effects were sometimes termed

“euphoriants”. The rationale and basic methods of assessment were most

elegantly described by Isbell (1948):

Since most people begin the use of drugs andbecome addicted

because the drugs produce effects which they regard as

pleasurable, the detection of euphoria is a very important

procedure in evaluating abuse liability. The method used is

simple: single doses of the drug under test are administered

to former drug abusers, and the subjects are unobtrusively

watched for a period of 6 hours or more by specially trained

observers. For our purposes, euphoria is defined as a series

of effects similar to those produced by morphine. These

effects are: increased talkativeness, boasting, greater ease

in the experimental situation, expression of satisfaction with

the effects of the drug, requests for increased doses of the

drug, increased motor activity, and, with larger doses slurring

of speech, motor ataxia, and evidence of marked sedation.

As many experiments are done as necessary to reach a clearcut conclusion. The observations are controlled by

administering 30 mg of morphine to the same subjects on

other occasions. Initially, small subcutaneous doses of the

drug under test are used, and if no untoward toxic effects are

observed, the dosage is increased progressively in subsequent

experiments until evidence of euphoria, roughly equivalent

to that produced by 30 mg of morphine is detected or if no

evidence of euphoria is detected, the dosage is elevated until

further increases would be regarded asdangerous. If euphoria

is detected, blind experiments are arranged in which neither

the subject nor the observer are aware whether the drug

given was morphine or the compound under test. Finally

various doses of the drug are administered intravenously.

75
It is noteworthy that the initial definition of euphoria was judged solely

by observed signs, that the data were exclusively those that could be

collected by observers, and that the model was based on the effects of

morphine. Subsequent theoreticians occasionally assumed that subjective

effects (viz. euphoria) were causal in the maintenance of drug seeking

behavior. The more widely accepted current position would seem to be

that, subjective effects are related to the maintenance of and relapse to

drug seeking in a complex but orderly manner but are not necessary in the

causation of the behavior (see discussion in Schuster et al., 1981).

Evolution of the methods of Isbell, and their practical implementation,

was greatly enhanced by developments in the 1950s and early 1960s. For

example, Rao (1952) developed procedures for assessing changes in

subjective state which were of substantially enhanced reliability, and

Beecherand his colleagues (Beecher 1959) adapted quantitative bioassay

procedures to assess subjective responses to pain stimuli and to the effects

of analgesic drugs on such responses (Jasinski 1977; USDHHS 1988).

Beecher alsoestablished the importance and utility of the crossover (within

subjects) experimental design with inclusion of standard and placebo

drug control procedures, the double-blind technique, and randomized

testing sequences in the assessment of subjective drug effects.

These pioneers in the assessment of abuse potential of drugs made the

following observations that provide the conceptual basis of current

strategies:

1) drugs produce reproducible transitory subjective states,

2) states produced by drugs may be used to define drug classes,

3) individuals can reliably discriminate drug induced subjective

states,

4) the subjective state characteristic of drugs of abuse is one of

euphoria,

5) the nature of the state is related to the propensity to take the drug,

6) physical dependence is neither necessary nor sufficient to establish

and maintain drug seeking behavior (cf. Jasinski 1977; USDHHS

1988).

Development of the Single Dose Questionnaire (SDQ) and the

Addiction Research Center Inventory (ARCI)

The advances described above contributed to the development of what is

generally considered the first standardized questionnaire used to compare

the addictive properties of a wide range of drugs, namely the Single Dose

Questionnaire (SDQ) (Appendix A). The SDQ was developed by Fraser

76
and his colleagues as an extension of the methods of Himmelsbach to

quantitate transient changes in mood and subjective state induced by the

administration or withdrawal of drugs (Fraser and Isbell 1960; Fraser et

al., 1961). The SDQ was comprised of scales that permitted the subject

to report feeling or not feeling the drug, to identify it from a list of possible

drugs, to report symptomology, and to rate any liking of it. An analogous

questionnaire, for completion by observers, permitted independent

verification of certain self-reported effects (Appendix A). The designation,

Single Dose Questionnaire, was derived from its applicability to the

qualitative and quantitative characterization of drugs based upon the

individual administration of drugs to human volunteers.

The next major advance in the quantification of subjective drug effects

was the development of the Addiction Research Center Inventory (ARCI)

by Haertzen and his colleagues (Haertzen et al., 1963; Haertzen 1966,

1974; Haertzen and Hooks 1969; Haertzen and Hickey 1987) (Appendix

B presents a short form of the ARCI). The ARCI contained scales that

were empirically derived to be sensitive to the effects of specific drugs

and drug classes (e.g., sedatives, stimulants, hallucinogens). One of the

most useful scales was developed to measure the effects of morphine and

benzedrine (a prototypic opioid and amphetamine, respectively); this

scale was subsequently referred to as the “Morphine Benzedrine Group”

or “MBG” or “Euphoriant” scale since morphine-like and benzedrinelike drugs increase the scale scores while simultaneously producing

feelings often reported as pleasurable (Haertzen et al., 1963; Haertzen

1974). Scores on the MBG scale are also elevated by most other addicting

drugs (Jasinski 1977; Jasinski et al., 1984).

Determination of pharmacologic equivalence

The SDQ and ARCI tests were standardized by administering them to

volunteers following their exposure to placebo or to some dose of a drug

that was already known to be widely abused or otherwise used by drug

addicts. These included morphine, amphetamine, pentobarbital, alcohol,

marijuana, and lysergic acid diethylamide. Subsequently, drugs such as

diazepam and nicotine were also tested. These drugs each served to some

degree as prototypic or standard drugs since each produced its own unique

profileof actions. Assessing the abuse liability of new drugs is essentially

a procedure for assessing their pharmacologic equivalence with the

standard drugs.

The method of classification by comparing new substances to prototypes

was not only important for pharmacological theory and clinical utility; it

was also the basis for legal/regulatory actions. In 1946, the Harrison

77
Licensing Act was amended to subject substances with addiction-forming

or addiction-sustaining liability similar to that of morphine to narcotics

control laws (Martin 1977). This action paved the way for the Narcotics

Manufacturing Act of 1960 to regulate substances with “addictionsustaining liability similar to morphine or cocaine...,” and, in turn, to the

Comprehensive Drug Abuse Prevention and Control Act of 1970. The

latter Act provided for various levels of restriction of manufacturing,

access, sale, and use of substances (i.e., Schedules I-V) depending, not

upon their chemical structure, but rather upon their degree of

pharmacologic equivalence to various prototypic addicting drugs (Martin

1977).

To the extent to which certain common features are identified, they may

be categorized together, e.g., as dependence producing or addicting drugs.

Furthermore, to the extent to which the drugs differ in certain respects,

they may be subcategorized as, for example, dependence producing drugs

of the morphine type or of the amphetamine type. Such categorization

must be viewed with caution, however, since overemphasis on any

particular feature of a drug can be misleading. For instance, nicotine has

been viewed as both a stimulant (“excitant”) (Lewin 1931) and a sedative

(Armstrong-Jones 1927). Most commonly, nicotine is now categorized

as more stimulant-like than sedative-like, but with an appreciation of its

diverse range of potential effects (Gilman et al., 1985).

It is now well-established that if a drug is discriminated and produces

elevations on the liking scale of the SDQ, and if it produces elevations on

scores on the MBG scale of the ARCI, then it is appropriately categorized

as a drug with a potential to addict users. Two other scales of the ARCI

are commonly used to characterize the subjective effects of psychoactive

drugs in humans. These are the Pentobarbital Chlorpromazine Alcohol

Group (PCAG) Scale which reflects sedation and intoxication, and the

Lysergic Acid Diethylamide (LSD) scale which reflects dysphoria and

feelings of fear and paranoia (Haertzen 1974). A drug identification scale

and symptom check list of the SDQ provide additional information

characterizing the subjective effects of the drug and providing an objective

basis for its classification.

The selectivity and sensitivity of such procedures is illustrated in figure

1. As shown in the figure, when persons with multiple addiction histories

were given drugs under double-blind conditions, they rated placebo and

the nonaddicting zomepirac at a minimal level of “liking.” As a direct

function of dose, however, the known addicting drugs were rated with

greater liking scores. Pretreatment with opioid antagonists blocks such

effects produced by morphine (Jasinski 1977) and pretreatment with a

78
nicotinic antagonist blocked such effects produced by nicotine

(Henningfield et al., 1984).

Using the MCI, a finer grain analysis of the subjective effect is possible.

For example, table 1 shows the profiles of some prototypic drugs obtained

on commonly used scales of the ARCI. As shown in the table, all of the

known addicting drugs produced changes in mood and feeling that

Figure 1: Mean scores on the Liking Scale of the Single Dose Questionnaire from

subjects tested at the Addiction Research Center. The number of subjects in each

group range from 6 (pentobarbital and chlordiazepoxide) to 13 (d -amphetamine).

The high dose of each drug except zomepirac produced significant (p < 0.05)

increases in scores above placebo data. The responses are peak responses which

occurred after the drug had been given. The time of the peak response ranged from

about 1 minute (nicotine) to 5 hours (buprenorphine). Morphineandzomepirac data

are from the same group of subjects as are the pentobarbital and chlordiazepoxide

data. The P+T point on the pentazocine graph is the score, by the same subjects, to

40 mg pentazocine given in combination with 50 mg tripelennamine (an antihistamine

thatproduceda Liking score of 0.9)—the street combination called “T’s and Blue’s.”

The Mpoint on the THC graph is the score, from the same subjects, obtained after

smoking a marijuana cigarette that contained 10 mg (1 percent by weight) -THC.

(from Jasinski, Johnson, and Henningfeld 1984).

79
Table 1. Drug-induced increases (+) and decreases (-) on ARCI scales.

Investigators’ Estimates: -- - -0 0 0+ + ++

Drug Condition

Stimulants-amphetamine, cocaine

Opiates-heroin, morphine,

methadone

Partial opiate agonists—

pentazocine, nalbuphine

Marijuana

Barbiturates—pentobarbital,

secobarbital

Minor tranquilizers—diazepam

Alcohol

Major tranquilizers—

chlorpromazine

Narcotic antagonists—

nalorphine, cyclazocine

Hallucinogens—LSD

Others—scopolamine

Inactive—zomepirac, loperamide,

bupropion

Opiate withdrawal—morphine,

heroin, methadone

Alcohol withdrawal

1

Simulated barbiturate withdrawal

Simulated alcohol withdrawal

Simulated opiate withdrawal

Simulated pep pill come down

Simulated cocaine come down

Ef MBG PCAG LSD SOW

Note: from Haertzen and Hicky 1987.

1

Test results based upon retrospective reporting of subjective effects.

EF = Efficiency or BG (Benzedrine group variability)

MBG = Morphine-Benzedrine group

PCAG = Pentobarbital, chlorpromazine, and alcohol group

LSD = LSD group or drug correction

SOW = Strong opiate withdrawal

80
resembled those produced by morphine or benzedrine enough to

significantly elevate the MBG scale scores.

Validation of measures

These self-reported markers of drug effects associated with their abuse

liability have been validated by the use of similar rating scales by observers

who are blind as to the condition. Based on their observation of the

behavior of the subjects, observers can provide similar dose-related

increases in scores on strength of the drug effect and/or the level of drug

liking for alcohol (Henningfield et al., 1984), pentobarbital (Martin et al.,

1974), morphine and heroin (Martin and Fraser 1961), amphetamine

(Jasinski and Nutt 1972), either i.v. nicotine or research cigarettes which

varied in nicotine delivery (Henningfield et al., 1985), and a variety of

other drugs (Jasinski 1977).

These self-reported indices of abuse liability also correspond to a variety

of physiologic effects that can be approximately simultaneously measured.

Some of these physiologic changes vary across drug class; for example,

pupil diameter increases appear to correspond to early nicotine-induced

subjective effects (Henningfield et al., 1984); whereas pupil diameter

decreases when morphine is given (Jasinski 1977). Other physiologic

effects show a greater degree of similarity across drug classes: for example,

studies of ethanol administration in human subjects revealed that

paroxysmal bursts of electroencephalogram (EEG) alpha activity

paralleled subjective reports of euphoria during the ascending limb of the

plasma ethanol curve (Lukas et al., 1985a, 1986a) which also paralleled

increases in plasma adrenocorticotropic hormone (ACTH) levels (Lukas

and Mendelson 1988). Similar effects were observed following marijuana

smoking (Lukas et al. 1985b, 1986b) and acute i.v. nicotine administration

(Lukas and Jasinski 1983). In turn, similar changes in EEG alpha activity

have been shown to correspond with subject-reported pleasurable states

which can occur in the absence of drug administration (Lindsley 1952;

Brown 1970; Wallace 1970; Matejcek 1982).

Physiologic data, obtained in the course of abuse liability assessment

studies, serve at least three distinct and important functions. First,

physiologic data provide an independent and objective means of

verification of exposure to the drug and of the degree of dose sensitivity

of the subjects. Second, physiologic data provide information regarding

the possible toxicity of the drug. Third, physiologic data may reveal

mechanisms, or at least, concommitants of drug induced changes in

subjective effects.

81
MEASUREMENT TECHNIQUES

Early on, it was recognized that reconciliation of clinical reports and

anecdotal observations with scientific theories of drug addiction could

best be accomplished through the careful observation of human volunteers

in a controlled research setting. In such settings, drugs could be

administered or withdrawn and resulting phenomena recorded, thus

revealing the oftentimes complex relationships among independent and

dependent variables.

Current methods for assessing subjective and physiologic drug effects

essentially entail giving either drug or placebo to a volunteer, and then

asking him/her to report the nature of effects produced. Replicability and

objectivity are increased by using standardized questionnaires such as

those described above (e.g., “liking” scales, ARCI). In practice, several

procedural variations are used to further enhance the reliability and

validity of the results. The dose of the drug is varied to assess the nature

of the dose-effect relations; for all dependence producing drugs, ratings

of dose strength, or percentage of accurate drug identifications, are directly

related to the dose given. Subjects with histories of use of a variety of

drugs can be asked to report which, if any, of those drugs, the test drug

feels like. Table 2 provides a summary of the basic methods of assessing

subjective and physiologic effects in abuse liability studies.

LIMITS OF USING SUBJECTIVE EFFECTS DATA TO

PREDICT ABUSE LIABILITY

The main constraint of using subjective effects assessment to predict

actual patterns of drug abuse is that such testing does not assess the wide

range of nonpharmacologic factors that may function to increase or

decrease the actual abuse and associated public health problems. For

example, use of even highly addictive substances such as heroin, cocaine,

and tobacco products have historically varied as a function of factors such

as price, availability, social acceptability, and public knowledge of health

risks (cf. USDHHS 1988).

Hallucinogens provide a notable category of substances in which patterns

of abuse have appeared to be particularly related to social factors (USDHHS

1988). Interestingly, these drugs tend to robustly increase reports of

items on the ARCI LSD scale that are often related to feelings of fear,

82
Table 2. Basic methods for assessing subjective drug effects.

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

Subjects are tested in a controlled laboratory setting with appropriate medical

support and with formal procedures to protect their rights and welfare.

Subjects are volunteers with histories of use of a variety of drugs; such

subjects can accurately discriminate substances with a potential for addiction.

To minimize possible bias, the subject and, ideally, the experimenter, are

kept blind as to whether drug or placebo were given, and possibly what type

of drug might be given

Single doses of drugs are given at sufficient time intervals to eliminate

residual drug effects. Intervals range from about one hour to several days

Following the drug administration, a variety of physiological, observerreported (signs or behaviors) and self-reported (symptoms or subjective)

effects are assessed at intervals which range from a few seconds to several

hours, depending on the time course of drug action. When possible,

simultaneous assessment of blood levels of the drug can provide information

relating the pharmacokinetics of the drug to the subjective and physiologic

effects.

The test compound is always compared to placebo, and usually to an

appropriate positive control (such as morphine in a study of analgesics, or

pentobarbital in a study of sedatives).

Both the test and control compounds are given at two or more dose levels.

A limited number of subjects (usually about 10) participate according to a

design whereby the subject is tested under each condition (cross-over or

within-subject design).

Pretreatment with a known blocker (antagonist) of the test drug can be

given to determine if the subjective effects are similarly blocked as previously

studied effects.

Data are expressed as changes from the pre-drug (baseline) observations

and are averaged across subjects. Depending on the temporal pattern, drug

effects may be expressed either as peak effect or as the area under the timeaction curve for changes in scores.

83
paranoia, andotheradverse effects, i.e., dysphoria (Haertzen 1966, 1974).

Consistently, such drugs do not serve as effective reinforcers for animals

(Griffiths et al., 1980). It is plausible that use of drugs in which there is

a notable degree of both pleasant and unpleasant effects at typically

ingested doses would be more dependent on nonpharmacologic factors

than drugs which do not produce such striking dysphoric effects at

commonly ingested doses.

Somewhat analogous to the findings with hallucinogens are those with

caffeine. Caffeine is a drug that produces only weak elevations on the

Liking and MBG scales while elevating scores on the LSD scale of the

ARCI and also the Tension-Anxiety scale of the Profile of Mood States

(Chait and Griffiths 1983). Consistent with such data are the observations

that although caffeine is occasionally abused, the overwhelming majority

of users do not use it in ways that are considered to be of significant

adverse health effect (cf. Gilbert 1976; Greden 1981; Griffiths and

Woodson 1988a,b). The subjective effects data suggesting limited

potential of caffeine to cause abuse are also consistent with the findings

that caffeine has not been shown to serve as an effective reinforcer for

animals (Griffiths and Woodson, 1988b). Patterns of use and abuse of

caffeine appear rather, to be heavily dependent upon social circumstance

and pressure and perceived or actual beneficial effect. In addition, because

caffeine exposure can produce physical dependence which is marked by

undesirable withdrawal effects (including headaches, lethargy, and

irritability), some use may occur as a means of avoiding such effects

(Griffith and Woodson 1988a).

MAXIMIZING THE ACCURACY OF CONCLUSIONS

Accurate conclusions are a function of both the methods of empirical data

collection as well as the analytic interpretation of data. To obtain valid

and reliable data, it is important to follow the procedures for subjective

effects assessment as summarized in table 2 and elsewhere (Jasinski

1977). In particular, use of appropriate positive and negative control

substances as well as appropriate manipulations of drug dose, and the use

of appropriate test subjects are fundamental. For example, variation in

dose level should result in variation of response magnitude. Analogously,

preloading subjects with antagonists should reduce the magnitude of

responses (USDHHS 1988). Improvement of measurement techniques

should also come with the innovative refinement of existing technology

and the development of new technologies such as computerized testing

and better observational techniques for verification of effects.

84
Improvement in accuracy can arise not only from careful use and

appropriate modification of procedures for collecting data, but also from

improved techniques of interpretation of data. Improvement via refinement

of interpretation can be illustrated by examination of Single Dose

Questionnaire data. The sensitivity of the instrument is greatest when

data from only a single scale is used, namely can the subject “feel the

drug.” Such data are directly related to dose as determined according to

double blind testing procedures, however, their specificity is poor. That

is, no information is provided regarding the liking of the substance or the

qualitative nature of its effects in comparison tootherdrugs. For example,

such data do not allow discrimination between the rarely abused major

tranquilizers and the widely abused psychomotor stimulants. Simply

relying upon scales of the ARCI, on the other hand, may imply that low

dose levels of addictive drugs are of little concern since they do not

significantly elevate scale scores. When studied in combination, the

scales which assess simple discriminability of drugs along with scales

that provide qualitative information can provide accurate information

about the potential of a certain drug to be abused and the dose threshold

at which any relevant effects may occur.

Interestingly, analogous observations and refinement in methods of

discrimination testing in animals were critical to establish animal drug

discrimination testing as a viable means to assess abuse liability. Overton

and his colleagues examined the hypothesis that simple determination of

discriminative effects would be sufficient to assess abuse liability (Overton

and Batta 1977). These researchers found that, although a sensitive,

measure, simply determining that a drug could serve as a discriminative

stimulus was not sufficiently specific for an abuse liability assessment;

for example, opioids, stimulants, tricyclic antidressants, and antihistamines

were approximately similar in their degree of discriminability (Overton

and Batta 1977). By training animals to identify prototypic drugs of

abuse and then determining the degree to which such identifications

would generalize to the test drugs, a sensitive and specific procedure

evolved (cf. Overton 1971; Goldberg et al., 1981b; Jarbe and Swedberg

1982; USDHHS 1988).

GENERALITY OF FINDINGS

The generality of data obtained from studies of subjective and physiologic

drug effects has been widely confirmed by a number of lines of laboratory

and nonlaboratory data. Patterns of drug use outside the laboratory

frequently correspond to laboratory obtained subjective effects data. This

85
has been found both in analyses of subjective effects of drugs already

known to be abused (e.g., morphine, cocaine, nicotine), as well as

evaluation of drugs prior to their becoming widely available (e.g.,

pentazocine, nicotine polacrilex gum, buspirone) (Jasinski 1977;

USDHHS 1988). Human subjective effects assessment data also are

generally consistent with those obtained from animal and human abuse

liability tests that utilize different test strategies. For example, two reviews

reported strong correlations between animal drug self-administrationdata

and human subjective effects data, i.e.. animals tended to self-administer

drugs which produced morphine-like profiles of effects in humans

(Griffiths and Balster 1979; Griffiths et al., 1980). Other kinds of laboratory

data demonstrating mechanisms by which drugs can control behavior

also correspond, to a rather remarkable degree, to data obtained from

studies of subjective drug effects in humans. A summary of several such

lines of data is provided in table 3. As shown in the table, there is a good

general correspondence across data sources; however, each procedure

and source of data provides additional information that is useful to fully

characterize the potential mechanisms by which drugs can control

behavior.

PRACTICAL APPLICATIONS OF SUBJECTIVE TESTING

STRATEGIES

There are diverse practical and theoretical applications of subjective effects

data. Studies of the subjective effects of drugs can provide basic data on

the biologic basis of drug dependence itself, as well as serve to provide

practical, useful information for drug development efforts. In these

capacities, for example, such data led to the postulation of differing

receptors to explain the diverse effects of opioids, they have helped to

determine appropriate ligands for drug receptor studies, and to quantitate

possible effects of therapeutic agents. These applications are not mutually

exclusive and are often incorporated within single studies.

The application of subjective effects assessment as a practical means of

abuse liability testing was not initially an end unto itself, but rather emerged

as a product of basic studies of the biological basis of drug dependence.

The usefulness of such data in making regulatory decisions about drugs,

however, did lead to the emergence of abuse liability testing in its own

right, largely in the 1960s and early 1970s. Although practically oriented,

these studies continued to provide a substantial base of data upon which

further theory related to the understanding and treatment of drug

dependence rested. For example, a high degree of correlation was observed

between drugs that were abused by humans, self-administered by animals,

86
Table 3. Characteristics of psychoactive drugs
and produced key subjective effects of opioids and stimulants. These

observations confirmed that the process of drug addiction involved basic

biologic mechanisms which were common to diverse drugs and species

(Crowley and Rhine 1985; Jasinski and Henningfield 1988; Jasinski 1988).

Perhaps the most practical application of subjective effects testing for

abuse liability assessment is in the development of drugs with selective

actions, i.e., retaining therapeutic efficacy with lowered abuse liability.

New psychoactive drugs and formulations of psychoactive drugs are now

routinely tested using such methods. For example, subjective effects data

were important in evaluation of the serotonergic acting drugs, fenfluramine

and buspirone, which were developed as anorectics and anxiolytics,

respectively, with lower potentials for abuse than the prototypic substances

that each was intended to replace (Griffith et al., 1975, 1986). Similarly,

nicotine polacrilex gum was a new formulationof nicotine which subjective

effects data had shown was low in abuse liability relative to several other

forms of nicotine and other addictive drugs (Nemeth-Coslett et al., 1987;

US DHHS 1988). Most recently, tilidine, transnasal butorphanol and

picenadol were evaluated as selective drugs with low abuse liability for

the treatment of pain, and zolpidem for the treatment of anxiety, using the

methods described in this chapter (Jasinski et al., 1988; Jasinski and

Preston 1986; Jasinski, personal communication).

As the aforementioned examples suggest, applications of this method

include the evaluation of drugs whose chemical structure or intended

therapeutic use differs from that of prototypic drugs used for assessments

of pharmacologic equivalence. For example, new generations of

behavioral performance enhancing drugs may be evaluated, and decisions

rationally made, as to whether their profile of effects most resembles that

of opioids, sedatives, stimulants, major tranquilizers, anticholinergics, or

any other previously tested substances. Observations that a drug produces

robust, dose-related elevations on the Liking and MBG scales are indices

of a liability for abuse regardless of other characteristics.

The need for continued development of procedures for assessing subjective

and physiologic drug effects is perhaps best illustrated by the continuing,

although evolving problems of drug dependence and for public health

needs for continued development of safer and more effective medications

for the alleviation of disease and suffering. The facts that drugs, drug

delivery systems, and public health needs continue to change imply that

there will be a continuing need for practical and effective methods of

abuse liability testing. The diversity of the challenges probably will

require the continued maintenance of a diversity of methods of abuse

liability assessment as represented in this volume and elsewhere (Goldberg

88
and Hoffmeister 1971; Thompson and Unna 1977; Brady and Lukas

1984; Bozarth 1987; USDHHS 1988).

As shown in this chapter, the strategy of abuse liability assessment relying

upon subjective effects assessment in humans can be used to provide a

quantitative and reliable base of data upon which rational decision making

can be made. Procedural and interpretational strategies discussed in this

chapter may strengthen the reliability, sensitivity and specificity of the

data obtained. Further refinement of such methods and their incorporation

into other strategies (e.g., combining human drug self-administration

tests with subjective effects evaluations) should provide even greater

reliability and specificity, and provide even more powerful tools for future

challenges.

REFERENCES

Armstrong-Jones, R. Tobacco, its use and abuse: From the nervous and mental

aspect. Practitioner 118:6-19, 1927.

Austin, G.A. Perspectives on the History of Psychoactive Substance Use,

National Institute on Drug Abuse Research Monograph No. 24. DHEW

Pub. No. (ADM) 79-810. Washington, D.C.: Supt. of Doc., U.S. Govt.

Print. Off., 1979.

Babor, T.F.; Mendelson. J.H.; Greenberg, I.; and Kuehnle. J.C. Marijuana

consumption and tolerance to physiologic and subjective effects. Arch

Gen Psychiatry 32(12):1548-1552, 1975.

Baldessarini, R.J. Drugs and the treatment of psychiatric disorders. In:

Goodman, L.S.. and Gilman, A. eds. The Pharmacological Basis of

Therapeutics. New York: MacMillan, 1980, pp. 391-447.

Bardo, M.T., and Neisewander. J.L. Single-trial conditioned place preference

using intravenous morphine. Pharmacol Biochem Behav 25:1101-1105,

1986.

Beardsley, P.M.; Balster, R.L.; and Harris, L.S. Dependence on

tetrahydrocannabinol in rhesus monkeys. J Pharmacol Exp Ther

239(2):311-319, 1986.

Beecher, H.K. Measurement of Subjective Responses Quantitative Effects of

Drugs. New York: Oxford University Press, 1959.

Bigelow. G.E.; Griffiths, R.R.; and Liebson, I.A. Experimental models for the

modification of human drug self-administration: Methodological

developments in the study of ethanol self-administration by alcoholics.

Fed Proc 34:1785-1792, 1975.

Bozarth, M.A., ed. Methods of Assessing the Reinforcing Properties of Abused

Drugs. New York: Springer-Verlag, 1987.

Brady, J.V., and Lukas, S.E., eds. Testing Drugs for Physical Dependence

Potential and Abuse Liability. National Institute on Drug Abuse Research

Monograph No. 52. DHHS Pub. No. (ADM) 84-1332. Washington, D.C.:

Supt. of Docs., U.S. Govt. Print. Off., 1984.

89
Brecher, E.M. Licit and Illicit Drugs. Boston: Little, Brown, 1972.

Brown, B.B. Recognition of aspects consciousness through association with EEG

alpha activity represented by a light signal. Psychophysiology 6(4):442-

452, 1970.

Carney, J.M. Effects of caffeine, theophylline and theobromine on scheduled

controlled responding in rats. Br J Pharmacol 75(3):451454, 1982.

Carpenter, J. Effects of alcohol on some psychological processes. Quart J Stud

Alcohol 23:274-314, 1962.

Carroll, M.E., and Lac, S.T. Cocaine withdrawal produces behavioral disruptions

in rats. Life Sci 40:2183-2190, 1987.

Chait, L.D., and Griffiths, R.R. Effects of caffeine on cigarette smoking and

subjective response. Clin Pharmacol Ther 34(5):612-622, 1983.

Childress, A.R.; McLellan, A.T.; Ehrman, R.; and O’Brien, C.P. Classically

conditioned responses in opioid and cocaine dependence: A role relapse?

In: Ray, B., ed. Learning Factors in Substance Use. National Institute on

Drug Abuse Research Monograph 84. DHHS Pub. No. (ADM)88-1576.

Washington, D.C.: Supt. of Docs., Govt. Print. Off., 1988, pp. 25-43.

Christen, A.G., and Glover, E.D. History of smokeless tobacco use in the United

States. Health Education 18(3):6-13, 1987.

Cone, E.J.; Johnson, R.E.; Moore, J.D.; and Roache, J.D. Acute effects of

smoking marijuana on hormones, subjective effects and performance in

male human subjects. Pharmacol Biochem Behav 24(6):1749-1754, 1986.

Connolly, G.N.; Winn, D.M.; Hecht, S.S.; Henningfield, J.E.; Walker, B., Jr.; and

Hoffman, D. The reemergence of smokeless tobacco. N Engl J Med

314(16):1020-1027, 1968.

Crowley, T.J., and Rhine, M.W. The substance use disorders. In: Simons, R.C.,

eds. Understanding Human Behavior in Health and Illness. Baltimore:

Williams and Wilkins, 1985, pp. 730-746.

Deneau, G.A., and Inoki, R. Nicotine self-administration in monkeys. Ann NY

Acad Sci 142:277-279, 1967.

Deneau, G.; Yanagita, T.; and Seevers, M.H. Self-administration of psychoactive

substances by the monkey. A measure of psychological dependence.

Psychopharmacologia 16:30-48, 1969.

De Wit, H.; Uhlenhuth, E.H.; Pierri, J.; and Johanson, C.E. Individual differences

in behavioral and subjective responses to alcohol. Alcoholism 11(1):52-

59, 1987.

Domino, E.F. Neuropsychopharmacology of nicotine and tobacco smoking.

Psychopharmacol Bull 19:398-401, 1978.

Downs, A.W., and Eddy, N.B. The effect of repeated doses of cocaine in the rat.

J Pharmacol Exp Ther 46:199-200, 1932.

Dreisbach, R.H., and Pfeiffer, C. Caffeine-withdrawal headache. J Lab Clin Med

28(8):1212-1219, 1943.

Eddy, N.B., and Downs, A.W. Tolerance and cross-tolerance in the human

subject to the diuretic effect of caffeine, theobromine, and theophyline. J

Pharmacol Exp Ther 33:167-174, 1928.

Fischman, M.W., and Schuster, C.R. Cocaine self-administration in humans. Fed

Proc 41(2):241-246, 1982.

90
Fischman, M.W.; Schuster, C.R.; Resnekov, L.; Shick, J.F.E.; Krasnegor, N.A.;

Fennell, W.; and Freedman, D.X. Cardiovascular and subjective effects of

intravenous cocaine administration in humans. Arch Gen Psychiatry

33:983-989, 1976.

Fraser, H.F., and Isbell, H. Human pharmacology and addiction liabilities of

phenazocine and Ievophenacylmorphan. Bull Narc 12:15-23, 1960.

Fraser, H.F.; Van Horn, G.D.; Martin, W.R.; Wolbach, A.B.; and Isbell, H.

Methods for evaluating addiction liability. (A) “Attitude” of opiate addicts

toward opiate-like drugs. (B) A short-term “direct” addiction test. J

Pharmacol Exp Ther 133:371-387, 1961.

Fudala, P.J.; Teoh, K.W.; and Iwamoto, E.T. Pharmacologic characterization of

nicotine-induced conditioned place preference. Pharmacol Biochem

Behav 22:237-241, 1985.

Gilbert, R.M. Caffeine as a drug of abuse. In: Gibbins, R.J.; Isreal, Y.; Kalant,

H.; Popham, R.E.; Schmidt, W.; and Smart, R.G., eds. Research

Advances in Alcohol and Drug Problems, Vol. 3, New York: John Wiley

and Sons, 1976, pp. 49-176.

Gilman, A.G.; Goodman, L.S.; Rail, T.W.; and Murad, F., eds. Goodman and

Gilman's The Pharmacological Basis of Therapeutics. New York:

Macmillan, 1985.

Goldberg, L. Quantitative studies on alcohol tolerance in man: The influence of

ethyl alcohol on sensory motor and psychological functions referred to

blood alcohol in normal and habituated individuals. Acta Physiol Scand

5(16, Supplement):1-128, 1943.

Goldberg, L., and Hoffmeister, F., eds. Psychic Dependence Definition.

Assessment in Animals and Man. Theoretical and Clinical Implications.

Berlin: Springer-Verlag, 1971.

Goldberg, S.R.; Spealrnan, R.D.; and Goldberg, D.M. Persistent behavior at high

rates maintained by intravenous self-administration of nicotine. Science

214(4520):573-575, 1981a.

Goldberg, S.R.; Spealman, R.D.; and Shannon, H.E. Psychotropic effects of

opioids and opioid antagonists. In: Hoffmeister, F., and Stile, G. eds.

Handbook of Experimental Pharmacology. Berlin: Springer-Verlag,

1981b, pp. 269-304.

Greden, J.F. Caffeinism and caffeine withdrawal. In: Lowinson, J.H., and Ruiz,

P., eds. Substance Abuse. Clinical Problems and Perspectives.

Baltimore: Williams and Wilkins, 1981, pp. 274-286.

Griffith, J.D.; Jasinski, D.R.; Casten, G.P.; and McKinney, G.R. Investigation of

the abuse liability of buspirone in alcohol-dependent patients. Am J Med

80:30-35, 1986.

Griffith, J.D.; Nutt, J.G.; and Jasinski, D.R. A comparison of fenfluramine and

amphetamine in man. Clin Pharmacol Ther 18:563-370, 1975.

Griffiths, R.R., and Balster, R.L. Opioids: Similarity between evaluations of

subjective effects and animal selfadministration results. Clin Pharmacol

Ther 25(5, Part 1):611-617, 1979.

Griffiths, R.R.; Bigelow, G.E.; and Henningfield, J.E. Similarities in animal and

human drug-taking behavior. In: Mello, N.K., eds. Advances In

Substance Abuse, Vol. 1, Greenwich, CT: JAI Press, 1980, pp. 1-90.

91
Griffiths, R.R.; Bigelow, G.E.; and Liebson, I. Human sedative selfadministration: Double-blind comparison of pentobarbital, diazepam,

chlorpromazine and placebo. J Pharmacol Exper Ther 210:301-310,

1979.

Griffiths, R.R.; Bigelow, G.E.; and Liebson, L.A. Human coffee drinking:

Reinforcing and physical dependence producing effects of caffeine. J

Pharmacol Exper Ther 239:416-425, 1986.

Griffiths, R.R., and Woodson, P.P. Caffeine physical dependence: A review of

human and laboratory animal studies. Psychopharmacology 94:437-451,

1988a.

Griffiths, R.R., and Woodson, P.P. Reinforcing properties of caffeine: Studies in

humans and laboratory animals. Pharmacol Biochem Behav 29:419-427,

1988b.

Haertzen, C.A. Development of scales based on patterns of drug effects, using

the Addiction Research Center Inventory (ARCI). Psychopharmacology

18:163-194, 1966.

Haertzen, C.A. An Overview of the Addiction Research Center Inventory Scales

(ARCI): An Appendix and Manual of Scales. National Institute on Drug

Abuse. U.S. DHEW Pub. No. (ADM)74-92, 1974.

Haertzen, C.A., and Hickey, J.E. Addiction Research Center Inventory (ARCI):

Measurement of euphoria and other drug effects. In: Bozarth, M.A., ed.

Methods of Assessing the Reinforcing Properties of Abused Drugs. New

York: Springer-Verlag, 1987, pp. 489-524.

Haertzen, C.A.; Hill, H.E.; and Belleville, R.E. Development of the Addiction

Research Center Inventory (ARCI): Selection of items that are sensitive

to the effects of various drugs. Psychopharmacologic 4:155-166, 1963.

Haertzen, C.A., and Hooks, N.T. Jr. Changes in personality (MMPI) and

subjective experience (ARCI) throughout a cycle of addiction to

morphine. J Nerv Ment Dis 148:606-614, 1969.

Harris, R.T.; Waters, W.; and McLendon, D. Evaluation of reinforcing capability

of delta-9-tetrahydrocannabinol in rhesus monkeys.

Psychopharmacologic 37(1):23-29, 1974.

Hatsukami, D.K.; Hughes, J.R.; Pickens, R.W.; and Svikis, D. Tobacco

withdrawal symptoms: An experimental analysis. Psychopharmacology

84(2):231-236, 1984.

Henningfield, J.E.; Chait, L.D.; and Griffiths, R.R. Effects of ethanol on

cigarette smoking by volunteers without histories of alcoholism.

Psychopharmacology 82:1-5, 1984.

Henningfield, J.E., and Goldberg, S.R. Nicotine as a reinforcer in human

subjects and laboratory animals. Pharmacol Biochem Behav 19(6):989-

992, 1983a.

Henningfield, J.E., and Goldberg, S.R. Stimulus properties of nicotine in animals

and human volunteers: A review. In: Seiden, L.S., and Balster, R.L.,

eds. Behavior Pharmacology. The Current Status. New York: Alan R.

Liss, 1985: pp. 433-449.

Henningfield, J.E.; Johnson, R.E.; and Jasinski, D.R. Clinical procedures for the

assessment of abuse potential. In: M.A. Bozarth, ed. Methods of

Assessing the Reinforcing Properties of Drugs. Berlin: Springer-Verlag,

1987, pp. 573-590.

92
Henningfield, J.E.; Miyasato, K.; and Jasinski, D.R. Cigarette smokers selfadminister intravenous nicotine. Pharmacol Biochem Behav 19(5):887-

890, 1983.

Henningfield, J.E.; Miyasato, K.; and Jasinski, D.R. Abuse liability and

pharmacodynamic characteristics of intravenous and inhaled nicotine. J

Pharmacol Exp Ther 234(1):1-2, 1985.

Henningfield, J.E.; Miyasato, K.; Johnson, R.E.; and Jasinski, D.R. Rapid

physiologic effects of nicotine in humans and selective blockade of

behavioral effects by mecamylamine. In: Harris, L.S., ed. Problems of

Drug Dependence, 1982. National Institute on Drug Abuse Research

Monograph No. 43, DHHS Pub. No. (ADM)83-1264. Washington, D.C.:

Supt. of Docs., U.S. Govt. Print. Off., 1983, pp. 259-265.

Higgins, S.T., and Stitzer, M.L. Acute marijuana effects on social conversation.

Psychopharmacology 89(2):234-238, 1986.

Himmelsbach, C.K. The morphine abstinence syndrome, its nature and treatment.

Ann Intern Med 15(5):829-839, 1941.

Himmelsbach, C.K., and Andrews, H.L. Studies on the modification of the

morphine abstinence syndrome by drugs. J Pharmacol Exp Ther 77(1):17-

23, 1943.

Hofmann, A. Chemistry of LSD: In: Sankar, S., ed. LSD - A Total Study.

Westbury, New York: PJD Publications Ltd., 1975, pp. 107-139.

Hoffmeister, F. Negative reinforcing properties of some psychotropic drugs in

drug-naive rhesus monkeys. J Pharmacol Exp Ther 192(2):468-477, 1975.

Hoffmeister, F., and Goldberg, S.R. A comparison of chlorpromazine,

imipramine, morphine and d-amphetamine self-administration in cocainedependent rhesus monkeys. J Pharmacol Exp Ther 187(1):8-14, 1973.

Hoffmeister, F., and Wuttke, W. Psychotropic drugs as negative reinforcers.

Pharmacol Rev 27(3):419-428, 1976.

Horst, K.; Buxton, R.E.; and Robinson, W.D. The effect of the habitual use of

coffee or decaffeinated coffee upon blood pressure and certain motor

reactions of normal young men. J Pharmacol Exp Ther 52:322-337, 1934.

Hughes, J.R., and Hatsukami, D. Signs and symptoms of tobacco withdrawal.

Arch Gen Psychiatry 43(3):289-294, 1986.

Isbell, H. Methods and results of studying experimental human addiction to the

newer synthetic analgesics. Ann NY Acad Sci 51(1):108-122, 1948.

Isbell, H.; Altschul, S.; Kometsky, C.H.; Eisenrnan, A.J.; Flanary, H.G.; and

Fraser, H.F. Chronic barbiturate intoxication. AMA Archives of

Neurology and Psychiatry. U.S. Department of Health, Education and

Welfare, Public Health Service, 1950, pp. 1-28.

Isbell, H.; Belleville, R.E.; Fraser, H.F.; Wikler, A.; and Logan, C.R. Studies on

lysergic acid diethylarnide (LSD-25) I. Effects in former morphine

addicts and the development of tolerance during chronic intoxication.

Arch Neurol Psychiatry (Chicago) 76:468-478, 1956.

Isbell, H.; Fraser, H.F.; Wikler, A.; Belleville, R.E.; and Eisenman, A.J. An

experimental study of the etiology of “rum fits” and delirium tremens.

Quart J Stud Alcohol 16:1-33, 1955.

Isbell, H., and Vogel, V.H. Drug addiction. Merck Manual (Edition 8). Rahway,

NJ: Merck and Company, 1948.

93
Rall, T.W.; and Murad, F., eds. Goodman and Gilman's The

Pharmacologic Basis of Therapeutics, 7th Ed. New York: MacMillan,

1985, pp. 532-581.

Jaffe, J.H. Drug addiction and drug abuse. In: Gilman, A.G.; Goodman, L.S.;

Jarbe, T.U.C., and Swedberg, M.D.B. Discriminative stimulus properties of

drugs: A brief history and a selective review. Scand J Psychol

(Supplement 1):72-78, 1982.

Jasinski, D.R. Assessment of the abuse potentiality of morphine-like drugs

(methods used in man). In: Martin, W.R., ed. Handbook of Experimental

Pharmacology, Volume 45/I. Drug Addiction I: Morphine. Sedative

Hypnotic and Alcohol Dependence. Heidelberg, West Germany:

Springer-Verlag, 1977, pp. 197-258. Jasinski, D.R. Human pharmacology

of narcotic antagonists. Br J Pharmacol 7:287S-290S, 1979.

Jasinski, D.R. Chemical Dependence. In: Harvey, A.M.; Johns, R.J.; McKusick,

V.A.; Owens, A.H., Jr.; and Ross, R.S., eds. 22nd Ed. The Principles and

Practice of Medicine. New York: Prentice Hall, 1988, pp. 1144-1148.

Jasinski. D.R., and Henningfield, J.E. Conceptual basis of replacement therapies

for chemical dependence. In: Pomerleau, O.F.; Pomerleau, C.S.;

Fagerstrom, K.O.; Henningfield, J.E.; Hughes, J.R., eds. Nicotine

Replacement; A Critical Evaluation. New York: Alan R. Liss, 1988, pp.

13-34.

Jasinski, D.R.; Johnson, R.E.; and Henningfield, J.E. Abuse liability assessment

in human subjects. Trends Pharmacol Sci 5:196-200, 1984.

Jasinski, D.R., and Nutt, J.G. Progress Report on the Assessment Program

NIMH Addiction Research Center. Committee on Problems of Drug

Dependence. Washington, D.C.: National Academy of Sciences, National

Research Council, 1972.

Jasinski, D.R.; Pevnick, J.S.; and Griffith, J.D. Human pharmacology and abuse

potential of the analgesic buprenotphine. Arch Gen Psychiatry 35:501-

516, 1978.

Jasinski, D.R., and Preston, K.L. Evaluation of tilidine for morphine-like

subjective effects and euphoria. Drug Alcohol Depend 18:273-292, 1986.

Jasinski, D.R.; Preston, K.L.; and Testa, M. Evaluation of the abuse potential of

transnasally given butorphanol in humans. The Pharmacologist 30:A196,

1988.

Jones, B.E., and Prada, J.A. Drug-seeking behavior during methadone

maintenance. Psychopharmacologia (Berlin) 41:7-10, 1975.

Jones, R.T. The pharmacology of cocaine. In: Grabowski, J.G., ed. Cocaine;

Pharmacology, Effects, and Treatment of Abuse, National Institute on

Drug Abuse Research Monograph No. 50. DHHS Pub. No. 84-1326.

Washington, D.C.: Supt. of Docs., U.S. Govt. Print. Off., 1984, pp. 34-53.

Jones, R.T., and Benowitz, N. The 30-day trip - Clinical studies of cannabis

tolerance and dependence. In: Braucle, M.C., and Szara, S., eds. The

. . Pharmacology of Marijuana. New York: Raven Press, 1976, pp. 627-642.

Jones, R.T.; Farrell, T.R.; and Herning, R.I. Tobacco smoking and nicotine

tolerance. In: N.A. Krasnegor, ed. Self Administratoin of Abused

Substances: Methods for Study, National Institute on Drug Abuse

Research Monograph No. 20. DHEW Pub. No. (ADM) 78-727.

Washington, D.C.: Supt. of Docs., U.S. Govt. Print. Off., 1978.

94
Kolb, L., and Himmelsbach, C.K. Clinical studies of drug addiction, III. A

critical review of the withdrawal treatments with method of evaluating

abstinence syndromes. Am J Psychiatry 94(4):759, 1938.

Langley, J.N. On the reaction of cells and of nerve-endings to certain poisons,

chiefly as regards the reaction of striated muscle to nicotine and to curari.

J Physiol (London) 33:374-413, 1905.

Levison, P.K.; Gerstein, D.R.; and Maloff, D.R., eds. Commonalities in

Substance Abuse and Habitual Behavior. Lexington, Massachusetts:

Lexington Books, 1983.

Lewin, L. Phantastica: Narcotic and Stimulating Drugs: Their Use and Abuse.

London: Kegan Paul and Trench, Ltd., 1931. Light, A.B., and Torrance,

E.G. Opium addiction VI - Effects of abrupt withdrawal followed by

readministration of morphine in human addicts, with special reference to

the composition of the blood, the circulation, and the metabolism. Arch

Intern Med (1):1-16, 1929a.

Light, A.B., and Torrance, E.G. Opium addiction: VIII - Effects of intramuscular

and intravenous administration of large doses of morphine to human

addicts. Arch Intern Med 44:376-394, 1929b.

Lindsley, D.B. Psychological phenomena and the electroencephalogram.

Electroencephalogr Clin Neurophysiol 4:443-456, 1952.

Lukas, S.E., and Jasinski, D.R. EEG power spectral effects of intravenous

nicotine administration in humans. Fed Proc 42: 1018, 1983.

Lukas, S.E., and Mendelson, J.H. Electroencephalographic activity and plasma

ACTH during ethanol-induced euphoria. Biol Psychiatry 23:141-148,

1988.

Lukas, S.E.; Mendelson, J.H.; Amass, L.; and Smith, R. Plasma delta9-

tetrahydrocannabinol (THC) levels during marijuana-induced EEG and

behavioral effects in human subjects. (Abstract). Pharmacologist

28(3):191, 1986b.

Lukas, S.E.; Mendelson, J.H.; Benedikt, R.A.; and Jones, B. EEG alpha activity

increases during transient episodes of ethanol-induced euphoria.

Pharmacol Biochem Behav 25:889-895, 1985a.

Lukas, S.E.; Mendelson, J.H.; Benedikt, R.A.; and Jones, B. Marijuana-induced

changes in EEG and P300 evoked responses in male volunteers.

Pharmacologist 27:235, 1985b.

Lukas, S.E.; Mendelson, J.H.; Benedikt, R.A.; and Jones, B. EEG, physiologic

and behavioral effects of ethanol administration. In: Harris, L.S., ed.

Problems of Drug Dependence 1985, National Institute on Drug Abuse

Research Monograph No. 67, DHHS Pub. No. (ADM) 86-1448.

Washington, DC.: Supt. of Docs., U.S. Govt. Print. Off., 1986a, pp. 209-

214.

Marks, M.J.; Burch, J.B.; and Collins, AC. Effects of chronic nicotine infusion

on tolerance development and nicotinic receptors. J Pharmacol Exp Ther

226(3):817-825, 1983.

Martin, W.R. General problems of drug abuse and drug dependence. In: Martin,

W.R., ed. Handbook of Experimental Pharmacology. Volume 45/I. Drug

Addiction I: Morphine. Sedative Hypnotic and Alcohol Dependence.

Heidelberg, West Germany: Springer-Verlag. 1977, pp. 3-40.

95
Martin, W.R., and Fraser, H.F. A comparative study of physiological and

subjective effects of heroin and morphine administered intravenously in

postaddicts. J Pharmacol Exp Ther 133(3):388-399, 1961.

Martin, W.R.; Thompson, W.O.; and Fraser, H.F. Comparison of graded single

intramuscular doses of morphine and pentobarbital in man. Clin

Pharmacol Ther 15:623-630, 1974.

Matejcek, M. Vigilance and the EEG: Psychological, physiological and

pharmacological aspects. In: Hermann, W.M., ed. EEG in Drug

Research. Stuttgart: Gustav Fischer, 1982, pp. 405-508.

McMillan, D.E.; Harris, L.S.; Frankenheim, J.M.; and Kennedy, J.S. 1-9-

transtetrahydrocannabinol in pigeons: Tolerance to the behavioral effects.

Science 169(3944):501-503, 1970.

Medical Economics Company. Physicians’ Desk Reference 1987. Oradell, NJ:

Medical Economics Company, Inc., 1988.

Mello, N.K. Some aspects of the behavioral pharmacology of alcohol. In: Efram,

D.H., ed. Psychopharmacology: A Review of Progress 1957-1967, PHS

Publication No. 1836, 1968, pp. 787-809.

Mendelson, J.H.. and Mello, N.K. Reinforcing properties of oral

tetrahydrocannabinol, smoked marijuana, and nabilone: Influence of

previous marijuana use. Psychopharmacology 83(4):351-356, 1984.

Morrison, C.F., and Stephenson, J.A. Nicotine injections as the conditioned

stimulus in discrimination learning. Psychopharmacologia 15:351-360,

1969.

Nemeth-Coslett , R.; Henningfield, J.E.; O’Keefe, M.K.; and Griffiths, R.R.

Nicotine gum: Dose-related effects on cigarette smoking and subjective

ratings. Psychopharmacology 92:424-430, 1987.

Overton, D.A. Discriminative control of behavior by drug states. In: Thompson,

T., and Pickens, R., eds. Stimulus Properties of Drugs. New York:

Appleton-Century-Crofts, 1971, pp. 87-110.

Overton, D.A., and Batta, S.K. Relationship between abuse liability of drugs and

their degree of discriminability in the rat. In: Pickens, R., and Thompson,

T. Cocaine-reinforced behavior in rats: Effects of reinforcement

magnitude and fixed-ratio sire. J Pharmacol Exp Ther 161(1):122-129,

1968.

President’s Advisory Commission on Narcotic and Drug Abuse. The President's

Advisory Commission on Narcotic and Drug Abuse. Washington, D.C.:

Supt. of Docs., U.S. Govt. Print. Off., 1963.

Rao, C.R. Advanced Statistical Methods in Biometric Research. New York: John

Wiley, 1952.

Schuster, C.R.; Fischman, M.W.; and Johanson, C.E. Internal stimulus control

and subjective effects of drugs. In: Thompson, T., and Johanson, C.E.,

eds. Behavioral Pharmacology of Human Drug Dependence, National

Institute on Drug Abuse Research Monograph No. 37. DHHS Pub. No.

(ADM) 81-1137. Washington, D.C.: Supt. of Docs., U.S. Govt. Print.

Off., 1981, pp. 116-129.

Siler, J.F.; Sheep, W.L.; Bates, L.B.; Clark, G.F.; Cook, G.W.; and Smith, W.A.

Marijuana smoking in Panama military. Military Surgeon 73:269-280,

1933.

96
Spyraki, C.; Fibiger, H.C.; and Phillips, A.G. Cocaine-induced place preference

conditioning: Lack of effects of neuroleptics and 6-hydroxydopamine

lesions. Brain Res 253(1-2): 195-203, 1982.

Stewart, R.R., and Grupp, L.A. Some determinants of the motivational properties

of ethanol in the rat: Concurrent administration of food or social stimuli.

Psychopharmacology 89:43-50, 1985.

Stitzer, M.L.; Griffiths, R.R.; Bigelow, G.E.; and Liebson, I.A. Social stimulus

factors in drug effects in human subjects. In: Thompson, T., and

Johanson, C.E., eds. Behavioral Pharmacology of Human Drug

Dependence, National Institute on Drug Abuse Research Monograph No.

37. DHHS Pub. No. (ADM) 81-1137. Washington, D.C.: Supt. of Docs.,

U.S. Govt. Print. Off., 1981, pp. 130-154.

Tatum, A.L., and Seevers, M.H. Experimental cocaine addiction. J Pharmacol

Exp Ther 36:401-410. 1929.

Terry, C.E., and Pellens, The Opium Problem. Montclair, NJ: Patterson

Smith, 1970.

Thompson, T., and Johanson, C.E., eds. Behavioral Pharmacology of Human

Drug Dependence, National Institute on Drug Abuse Research Monograph

No. 37. DHHS Pub. No. (ADM) 81-1137. Washington, D.C.: Supt. of

Docs., U.S. Govt. Print. Off., 1981.

Thompson, T., and Schuster, C.R. Morphine self-administration, food-reinforced

and avoidance behaviors in rhesus monkeys. Psychopharmacologic 5:87-

94, 1964.

Thompson, T., and Schuster, C.R. Behavioral Pharmacology. Englewood Cliffs,

NJ: Prentice Hall, Inc., 1968.

Thompson, T., and Unna, K.R., eds. Predicting Dependence Liability of

Stimulant and Depressant Drugs. Baltimore, MD: University Park Press,

1977, pp. 125-135.

United States Department of Health and Human Services. The Health

Consequences of Smoking: Nicotine Addiction, a report of the Surgeon

General (DHHS Pub. No. 88-406). Washington, D.C.: Supt. of Docs.,

US. Govt. Print. Off., 1988.

Wallace, R.K. Physiological effects of transcendental meditation. Science

167(3926):1751-1754, 1970.

Weil, A.T.; Zinberg, N.E.; and Nelsen, J.M. Clinical and psychological effects of

marijuana in man. Science 162:1234-1242, 1968.

Winger, G., and Woods, J.H. The reinforcing property of ethanol in the rhesus

monkeys I. Initiation, maintenance and termination of intravenous

ethanol-reinforced responding. Ann NY Acad Sci 215:162-165, 1973.

Wood, D.M., and Emmett-Oglesby, M.W. Evidence for dopaminergic

involvement in tolerance to the discriminative stimulus properties of

cocaine. Eur J Pharmacol 138:155-157, 1987.

Woolverton, W.L., and Schuster, C.R. Behavioral tolerance to cocaine. In:

Krasnegor, N.A., ed. Behavioral Tolerance: Research and Treatment

Implications, National Institute on Drug Abuse Research Monograph No.

18. DHEW Pub. No. (ADM) 78-551. Washington, D.C.: Supt. of Docs.,

U.S. Govt. Print. Off., 1977, pp. 127-141.

World Health Organization 5th Review of Psychoactive Substances for

International Control. Geneva: WHO November 16-20, 1981.

97
ACKNOWLEDGMENTS

Table 3 is modified from one that was originally developed by R. J. Lamb

and J.E. Henningfield for use in a report of the U.S. Surgeon General

(USDHHS 1988).

AUTHORS

Donald R. Jasinski, M.D.

Associate Professor of Medicine

The Johns Hopkins University School of Medicine

Center for Chemical Dependency

Francis Scott Key Medical Center

Baltimore, Maryland 21224

Jack E. Henningfield, Ph.D.

Associate Professor of Behavioral Biology

Department of Psychiatry and Behavioral Sciences

The Johns Hopkins University School of Medicine

Addiction Research Center

National Institute on Drug Abuse

P.O. Box 5180

Baltimore, Maryland 21224

98
APPENDIX A

Items of single-dose opiate questionnaires (from Jasinski 1977).

Subject rating Observer rating

1. Do you feel the medicine? Yes No

2. Drug is most like what drug

listed below (check 1):

a) Blank

b) “Dope” (opiate or potent

analgesics)

c) Cocaine

d) Marijuana (pot)

e) Barbiturate (“goofballs”)

f) Alcohol*

g) Benzedrine (amphetamine,

speed, bennies. methedrine)

h) LSD (acid)*

i) Thorazine*

j) Miltown or Librium*

k) Other

3. Check each of the sensations

you feel:

a) Normal (no change)

b) Turning of stomach (1)

c) Skin itchy (2)

d) Relaxed (1)

e) “Coasting” (2)

f) “Soapbox” (1)

g) Pleasant sick (1)

h) Drive (2)

i) Sleepy (2)

j) Nervous (1)

k) Drunken (1)

1) Other

4. My liking for this drug is most nearly

described by which of the following:

a) Not at all (0)

b) Slight (1)

c) Moderate (2)

d) A lot (3)

e) An awful lot (4)

f) Other

Any evidence of drug effect? Yes No

Behavior is like that seen after:

a) Blank

b) “Dope” (opiate or potent

analgesics)

c) Cocaine

d) Marijuana (pot)

e) Barbiturate (“goofballs”)

f) Alcohol*

g) Benzedrine (amphetamine,

speed, bennines, methedrine)

h) LSD (acid)*

i) Thorazine*

j) Miltown or Librium*

k) Other

Check each item which you think

the patient shows:

a) Normal

b) Scratching (2)

c) Red eyes (1)

d) Relaxed (1)

e) “Coasting” (2)

f) “Soapbox” (1)

g) vomiting (1)

h) Nodding (2)

i) Sleepy (1)

j) Nervous (1)

k) Drunken (1)

1) Other

How much do you think patient

liked the effects of this drug?

a) Not at all (0)

b) Slight (1)

c) Moderate (2)

d) A lot (3)

e) An awful lot (4)

f) Other

( ) The figures given following items of questions 3 and 4 are the weights given

to the particular responses for the purpose of calculating the opiate symptom, opiate

sign, subject’s “liking” and observer’s “1iking”scores (Martin and Fraser 1961).

* Items were not in the original single-dose opiate questionnaire.

99
APPENDIX B

The forty items from the Addiction Research Center Inventory utilized in multiplescale questionnaires to distinguish the subjective effects of nalorphine andcyclazocine

from those of morphine (from Jasinski 1977).

Morphine-Benzedrine Group Pentobarbital- LSD-Specific

WBG) Chlorpromazine-Alcohol

Group(PCAG)

I would be happy all the

time if I felt as I do now.

I feel as if I would be more

popular with people today.

Today I say things in the

easiest possible way.

*I feel more clear-headed

than dreamy.

Things around me seem more

pleasing than usual.

I have a pleasant feeling in

my stomach.

I feel a very pleasant

emptiness.

I fear that I will lose

the contentment I now have.

I feel in complete harmony

with the world and those

about me.

I feel less discouraged

than usual.

I can completely appreciate

what others are saying when

I am in this mood.

I would be happy all the

time if I felt as I feel

now.

I am full of energy.

Iaminthemoodtotalk

about the feeling I have.

I feel so good that I know

other people can tell it.

I feel as if something

pleasant had just happened

to me.

*My speech is slurred.

I am not as active as usual

I have a feeling of just

dragging along rather than

coasting.

*I feel more clearheaded than dreamy

(answered negatively).

I feel sluggish.

*A thrill has gone

through me one or more

times since I started

the test (answered

negatively).

My head feels heavy.

I feel like avoiding

people although I usually

do not feel this way.

I feel dizzy.

*I am full of energy

(answered negatively).

People might say that I am

a little dull today.

It seems harder than usual

to move around.

I am moody.

*I feel drowsy.

I feel more excited than

dreamy (answered

negatively).

*I have a weird

feeling.

I have a

disturbance in my

stomach.

I feel an increasing

awareness of bodily

sensation.

I would be happy all

the time if I felt

as I do now (answer in

negatively).

I feel anxious and

upset.

*A thrill has gone

through me one or

more times since

I started the

test.

My movements are

free, relaxed

and pleasurable

(answered

negatively).

I feel very patient

(answer negatively).

I have unusual

weakness of my

muscles.

Some parts of my

body are tingling.

It seems I’m

spending longer than

I should on each of

these questions.

My hands feel

clumsy.

I notice my hand

shakes when I try to

write.

* I feel drowsy

(answered

negatively).

* contained in more than one scale but scored for the appropriate scale depending

upon the positive or negative answers.

100
CHAPTER 6

Drug Discrimination: Methods for Drug

Characterization and Classification

George E. Bigelow, Ph.D.

Kenrie L. Preston, Ph.D.

INTRODUCTION

The prototypic method for assessing the abuse liability of novel drugs is

to assess the extent to which their effects are similar to the effects of

known drugs. Test drugs are compared to reference drugs of known

abuse liability, and drugs with similar effects are considered likely to

have similar abuse liabilities. This approach, of comparing the test drug

to a known reference drug, is the methodology developed and used for

several decades by the USPHS Addiction Research Center. One of the

useful elements of that methodology has been a question asking subjects

to identify the pharmacological class to which test drugs are most similar

— i.e., is the test drug morphine-like, barbiturate-like, amphetaminelike, etc? One limitation of this question is that it relies upon subjects’

uncontrolled and variable prior experience with the various drug classes.

The approach to be discussed here - the use of a behavioral drug

discrimination methodology - avoids this problem by providing explicit,

standardized training experience with each of the reference drugs prior

to asking subjects to evaluate the similarity of test drugs to those reference

standards.

In human subjects the drug discrimination methodology provides a unique

opportunity to assess the similarity of test compounds to reference

compounds in multiple dimensions and, thereby, to assess the

comparability of drug characterization and classification decisions

suggested by different measures. The results of drug discrimination

testing can be compared with the results of assessing the profile of acute

effects on other subjective, behavioral and physiological indices; these

other measures can be conveniently collected concurrent with drug

discrimination training and testing. Perhaps the most interesting of these

101
concurrently-available data are measures of the subjective effects produced

by the drugs. Subjective effects appear to be related to abuse potential,

and their measurement has constituted a significant element of traditional

abuse liability testing in humans (Jasinski 1977). The discriminative

stimulus effects of drugs have been considered analogous to their subjective

effects (Holtzman 1985). Human drug discrimination studies provide a

unique opportunity to assess this relationship.

DRUG DISCRIMINATION PROCEDURES

The methodology for drug discrimination testing is derived from the

animal laboratory, where it has become one of the mostly widely used

paradigms in behavioral pharmacology (Stolerman and Shine 1985;

Stolerman et al., 1982). Investigators face the problemof asking subjects

without prior drug experience to assess the similarity of test drugs to

other, known drugs; and, of course, the added problem that in the animal

laboratory this similarity-assessment question is asked of nonverbal

subjects. Therefore, two elements have been necessary for investigators

to obtain this assessment — first, providing the experience of

pharmacological exposure to the reference drugs against which similarity

is to be judged; and second, training a behavioral response that allows the

subject to indicate the degree of similarity of test drugs to the reference

drugs. The behavioral procedure used has involved operant conditioning

procedures (i.e., response contingent reinforcement) to train subjects to

emit different responses in the presence of different drug conditions. One

of the reference, or training drugs, is administered shortly prior to each

experimental session, and is considered to act as a drug stimulus. For

each training drug stimulus there is a specific response that will lead to

reinforcement; other responses are unreinforced. Two or three training

drugs are administered in a mixed order across sessions so that subjects

can learn to make the correct response in the presence of each training

drug stimulus. As with traditional sensory discriminations subjects rapidly

learn correct discriminative performance (Overton 1984).

The behavioral procedure for drug discrimination training is presented

schematically in figure 1. Most drug discrimination studies are conducted

with only two alternatives — typically one active drug versus placebo.

Figure 1, however, illustrates the procedure for a more complex threechoice discrimination.

102
Figure 1: Schematic representation of the behavioral contingencies used in training

and maintaining a three-choice drug discrimination performance. Each drug

stimulus is associated with a distinctive response which, if made following the

appropriate drug treatment, leads to reinforcement (monetary payment in the case

of the present studies with human volunteers); incorrect responses are unreinforced.

OPIOID DRUG DISCRIMINATION

The discriminative stimulus properties of opioid drugs have been

extensively studied in the animal laboratory (Holtzman 1983). To illustrate

the use and value of drug discrimination methods in humans, we will rely

primarily upon our own work concerning discrimination of opioid agonists,

103
antagonists, and mixed agonist-antagonists with opioid-experienced postaddict volunteers. Detailed descriptions of these methods are provided

elsewhere (Preston et al., 1987; Bickel et al., in press; Preston and Bigelow,

in press); the emphasis here will be on the unique contributions that the

drug discrimination methodology can make to the task of characterizing

and categorizing the nature of opioid drug effects and to assessing their

likely abuse liability. The studies are conducted in a residential laboratory

setting where the volunteer participants remain throughout the

experiments.

Method

These studies have generally utilized a three-drug discrimination procedure

as illustrated in figure 1. In this procedure, recognition of and differential

responding to each of three different pharmacological stimuli is trained.

The drug stimulus conditions have included saline placebo plus two

different active opioids. The active opioid training drugs have been

chosen to represent opioids acting via different opioid receptor

mechanisms. Hydromorphone has been used as the prototypic morphinelike mu-receptor agonist. Pentazocine has been used as the prototypic

kappa-receptor agonist. Specifically, in the work to be described below,

a discrimination has been trained between intramuscularly administered

saline, hydromorphone HCl 3 mg, and pentazocine lactate 45 mg.

Studies have proceeded in three phases: training, test of acquisition, and

testing. Sessions of 1-2 hour duration are scheduled daily, and subjects

remain in a residential laboratory setting throughout the approximately

8 week study duration. Subjects are paid for their research participation,

and the amount of their payment is contingent upon their accurately

discriminating the training drugs; all earnings are paid after completion

of the study. Subjects are told at the study outset that their task is to attend

carefully to the drug effects and to try to learn to discriminate among

drugs, which are identified only by arbitrary letter codes — e.g., A, B, C.

In the training phase subjects receive, in a random order, two sessions of

exposure to each of the three training drugs; at the start of each of these

sessions subjects are informed of the letter code of the drug they are

receiving and then respond to that letter code during the session.

During the subsequent test of acquisition phase, subjects again receive, in

randomorder, two sessions of exposure to each of the three training drugs

with no prior information provided; in these sessions subjects’ earnings

are contingent upon their accurate identification of the drugs by letter

code. At the end of each session a codeenvelope is opened which identifies

104
the administered drug by letter code, thus providing confirmation of the

subject’s discrimination response as well as indicating the amount of

money earned. This procedure provides a test of the accuracy of the

acquired discrimination as well as continued training.

Following acquisition of the discrimination, subjects enter the test phase

during which novel drugs or novel doses of the training drugs are

administered to assess their similarity to the three training drug conditions.

Further test of acquisition sessions with the training drugs/doses are

interspersed during this phase to provide continued training and contingent

reinforcement for correct drug discrimination performance. In trials with

novel test conditions there is no “correct” response, so at the session

conclusion subjects are informed this was a test trial and the drug identity

can not be revealed; they are paid in proportion to the accuracy of their

discrimination on the most recent test of acquisition trials.

Discrimination Performance

That this opioid drug discrimination is rapidly and accurately learned by

human volunteers is illustrated in figure 2, which shows the average drug

discrimination performance during the six-session test of acquisition phase

for six nondependent opioid post-addict subjects. After only two prior

training exposures to each of the drug conditions, both saline and

hydromorphone were correctly discriminated 100 percent of the time.

Pentazocine showed some stimulus overlap with hydromorphone but

was correctly discriminated 75 percent of the time.

Relation to Subjective Indices

One of the great strengths of the drug discrimination procedure in humans

is that it permits the concurrent assessment of a wide range of subjective

and objective indices of acute drug effects that are themselves commonly

used in assessing the likely abuse potential of drugs. One of the commonly

used subjective effect questions in such assessments, and acomponent of

the Single Dose Questionnaire (SDQ) developed by the USPHS Addiction

Research Center for opioid abuse liability assessments (Jasinski 1977),

is drug class identification. In this procedure subjects are simply asked

what drug class they think they have received — e.g., opiate, barbiturate,

CNS stimulant, etc. On its surface it might appear that the drug

discrimination procedure is simply a complicated way of asking this

question. Therefore, it is important to emphasize that the drug

discrimination procedure is not functionally identical to such verbal

subjective-identification questions; it can yield drug characterizations

and categorizations that differ from those provided by verbal techniques.

105
Figure 2: Distribution of drug discrimination responding by nondependent human

opioidpost-addicts to the three training drug conditionsduring the test-of-acquisition

phase. Each column shows the mean percent of responding allocated to each of the

three response alternatives. In each panel the correct response category is darkened.

The drug conditions were saline, hydromorphone 3 mg, and pentazocine 45 mg, given

intramuscularly.

106
Figure 3: Comparison of behavioral drug discrimination performance (top panel)

with two subjective effect indices — categorical identification as an opiate on a drug

identification questionnaire (middle panel), and rated similarity to the training dose

of 3 mg hydromorphone on a 100-point visual analog scale (bottom panel). Saline (S)

and a range of hydromorphone doses were tested.

107
Figure 4: Comparison of behavioral drug discrimination performance (top panel)

with two subjective effect indices — categorical identification as an opiate on a drug

identification questionnaire (middle panel), and rated similarity to the training dose

of 45 mg pentazocine on a 100-point visual analog scale (bottom panel). Saline (S)

and a range of pentazocine doses were rested.

108
pentazocine, respectively, the dose-response relation for three different

types of drug identification procedures. These data were collected during

test phase exposure to a range of doses of the the two active training drugs.

The top panel in each figure shows the trained and reinforced drug

discrimination performance; in both cases as the dose of the test drug

increased it was discriminated as being more similar to the training drug,

with test doses equal to the training dose being correctly discriminated

100 percent of the time. The other two panels in each figure show the

results from two different verbal-categorization responses, neither of

which had received explicit training and reinforcement.

The center panel in each figure shows the percent of identifications as an

opiate on a drug class identification questionnaire. For hydromorphone

there is good correspondence between behavioral drug discrimination

performance and subjective drug class identification, but this is not true

for pentazocine. Pentazocine is accurately discriminated in a dose-related

fashion as pentazocine-like, but it is not systematically identified as an

opiate.

The bottom panel in each figure shows the subjective rating on a 100-

point visual analog scale of the similarity of the test dose to the training

drug (identified by letter code); e.g., “how much is it like Drug A?”. For

neither hydromorphone nor pentazocinedoes this nonreinforced subjective

assessment of similarity bear a close correspondence to the trained and

reinforced behavioral discrimination performance.

Assessment of Novel Test Conditions

The purpose of training the 3-way opioid drug discrimination that we

have been discussing was to utilize it to assess the profiles of action of a

variety of opioid mixed agonist/antagonists. It is our belief that the drug

discrimination procedure can make especially unique contributions to

the task of characterizing and categorizing drugs with complex and

overlapping profiles of action. This is a task that can be quite difficult

when based upon examination of acute drug effects on a wide range of

subjective and objective indices, i.e., the traditional method of assessing

the similarity of the acute profiles of effects.

To illustrate the value of the drug discrimination procedure it may be

useful to begin by illustrating the difficulty one can face in making decisions

about the similarities and differences among drugs based upon examining

the profiles of their acute effects. The data we present here are based upon

test phase assessments of a range of doses of the two active training drugs

109
(hydromorphone and pentazocine) as well as three marketed opioid mixed

agonist/antagonists — butorphanol, nalbuphine, and buprenorphine.

All five of these drugs produced statistically significant dose-related

pupillary constriction (data not shown), as is characteristic of opioid

analgesics. However, their profiles of subjective effects differed

considerably. Their profiles of action over a range of doses on three

different subjective effect measures are shown in figure 5.

The left hand column of figure 5 presents the dose-effect functions for

responses on an adjective rating scale questionnaire designed to detect

typical morphine-like opioid agonist subjective effects. Only

hydromorphone produced statistically significant effects on this variable,

but butorphanol achieved borderline significance (p=0.067), suggesting

that, of these five drugs, hydromorphone and butorphanol are most similar

to one another on this dimension.

The center column of figure 5 presents the dose-effect functions for

responses on a 100-point visual analog scale rating of subjective liking

of the drug effect. Both hydromorphone and pentazocine produced

statistically significant effects on this variable, and buprenorphine achieved

borderline significance (p=0.053), suggesting that, of these five drugs,

hydromorphone, pentazocine, and buprenorphine are most similar to one

another on this dimension.

The right hand column of figure 5 presents the dose-effect functions for

responses on the Lysergic Acid Diethylamide (LSD), or “dysphoria,”

scale of the Addiction Research Center Inventory (ARCI). Pentazocine,

butorphanol, and buprenorphine each produced statistically significant

effects on this variable, suggesting that, of these five drugs, these three

are most similar to one another.

The point to be made from the above data is that examination of the acute

profile of effects of test drugs on multiple variables can result in confusing

and contradictory patterns of similarities and differences. While this

method is extremely valuable in assessing and comparing drug effects, it

is by no means a simple method for reaching conclusions about the

characterization and categorization of test drugs.

Nor does the method of asking subjects to identify the drug class they

received always provide an accurate characterization or categorization of

the test compound. Test drugs may be identified as belonging to incorrect

pharmacological classes. Table 1 summarizes subjects’ answers to a

pharmacological class questionnaire administered during the test phase

110
Figure 5: Profile of subjective effects for five opioid analgesics assessed over a range

of doses during a drug discrimination study in nondependent human opioid postaddicts. † p<0.10; * p<0.05; ** p<0.01; *** p<0.001

111
pharmacological class questionnaire administered during the test phase

of our assessment of a range of doses of hydromorphone, pentazocine,

butorphanol, nalbuphine, and buprenorphine. The pharmacological class

questionnaire responses are collapsed across all test drugs and doses but

are summarized separately according to the subjects’ behavioral drug

discrimination response. As can be seen, whenever a test drug condition

was discriminated as being either saline-like or hydromorphone-like the

drug class questionnaire response tended to show good agreement with

the discrimination performance. Drug classes were labeled as 97 percent

“blank” and 76 percent “opiate” when discriminated as being saline-like

or hydromorphone-like, respectively. However, there was no agreeement

between the pharmacological class questionnaire response and the drug

discrimination response when the test condition was discriminated as

being pentazocine-like. Pharmacological class identifications covered

quite a broad range, with Benzodiazepine being the most common

identification, but also with substantial identifications as Stimulant,

Hallucinogen, or Opiate Antagonist; test conditions discriminated as

pentazocine-like were only rarely identified as Opiate.

Table 1. Relationship between behavioral drug discrimination and

subjective drug class identification

Behavioral Discrimination1

Subjective Saline- Hydromorphone- PentazocineDrug Class Like Like Like

Identification N=78 N=71 N=lll

Blank 97 1 2

Opiate 3 76 3

Benzodiazepine 18 27

Barbiturate 4 7

Stimulant 22

Hallucinogen 18

Antidepressant 5

Opiate Antagonist 17

1

 Entries are percents of each column; columns may not total to 100 due to

rounding. For clarity 0 percent entries are not shown.

112
The results for the behavioral drug discrimination performance for the

five test drugs (collected in the same sessions as the above acute effect

data) are presented in figure 6. The left hand column shows the extent of

saline-appropriate responding as a function of dose; all five drugs are

discriminated as being significantly not saline-like. The center column

shows the extent of hydromorphone-appropriate responding as a function

of dose. Only hydromorphone is discriminated as being significantly

hydromorphone-like; both nalbuphine and buprenorphine show partial,

but statistically nonsignificant, generalization to the hydromorphone

stimulus. The right hand column shows the extent of pentazocineappropriate responding as a function of dose. Both pentazocine and

butorphanol show statistically significant complete generalization to the

pentazocine training stimulus. Bothnalbuphine and buprenorphine show

partial generalization to the pentazocine stimulus; in the case of nalbuphine

this reaches borderline statistical significance (p=0.058).

Conclusions

Thus, these behavioral drug discrimination results lead us to conclude

that none of the tested mixed agonist/antagonists is completely

hydromorphone-like, and that only butorphanol completely shares the

stimulus properties of pentazocine. Nalbuphine and buprenorphine are

both judged as having stimulus properties that partially overlap those of

both hydromorphone and pentazocine.

Animal laboratory drug discrimination studies indicate that opioids’

stimulus properties appear to be related to their profile of opioid receptor

activity. Therefore, our above drug discrimination data, in combination

with data from subsequent studies examining other trained opioid

discriminations, as well as data from other sources have led us at present

to conceptualize the actions of these various opioids as follows:

hydromorphone appears to be a pure mu-receptor agonist; butorphanol

appears to be a kappa-receptor agonist and a mu-receptor antagonist;

buprenorphine appears to be a mu-receptor partial agonist; pentazocine

and nalbuphine appear to be mu-receptor partial agonists and kappa

receptor agonists. This conceptualization remains open to modification

on the basis of additional data, and it may well be true that the mureceptor/kappa-receptor model of opioid activity is insufficient to account

for the complexity of opioid drug actions. However, the primary point

to be made here is the procedural one, that the drug discrimination

methodology in humans can serve as a valuable complement and adjunct

to other procedures for characterizing and categorizing drugs, especially

drugs with complex and overlapping profiles of activity.

113
Figure 6: Profile of behavioral drug discrimination responding for five opioid

analgesics assessed over a range of doses in nondependent human opioid postaddicts. † p<0.10; * p<0.05 ** p<0.01; *** p<0.001

114
OTHER DRUG DISCRIMINATIONS

While we have used our opioid discrimination studies as the vehicle for

discussing drug discrimination methods, application of the methods is by

no means limited to the opioids; rather, the methods can be extended to

a broad range of pharmacological classes. At this time we do not know

the full breadth of drug classes for which drug discriminations can be

established in humans, simply because the efforts have not yet been

made. Data from the animal laboratory certainly indicate that drug

discriminations can be established with a very broad range of drug types,

probably including all of the drugs of abuse. The expectation is that the

same will be true for humans.

Besides opioid drug discriminations human studies so far have documented

the establishment of drug discriminations for nicotine delivered in tobacco

smoke (Kallman et al., 1982), for -THC delivered in marijuana smoke

(Chait et al., 1988), for caffeine delivered orally (Griffiths and Evans,

personal communication), and for d-amphetamine delivered orally (Chait

et al., 1986a).

Kallman et al., (1982) trained regular tobacco cigarette smokers to

discriminate between two cigarettes which differed only in their nicotine

yields. The smokers were one-hour abstinent from tobacco at the time of

training and smoked complete cigarettes in their normal fashion. Subjects

received single sampling exposures to each cigarette (identified by letter

code) prior to the start of discrimination testing. The ease of learning the

discrimination was directly related to the difference in nicotine yields of

the two cigarettes. The discrimination between the two moderate-yield

cigarettes (0.28 vs 0.69 mg nicotine) was not well learned, being mastered

by only 27 percent of subjects. In contrast, the discrimination between

the high-yield and low-yield cigarettes (1.30 vs 0.14 mg nicotine) was

readily learned, being mastered by 94 percent of subjects; in addition, this

discrimination was rapidly learned, apparently being immediately

established with only the single training exposures to each cigarette.

These results further document the speed with which humans can learn

drug discriminations.

Chait et al., (1988) trained experienced marijuana users to discriminate

between the effects of smoked marijuana (4 puffs) containing 2.7 percent

-THC versus 0 percent THC and then tested with two lower doses

(concentrations) of marijuana cigarette. All subjects learned the

discrimination. Test conditions with 0.9 percent and 1.4 percent THC

marijuana cigarettes resulted, respectively, in 20 percent and 100 percent

115
marijuana-appropriate responses. Thus, the drug discrimination behavior

was appropriately dose-related, with the 1.4 percent dose completely

generalizing to the 2.7 percent training condition, and the 0.9 percent

dose failing to generalize and being discriminated as predominantly

placebo-like. These data further document the dose-related generalization

of drug stimulus effects to the training drug conditions.

In as yet unpublished work in our laboratory Griffiths and Evans (personal

communication) have established discriminations between orally

administered caffeine versus placebo in humans. Participants are normal

volunteers; they are experienced caffeine users (in the sense of their being

usually exposed to caffeine in the normal dietary range), but they maintain

a caffeine-free diet during the drug discrimination study. Discrimination

of 100 mg of caffeine versus placebo has been established in 100 percent

of participants. Since this dose falls within the normal dietary range for

caffeine, these results serve to emphasize the subtlety of drug effects for

which effective behavioral discriminations can be established.

The most comprehensive series of human drug discrimination studies yet

published is that of Chait and colleagues concerning discrimination of

orally administered d-amphetamine 10 mg versus placebo. A description

of their methodology is provided by Chait et al., (1984). Participants in

these studies have been normal volunteers without histories of drug abuse.

Sessions occurred 3 days per week. Subjects received single sampling

exposures to each of the training drugs (identified only by letter code) and

then, over the next six sessions, were asked to discriminate which one

they had received that day. Volunteers participated on an ambulatory

basis, in which they reported to the laboratory in the morning to receive

a study drug and then went about their normal daily activities. They filled

out subjective effect questionnaires at 1, 3, and 6 hours following drug

administration and, at hour 6, telephoned the experimenter to provide

their drug discrimination response (i.e., identifying the study drug by

letter code). Those who correctly learned the discrimination progressed

on to a test phase in which they were tested with novel drugs and/or with

novel doses of the training drug.

Three studies have been reported in this series; one (Chait et al., 1985)

tested a range of d-amphetamine doses (2.5,5, and 10 mg) and a single

dose of diazepam (10mg); another (Chait et al., 1986a) tested the anorectics

phenmetrazine (25 and 50 mg) and fenfluramine (20 and 40 mg); and the

other (Chait et al., 1986b) tested the anorectics phenylpropanolamine (25

and 75 mg) and mazindol (0.5 and 2 mg). Results of all three studies are

summarized in figure 7 (from Chait et al., 1986c), which shows the percent

d-amphetamine-appropriate discrimination responses during the test phase

116
Figure 7: Percent of amphetamine-like discrimination responses by normal human

volunteers trained to discriminate between placebo (P) and 10 mg d-amphetamine

p.o. (10 AMP) is shown for the two training drugs and for a range of test drugs -

primarily anorectics. MAZ, mazindol; AMP, d-amphetamine; DZ, diazepam; FFL,

fenfluramine; PMT, phenmetrazine; PPA, phenylpropanolamine. The data summarize

three experiments and are redrawn from Chait et al., (l986c).

d-amphetamine-appropriate discrimination responses during the test phase

for the training conditions and each of the test conditions. The dashed

horizontal line at 50 percent in the figure represents the “chance” level in

this 2-choice procedure. The discrimination between 10 mg damphetamine and placebo was well-maintained throughout the test phase,

averaging better than 80 percent correct. All of the anorectics, except

fenfluramine, generalized to the d-amphetamine stimulus (>75 percent

amphetamine-appropriate responses), at least at their highest dose. Neither

fenfluramine nor 10 mg diazepam generalized to the d-amphetamine

stimulus.

These data from the studies of anorectic drugs by Chait and co-workers

raise questions concerning the utility of human drug discrimination

procedures for the assessment of abuse liability. In these studies the

higher doses of both mazindol and phenylpropanolamine were

discriminated as being d-amphetamine-like; but neither of these drugs

appears in other contexts to possess amphetamine-like abuse liability or

to produce amphetamine-like subjective effects. Therefore, we discuss

below several factors that may be relevant to using drug discrimination

procedures in efforts to assess abuse potential.

117
RELATION TO ABUSE LIABILITY ASSESSMENT

First, it must be emphasized that drug discrimination procedures assess

the stimulus properties of drugs, not their reinforcing properties. These

are not necessarily the same thing; drugs with similar stimulus properties

may have differing reinforcing effects, just as drugs with differing stimulus

properties may have similar reinforcing effects. Thus, the aspect of the

drug stimulus complex that individuals use to learn a drug discrimination

is not necessarily the same as the aspect(s) of drug effects related to abuse

liability.

Second, it may be that studies intending to assess the dimension of abuse

liability should use as subjects individuals with personal histories of drug

abuse rather then relatively drug-naive non-abusers. The majority of data

documenting the ability of clinical testing to predict abuse liability has

been developed with subjects with extensive drug abuse histories (Jasinski

1977). However, in the Chait et al., anorectic studies discussed above, in

which the non-abused drugs mazindol and phenylpropanolamine were

discriminated as being amphetamine-like, the subject participants were

specifically selected for absence of a history of drug abuse. While

assessment of drug effects in normal, non-drug-abuser populations is

scientifically very interesting, its relevance to the assessment of abuse

liability remains uncertain at this time. It is possible that drugs may have

different stimulus properties in abusers versus non-abusers, or that

discrimination behavior might come under control of different aspects of

the drug stimulus complex in the two different populations. One certainly

wonders whether experienced stimulant abusers would also discriminate

mazindol and phenylpropanolamine as being amphetamine-like. This

issue of the utility of non-drug-abuser populations for assessing abuse

liability and of the comparability of abuser and nonabuser populations is

fascinating and deserves considerably more investigation. However, at

this time we would recommend that studies intended to assess drug abuse

liability in humans should select as subjects volunteers with histories of

drug abuse.

Third, drug discrimination behavior may have greater pharmacological

specificity if it is trained in a procedure with more than two alternatives.

Animal laboratory drug discrimination studies indicate that an increased

number of training and response alternatives tends to sharpen the specificity

of the discrimination (Overton 1984). A two-choice procedure does not

permit as refined a distinction among drugs as would a procedure with

more training drugs and more discriminative response alternatives.

Theoretically, a two-choice drug versus placebo discrimination procedure

118
could result in a drug-no drug discrimination performance with minimal

specificity. The important impact of the number and type of training drug

alternatives is illustrated in table 2, which summarizes human drug

discrimination performance with a group of opioid agonists and mixed

agonist/antagonists studied under two different training conditions. The

right hand column shows the percent of hydromorphone-appropriate

discrimination responding in the three-choice discrimination study

described earlier, in which subjects were trained to discriminate among

hydromorphone, pentazocine, and saline (Preston et al., in press). In this

procedure only hydromorphone was consistently discriminated as being

hydromorphone-like; none of the mixed agonist/antagonists generalized

completely to the hydromorphone stimulus. In contrast, the left hand

column shows the percent of hydromorphone-appropriate discrimination

responding in a two-choice discrimination study in which subjects were

trained to discriminate between hydromorphone and saline (Preston and

Bigelow unpublished data). In this two-choice procedure, all of the

mixed agonist/antagonists were discriminated as being hydromorphonelike. Thus, the number and/or nature of the training drug alternatives can

clearly have a dramatic influence upon how test drugs are characterized

or categorized in a drug discrimination assessment. It seems that more

Table 2. Influence of discriminative response alternatives upon opioid

discrimination behavior

Mean Percent

Hydromorphone-Appropriate Responding

Drug1

2-Choice 3-Choice

Procedure2

Procedure3

Hydromorphone 3 mg 100 100

Pentazocine 45 mg 80 0

Butorphanol 6 mg 100 0

Nalbuphine 24 mg 100 60

Buprenorphine 0.9 mg 100 50

1

 All doses are per 70 kg.

2

 2-Choice Procedure = Hydromorphone 3 mg vs. placebo.

3

 3-Choice Procedure = Hydromorphone 3 mg vs. Pentazocine 45 mg vs.

placebo.

119
precise and refined characterizations of abuse liability are likely to result

from multiple-choice drug discrimination procedures that characterize

test drugs in relation to several reference training drugs.

Fourth, animal laboratory data indicate that more precise or specific

discriminations, with a narrower range of generalization, tend to be

established with higher doses of the training drugs (Over-ton 1984). The

traditional method of assessing abuse liability by evaluating the acute

profile of drug effects has been validated in procedures that typically use

doses several times the therapeutic level. It seems likely that the drug

discrimination procedure may also be most applicable to abuse liability

assessment when comparably large doses are used. For example, in the

Chait et al., studies of anorectic drug discrimination discussed earlier, the

relatively low dose of d-amphetamine used, and its borderline

discriminability from placebo, may have contributed to broad

generalization of the amphetamine drug stimulus to nonabused anorectics.

That the oral dose of 10 mg d-amphetamine was of borderline

discriminability from placebo is indicated by the fact that of the 64 subjects

trained in those studies only 52 percent successfully learned it. More

distinctively different training drugs might have resulted in a more specific

discrimination with less generalization to other drugs. In the opioid drug

discriminations in our laboratory and in the other drug discriminations

summarized earlier, which have used relatively larger training doses,

approximately 90 percent of subjects have correctly learned the trained

discriminations. Studies demonstrating the establishment of drug

discrimination between two doses of the same drug (e.g., Colpaert and

Janssen 1986) illustrate that the stimulus properties of drugs change as

dose changes. Since drug abusers typically use greater than therapeutic

doses it seems likely that it is the stimulus properties of these larger doses

that will be most relevant to abuse liability.

CONCLUSIONS

The drug discrimination methodology is one that has proven its utility in

the animal laboratory. There it appears that drugs with similar

pharmacological actions or mechanisms share stimulus properties- i.e.,

they are discriminated as being similar to one another. Application of the

drug discrimination methodology to human testing remains relatively

novel. Here also we believe the drug discrimination methodology will

have great utility, although insufficient data are yet available to clarify the

full extent of its application and value.

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In the work conducted thus far with humans, it is clear that drug

discriminations with a wide range of different drug classes can be readily

and rapidly learned by human volunteers. Also, it is clear that the procedure

is compatible with concurrently collecting a broad array of subjective and

physiological measures as is done in traditional assessments of the profile

of acute effects. Yet, interpretation of the array ofthesetraditionalmeasures

is often complicated. Drug discrimination procedures appear to provide

a convenient method that can aid in more precise and refined

differentiations among, and characterizations and categorizations of the

nature of the effects of psychopharmacological agents.

Drug discrimination performance is not a direct index of abuse liability;

but by aiding in the precise assessment of the similarities and differences

among compounds the procedure can provide an improved estimation of

the likely abuse potential of test compounds.

REFERENCES

Bickel, W.K.; Bigelow, G.E.; Preston, K.L.; and Liebson, LA. Opioid drug

discrimination in humans: Stability, specificity, and relation to selfreported drug effect. J Pharmacol Exp Ther in press.

Chait, L.D.; Evans, S.M.; Grant, K.A.; Kamien, J.B.; Johanson, C.E.; and

Schuster, C.R. Discriminative stimulus and subjective effects of smoked

marijuana in humans. Psychopharmacology 94:206-212, 1988.

Chait, L.D.; Uhlenhuth, E.H.; and Johanson, C.E. An experimental paradigm for

studying the discriminative stimulus properties of drugs in humans.

Psychopharmacology 82:272-274, 1984.

Chait, L.D.; Uhlenhuth, E.H.; and Johanson, C.E. The discriminative stimulus

and subjective effects of d-amphetamine in humans. Psychopharmacology

86:307-312, 1985.

Chait, L.D.; Uhlenhuth, E.H.; and Johanson, C.E. The discriminative stimulus

and subjective effects of d-amphetamine, phenmetrazine and fenfluramine

in humans. Psychopharmacology 89:301-306, 1986a.

Chait, L.D.; Uhlenhuth, E.H.; and Johanson, C.E. The discriminative stimulus

and subjective effects of phenylpropanolamine, mazindol and damphetamine in humans. Pharmacol Biochem Behav 24: 1665-1672,

1986b.

Chait, L.D.; Uhlenhuth, E.H.; and Johanson, C.E. Human drug discrimination: dAmphetamine and other anorectics. In: Harris, L.S., ed. Problems of

Drug Dependence, 1985. National Institute on Drug Abuse Research

Monograph 67. DHHS Pub. No. (ADM) 86-1448. Washington, D.C.:

Supt. of Docs., U.S. Govt. Print. Off., 1986, pp. 161-167.

Colpaert, F.C., and Janssen, P.A.J. Agonist and antagonist effects of prototype

opiate drugs in fentanyl dose-dose discrimination. Psychopharmacology

90:222-228, 1986.

121
Holtzman, S.G. Discriminative stimulus properties of opioid agonists and

antagonists. In: Cooper, S.J., ed. Theory in Psychopharmacology. Vol 2.

London: Academic Press, 1983, pp. l-45.

Holtzman, S.G. Drug discrimination studies. Drug Alc Dep 14:263-282, 1985.

Jasinski, D.R. Assessment of the abuse potential of morphine like drugs (methods

used in man). In: Martin, W.R., ed. Drug Addiction I. New York:

Springer-Verlag, 1977, pp. 197-258.

Over-ton, D.A. State dependent learning and drug discriminations. In: Iversen,

L.L.; Iversen, SD.; and Snyder, S.H., eds. Handbook of

Psychopharmacology. Vol. 18. New York Plenum Publishing

Corporation, 1984, pp. 59-127.

Preston, K.L., and Bigelow, G.E. Drug discrimination in human post-addicts:

Agonist/antagonist opioids. J Pharmacol Exp Ther in press.

Preston, K.L.; Bigelow, G.E.; Bickel, W; and Liebson, I.A. Three-choice drug

discrimination in opioiddependent humans: Hydromorphone, naloxone

and saline. J Pharmacol Exp Ther 243:1002-1009, 1987.

Stoleman, I.P. and Shine, P.J. Trends in drug discrimination research analysed

with a cross-indexed bibliography, 1982-1983. Psychopharmacology

86:1-11, 1985.

Stolerman., I.P.; Baldy, R.E.; and Shine, P.J. Drug discrimination procedure: A

bibliography. In: Colpaert, F.C.. and Slangen, J.L., eds. Drug

Discrimination Applications in CNS Pharmacology. Amsterdam:

Elsevier Biomedical Press, 1982, pp.401-441.

ACKNOWLEDGMENTS

Supported by USPHS research grant DA-04089 and Research Scientist

Award DA-00050.

AUTHORS

George E. Bigelow, Ph.D.

Associate Professor of Behavioral Biology

Kenzie L. Preston, Ph.D.

Assistant Professor of Behavioral Biology

Behavioral Pharmacology Research Unit

Department of Psychiatry and Behavioral Sciences

The Johns Hopkins University School of Medicine

and Francis Scott Key Medical Center

BPRU; D-5-West; Psychiatry

Johns Hopkins/Key Medical Center

4940 Eastern Avenue

Baltimore, Maryland 21224

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CHAPTER 7

Abuse Liability of Anxiolytics and Sedative/

Hypnotics: Methods Assessing

the Likelihood of Abuse

John D. Roache, Ph.D.

Roland R. Griffiths, Ph.D.

INTRODUCTION

Drug abuse is a culturally-defined term referring to a socially unapproved

pattern of drug self-administration behavior. Two important characteristics

of the drug which influence the cultural definition(s) of drug abuse are

whether the drug maintains self-administration and whether this selfadministration occurs in a pattern that is injurious to the individual or

society. Assessments of abuse liability therefore involve evaluations of

both the potential for drug self-administration and the potential for

deleterious consequences of drug use. These assessments correctly use

the term, abuse liability, since definitions of “liability” include both the

concept of likelihood as well as the concept of hazard or disadvantage.

There are certainly amultiplicity of factors influencing whether a particular

drug will be defined as or become an abused substance including cultural

and socioeconomic factors as well as pharmacological variables.

Laboratory studies of abuse liability generally have focused on the

pharmacological variables which may differentiate individual drugs with

respect to their abuse liability. In humans, laboratory studies generally

have attempted to predict the abuse liability of a particular test drug by

examining the physiological and behavioral changes produced by the test

drug in comparison to a standard drug with known abuse liability. This

chapter will briefly discuss and illustrate the methods used in humans, to

assess the abuse liability of drugs having a sedative profile (i.e., both

anxiolytics and sedative/hypnotics). The emphasis of this chapter will be

on those methods used to predict the likelihood of abuse although the

value of simultaneous assessments of performance impairment as a

deleterious consequence will be discussed as well. Basic principles

involved in meaningful assessments will be emphasized and issues related

123
to the predictive validity of these methods will be discussed. A final

section will outline a proposed course for abuse liability assessment in the

development of new anxiolytics and sedative/hypnotics.

METHODS ASSESSING THE LIKELIHOOD OF SEDATIVE

ABUSE

In humans, the likelihood of abuse usually is predicted through the use of

one of two basic methods employed in subjects with histories of drug

abuse. The most common method involves examination of the druginduced profile of subject ratings such as ratings of drug liking, positive

mood or euphoria. These subject ratings usually are assumed to reflect

the subjective experience or psychoactivity produced by the drugs. Subject

ratings are used to predict the likelihood of abuse with the assumption that

the subjective mood changes produced by a drug may contribute to the

likelihood of self-administration behavior. The second and most face

valid approach involves a direct measure of the ability of drugs to reinforce

drug self-administration. The reinforcing effects of a drug refer to its

ability to increase the probability of behavior resulting in the administration

of the drug. Studies in several laboratory animal species have shown that

drugs can serve as reinforcers and maintain drug self-administration

behavior much like food or water delivery serve to reinforce behaviors

leading to their presentation. Such reinforcing effects of drugs are a

major determinant influencing the likelihood that a particular drug will

be abused. It is not clear how well subject ratings correlate with the

reinforcing effects of drugs and a causal relationship cannot be assumed.

Although both methods have face validity, the predictive validity of either

human methodology has not been fully demonstrated.

SUBJECT RATINGS INDICATING A LIKELIHOOD OF

ABUSE

Addiction Research Center Inventory (ARCI): The Addiction Research

Center Inventory (ARCI) has been the subject rating scale most widely

used to assess the subjective effects and abuse potential of psychoactive

drugs. It is an empirically-developed true/false questionnaire from which

subscales were derived based upon the subjective responses to seven

different psychoactive drugs of male narcotic addict prisoners at the

Addiction Research Center in Lexington, KY (Haertzen, 1966). These

scales have been widely used to assess analgesics for morphine-like abuse

potential (Fraser and Jasinski 1977; Jasinski et al., 1977). The MBG scale

is comprised of those item responses produced by morphine and

124
amphetamine (benzedrine) and is often considered a euphoria scale. The

PCAG scale is considered a sedative scale comprised of those items

affected by the sedatives pentobarbital, chlorpromazine and alcohol.

Researchers utilizing the ARCI scales to assess the abuse liability of

sedatives have obtained variable results. Of the ARCI scales, the PCAG

scale is the most reliably affected by sedative drugs. In narcotic addicts,

the PCAG scale has been increased by secobarbital, pentobarbital and

phenobarbital (Fraser and Jasinski 1977). In sedative abusers, the PCAG

sedation scale has been increased by pentobarbital (McLeod and Griffiths

1983; Griffiths et al., 1983), methaqualone (Cole et al., 1982b), diazepam

(Griffiths et al., 1983; 1984b) and prazepam (Cole et al, 1982b). However,

since chlorpromazine, which is not a drug of abuse, also increases ratings

on this scale (Haertzen 1966), PCAG scale increases do not indicate a

potential for abuse. The effects of sedatives on the MBG scale have been

much less consistent. In narcotic addicts, secobarbital and pentobarbital

have increased MBG ratings (Fraser and Jasinski 1977). In sedative

abusers, increased MBG ratings have been observed with pentobarbital

(Griffiths et al., 1983) and diazepam (Griffiths et al., 1983; 1984b).

However, experiments have alsoreported failures to increase MBG ratings

with pentobarbital (Haertzen 1966; McLeod and Griffiths 1983),

phenobarbital (Fraser and Jasinski 1977) and diazepam and oxazepam

(Griffiths et al., 1984a). While failures to increase the MBG scale

sometimes have been suggested to indicate a lack of euphoria and abuse

potential, it should be recognized that the MBG scale originally was

derived from those items which discriminated morphine and amphetamine

fromsedatives such as pentobarbital and alcohol which did not significantly

affect this scale (Haertzen 1966). The lack of consistent effects on the

MBG scale with pentobarbital, a standard sedative with known abuse

potential, certainly reduces its value as an indicator of sedative abuse

potential.

In anattempt to improve the sensitivity of the ARCI for sedative/hypnotic

abuse potential assessment, a subset of items from the MBG and PCAG

scales were selected (Jasinski et al., 1977) to derive new euphoria and

sedative scales. In that report, pentobarbital, secobarbital, phenobarbital

and methaqualone each produced dose-related increases on the modified

euphoria scale. In subsequent reports, diazepam and chlordiazepoxide

also produced dose-related increases in the euphoria scale (Jasinski et al.,

1982) although the chlordiazepoxideeffect did not replicate in a subsequent

study (Jasinski et al., 1983). Other researchers have reported variable

results with this euphoria scale. In one study, methaqualone did but

single low doses of diazepam and prazepam did not significantly increase

ratings on the euphoria scale (Cole et al., 1982b). In another study,

diazepam produced dose-related increases in euphoria ratings but

125
halazepam did so only minimally at a lower dose (Jaffe et al., 1983).

Finally, Cole et al. (1982a) used a seven-point rating scale with the ARCI

items to derive new euphoria and abuse potential scales which have not

been further tested.

Subject Ratings of Drug Liking: In subjects with histories of sedative

drug abuse, subject ratings on graded scales indicating that subjects “like”

the effects of the drug reasonably suggest that the drug has some likelihood

of abuse. In addition to the ARCI, researchers at the National Institute on

Drug Abuse (NIDA)/Addiction Research Center employed subject ratings

of drug liking from the single-dose opiate questionnaire in their sedative

studies (Fraser and Jasinski 1977; Jasinski et al., 1977). These studies

demonstrated dose-related increases in subject ratings of drug liking

produced by secobarbital, pentobarbital, phenobarbital and methaqualone

in subjects under the influence of these drugs. In a series of studies with

sedative abusers, Griffiths and colleagues (McLeod and Griffiths 1983;

Griffiths et al., 1980; 1983; 1984a,b) employed five-point rating scales

with qualifying phrases associated with each response and showed that

pentobarbital, diazepam and oxazepam produced dose-related increases

in subject ratings of drug liking. Notably, changes in these drug liking

ratings were more consistently observed than were changes in MBG

ratings (McLeod and Griffiths 1983; Griffiths et al., 1980; 1984a).

Subsequent studies (Roache and Griffiths 1985; 1987) extended these

observations by showing dose-related increases in drug liking ratings by

subjects under the influence of triazolam, lorazepam and meprobamate.

These studies also employed analog line rating scales which were given

to subjects on the morning of the next day and were to be completed with

reference to the previous days’ drug effect, Dose-related increases in

next day ratings of drug liking were obtained withpentobarbital, triazolam,

lorazepam and meprobamate. These next day ratings of drug liking may

be important in that they may reflect the overall liking of the remembered

drug experience and may predict the likelihood of future drug use better

than ratings obtained while subjects are under the influence of the drug.

All of the above mentioned studies employed urn-directional liking

measures which ranged from no liking to an extreme specified by an

adjective describing much liking. However, bi-directional liking measures

ranging from dislike to neutral to like have also been employed. One

study in alcoholics (Jaffe et al., 1983), reported difficulties in the analysis

of the bipolar liking scale so the authors converted the data to fit two unidirectional dimensions of liking and disliking.

126
OTHER MEASURES INDICATING LIKELIHOOD OF ABUSE

Other measures have been employed which intuitively seem related to

the abuse potential of a drug. One such measure is the subject’s estimate

of the monetary street value of the drug. In sedative abusers, dose-related

increases in estimated street value have been observed with diazepam but

not oxazepam (Griffiths et al., 1984b), with triazolam and pentobarbital

(Roache and Griffiths 1985), and with lorazepam and meprobamate

(Roache and Griffiths 1987). Cole et al. (1982a) also reported significant

estimates of street value for diazepam and methaqualone and correlated

these estimates with items from the ARCI to derive a new abuse potential

scale. Another measure which has been used is a direct inquiry of the

likelihood of future use. These ratings have been collected on a unidirectional visual analog line of “would choose again” (Roache and

Griffiths 1985; 1987) and a bi-directional analog line of “would use/

never use again” (Cole et al., 1982a). Subjectwrittencommentsabout the

effects of the drug also have been used to compare the abuse liability of

diazepam and oxazepam (Griffiths et al., 1984b) and diazepam and

triazolam (Roache and Griffiths 1988). One other measure which has

been used to make inferences regarding abuse liability is classification,

by experienced drug abusers, of the drug administered under doubleblind conditions. In several studies (Roache and Griffiths 1985; 1987;

Griffiths et al., 1984a,b; Jasinski et al., 1977) the differential classification

of sedatives as belonging to either the barbiturate or benzodiazepine drug

classes provided information regarding abuse liability to the extent that

drugs perceived as barbiturate-like may have a greater likelihood of abuse.

POSITIVE AND NEGATIVE MOOD CHANGES

On an intuitive basis, it is sometimes assumed that drugs producing positive

subjective mood changes would have a greater likelihood of selfadministration than drugs which produce negative mood changes.

Inferences regarding abuse liability have been made on the basis of positive

or negative subjective mood changes. In the development of the ARCI,

an LSD scale was derived from those items affected by LSD (Haertzen

1966). This LSD scale as well as a modified dysphoria scale have been

employed in abuse liability studies to assess dysphoric effects of sedatives

(Jasinski et al., 1977); however, significant dysphoric effects of sedatives

have not been routinely described by other investigators. Significant

dysphoric effects of buspirone in combination with reduced euphoric

effects have supported the suggestion that buspirone has a reduced

likelihood of abuse in comparison to diazepam (Cole et al., 1982a). A

deterioration of mood and social behavior observed with diazepam but

127
not pentobarbital was suggested to contribute to lower abuse liability of

diazepam (Griffiths et al., 1983).

MEASURES OF REINFORCING EFFECTS: DRUG SELFADMINISTRATION

Multiple Daily Dose Ingestion Procedures

Griffiths and colleagues (Bigelow et al., 1976; Griffiths et al., 1976;

1979) have employed procedures in which multiple ingestions per day of

unit doses of pentobarbital or diazepam were available to subjects with

histories of sedative abuse contingent upon completion of an exercise

bicycle riding response requirement. These studies have shown that in

subjects with histories of sedative abuse, sedatives are self-administered

in a controlled laboratory environment. Furthermore, these studies

collectively have shown that number of self-ingestions is an orderly

function of dose, response requirement and inter-ingestion interval. The

latter of these studies (Griffiths et al., 1979) employed double-blind

placebo-controlled procedures in which, over an 8.5 hr period each day,

subjects could self-administer up to ten ingestions of letter-coded doses

of placebo, pentobarbital (30 or 90 mg/ingestion), diazepam (10 or 20

mg/ingestion) and chlorpromazine (25 or 50 mg/ingestion) across a ten

consecutive day period. On the first day, subjects were encouraged to

ingest a sufficient number of doses to sample the effects of that drug dose,

however, the number of ingestions on this and all subsequent days were

completely determined by the subjects. Figure 1 shows the mean number

of ingestions per day for each of the dose conditions. Clearly, placebo and

chlorpromazine failed to maintain self-administration since the rates of

self-administration rapidly declined to near zero levels. In contrast,

diazepam and pentobarbital produced dose-related increases in the number

of daily ingestions. Pentobarbital produced overall greater and more

stable rates of self-administration than diazepam which produced

submaximal and gradually declining rates of self-administration across

the ten days. These results are consistent with the suggestion that diazepam

is less reinforcing than pentobarbital but more reinforcing than

chlorpromazine. The use of chlorpromazine in this study illustrates the

value of a negative control agent and demonstrates the sensitivity of the

procedure to discriminate between drugs having definite abuse potential

(e.g., pentobarbital) and drugs having very little or no abuse potential

(e.g., chlorpromazine).

Two studies (Healey and Pickens 1983; Pickens et al., 1977) examined

sedative self-administration in male and female subjects who were

128
Figure 1: Daily self-administration of placebo, chlorpromazine, diazepam and

pentobarbital. Y-axes: No. of ingestions. X-axes: Ten consecutive experimental

days. Data are mean (± S.E.M.) number of ingestions consumed each day for

placebo, chlorpromazine (25 and 50 mg/ingestion), diazepam (10 and 20 mg/

ingestion), and penfobarbital (30 and 90 mg/ingestion). Numerals indicate the

number of subjects tested each day. Reprinted from, Griffiths et al., 1979, J

Pharmacol Exp Ther 210:303-310, 1979, with permission from Am. Soc. for

Pharmacology Exp. Therapeutics.

129
presumably physically-dependent on sedatives and were living on a

psychiatric research unit. These studies utilized a concurrent access

schedule in which subjects had concurrent ad libitum access to two

alternative drug doses with a minimum inter-ingestion interval of 30

minutes. The first study (Pickens et al., 1977) examined relative

preferences for varying doses of pentobarbital which were concurrently

available. The authors concluded that subjects generally preferred

intermediate doses (50-150 mg) over the high (200 mg) or low (30 mg)

doses of pentobarbital. The second study (Healey and Pickens 1983)

examined varying doses of diazepam (2-20 mg/ingestion) currently

available with either diazepam (5 or 20 mg/ingestion) or pentobarbital

(30 or 50 mg/ingestion). Dose-related effects of diazepam were only

observed in some subjects. The significance of these studies to abuse

liability assessment is not clear. The lack of a placebo control limits

conclusions regarding relative reinforcing effects and consistent dose

relationships were not reliably observed.

A recent study (Roache et al., 1988) employed a concurrent access

procedure in which differently-colored capsules containing placebo or

varying doses of triazolam were available by verbal request over a 3 hr

period with a 10 min minimum interingestion interval. This preliminary

study reported results in only three non-dependent male subjects with

histories of sedative abuse. Generally stable levels of triazolam (0.125

mg/ingestion) self-administration were observed across a ten day period

and variations in the triazolam dose (0.0312-0.25 mg) showed that the

number of ingestions per day was inversely related to triazolam dose.

The use of the concurrently-available placebo in this report allows the

conclusion that triazolam maintained self-administration behavior in this

concurrent access procedure.

Single Daily Dose Ingestion Procedures

Choice procedures have been used to provide a direct measure of the

relative preference for single doses of each of two available alternatives.

In order to directly compare the relative preference for different doses of

pentobarbital and diazepam, subjects with histories of sedative abuse

who were living on a research ward were given multiple independent

discrete choices between two available alternatives under double-blind

conditions (Griffiths et al., 1980). Subjects preferred high doses of both

pentobarbital and diazepam over placebo and preferred higher doses of

pentobarbital over lower doses. This study also showed that 400 mg

pentobarbital was preferred over 200 mg diazepam, however, the fact

that only single doses were tested precludes conclusions regarding the

relative reinforcing effects of the two drugs. A subsequent study (Griffiths

et al., 1984b) utilized similar procedures and varied the dose of diazepam

130
which was available as an alternative to a high dose of oxazepam (480

mg). Figure 2 shows that diazepam produced dose-related increases in

the number of subjects choosing diazepam over oxazepam. Conclusions

from this study would have been more definitive if varying doses of

oxazepam were compared to diazepam. However, the diazepam doseresponse function permitted an estimation that diazepam may be eight

times more potent than oxazepam in its relative reinforcing effects. This

eight-fold potency difference in reinforcing effects was consistent with

potency determinations from other measures indicating likelihood of

abuse including MBG ratings and ratings of drug liking and street value.

This eight-fold potency difference on measures of likelihood of abuse

was contrasted with the fact that, in clinical use and in measures of

psychomotor impairment, diazepam is only three times more potent than

oxazepam.

Figure 2: Diazepam dose preference over oxazepam. Y-axis: Percentage of subjects

choosing diazepam (DZ) over oxazepam (OX) in three separate choice comparisons.

X-axis: Three separate choice comparisons of 40 mg OX vs. 480 OX; 80 mg DZ vs.

480 OX; and 160 mg DZ vs. 480 mg OX. Numerals indicate the number of subjects

tested in each choice comparison. Reprinted from, Griffiths, et al., 1984b, J

Pharmacol Exp Ther 229:501-508, 1984, with permission from Am. Soc. for

Pharmacology Exp. Therapeutics.

131
Two other studies have employed methods in which subjects, with histories

of sedative abuse who were living on a research ward, were allowed to

choose whether or not to receive a single letter-coded drug dose which

they had sampled on a previous occasion. One study (McLeod and Griffiths

1983) employed a progressive ratio schedule in which subjects had to

press buttons or ride an exercise bicycle to complete progressively

increasing response (work) requirements in order to receive placebo or

various doses of pentobarbital. The results showed that the amount of

work subjects engaged in was an orderly function of pentobarbital dose;

higher doses maintained greater response ratios and therefore, were

presumably more reinforcing. Another study (Roache and Griffiths 1988)

employed a progressively increasing bicycle riding requirement in order

for subjects to self-administer single doses of diazepam (40 or 80 mg),

triazolam (1.0 or 2.0 mg) or placebo across a 6 day period. Both diazepam

and triazolam were self-administered on more occasions and by more

subjects than placebo which was self-administered by only one subject

on only two occasions. Across the six day period, the bicycle riding

requirement was progressively increased from 30 to 180 minutes and the

number of subjects choosing to self-administer drug decreased for both

drugs. Nodifferences in the reinforcing effects of diazepam and triazolam

were detected in this study.

CORRESPONDENCE BETWEEN SUBJECT RATINGS AND

SELF-ADMINISTRATION

The recent study (Roache and Griffiths 1988), which compared the selfadministration of single doses of diazepam (40 or 80 mg) and triazolam

(1.0 or 2.0 mg), provided an opportunity to compare the subject ratings

obtained on initial drug exposures with subsequent drug self-administration

behavior. Following an inital sampling exposure to a letter-coded drug

under double-blind conditions, subjects chose whether or not to receive

that same drug on each of the next six consecutive days. Both diazepam

and triazolam were self-administered by all eight subjects on the first

self-administration opportunity. However, there were differences in the

total number of occasions each subject self-administered diazepam and

triazolam across the six days of availability. Various subject ratings were

compared to the subjects’ self-administration behavior to examine the

correspondence of these two methods which are used for abuse liability

assessment. Figure 3 shows that subject ratings of drug liking obtained

on the morning of the day following the first occasion of self-administration

was significantly correlated with the total number of occasions subjects

subsequently self-administered each drug. Because of the small sample

132
Figure 3: Correlations of self administration and subject ratings of drug liking for

diazepam and triazolam. Y-axes: Millimeter scores from a 100 mm analog rating

scale for drug liking. X-axes: No. of occasions of self-administration. Circles

represent coordinate point data for each of eight subjects who were provided

separate opportunities to self-administer diazepam and triazolam on a maximum of

six occasions across six consecutive days. Also shown are the regression lines of y

on x, correlation coefficients and p-values determined by linear regression. Subject

ratings of drug liking were collected on the morning of the day following the first

occasion of self-administration. Reprinted from, Griffiths et al., 1979, J Pharmacol

Exp Ther 210:303-310, 1979, with permission from Am. Soc. for Pharmacology Exp.

Therapeutics.

133
size and the limited number of doses tested, these results should be

considered preliminary. However, they demonstrate procedures which

may be of value in examining the relationship of reinforcing effects and

subject ratings and suggest that a positive relationship may indeed exist.

A series of studies conducted in student and employed male and female

volunteers without histories of drug abuse have provided many insights

into the relationship between subject ratings and reinforcing effects. These

studies examined the reinforcing effects of sedatives and stimulants in

subjects who were not maintained in laboratory environments but were

allowed to leave the laboratory and go about their daily routines following

drug ingestion. The procedures involved initial double-blind sampling

of color-coded placebo or drug capsules and five subsequent choice trials

between the drug or placebo alternatives. These studies have shown that

stimulants such as amphetamine were self-administered but sedatives

including diazepam (Johanson and Uhlenhuth 1980), lorazepam (de Wit

et al., 1984a) and flurazepam (de Wit et al., 1984b) generally were not

self-administered. In a modified procedure (de Wit et al, 1984c), the

same subject population was maintained in the laboratory following

evening drug administration; however, diazepam and pentobarbital selfadministration was not observed. In these studies, the benzodiazepines

generally increased PCAG sedation ratings but not MBG euphoria ratings

(de Wit et al., 1984a,b). Although pentobarbital increased MBG ratings

(de Wit et al., 1984c), it also was not chosen over placebo. Although

reinforcing effects of sedatives generally have not been detected in these

procedures, a review of several studies conducted with amphetamine and

diazepam reported that a minority of subjects did in fact prefer diazepam

over placebo (de Wit et al., 1986b). In this review, the tendency for

subjects to choose drug over placebo was associated with drug-induced

subject ratings on the Profile of Mood States (POMS). Subjects choosing

amphetamine over placebo tended to show greater positive mood changes

than non-choosers and subjects choosing diazepam over placebo have

tended to show lesser sedative effects of diazepam than those choosing

placebo. These studies also have used bidirectional drug liking scales.

Although liking scores were not presented, tendencies for drug choosers

to like drug better than placebo and for placebo choosers to like placebo

better than drug were reported. These results suggest that the drug selfadministration patterns of individual subjects may be related to their

subjective response to drugs as revealed by subject ratings of mood and

drug liking.

134
EXPERIMENTAL DESIGN CONSIDERATIONS

The Validity of Methods Suggesting Differences Between Drugs

Using these methods of abuse liability assessment, predictions regarding

the likelihood of abuse of various sedatives seem reasonable based upon

the face validity of the measures of drug-induced subjective effects and

self-administration. However, the predictive validity of these methods

has not been established due to a general lack of studies evaluating drugs

which could serve as negative controls (i.e., drugs clearly lacking abuse

liability). For these reasons, confidence in predictions of the likelihood

of abuse will be improved as methods are better developed and a larger

variety of drugs are tested under a wider range of conditions. The

demonstrated value of these methods has been in the description of

quantitative differences between various sedative drugs using measures

which are clearly sensitive to effects of standard drugs of abuse.

Conclusions regarding quantitative and qualitative drug differences have

been possible in studies which examined the effects of a range of doses

of the test compound in comparison to a standard drug using measures

which were sensitive to the effects of the standard drug. Additional

confidence in conclusions of drug differences has been gained through

the use of a multiplicity of measures and systematic replication of

experimental results under different conditions.

As noted in two reviews on the abuse liability of benzodiazepines (Griffiths

and Roache 1985; Woods et al., 1987), experiments testing a range of

doses with a variety of procedures and measures have reasonably

demonstrated differences in the abuse liability of various sedatives. Several

studies have shown that diazepam and other benzodiazepines, have a

lesser likelihood of abuse than pentobarbital andmethaqualone (Griffiths

and Roache 1985). The conclusion that benzodiazepines have a lower

abuse liability than many other barbiturate and non-barbiturate sedatives

is supported by the variety of experimental procedures suggesting this

conclusion and is also supported by epidemiological data indicating a

lower prevalence of benzodiazepine abuse (Woods et al., 1987). The best

demonstration of differences among the benzodiazepines has been in two

studies suggesting that oxazepam has a lesser likelihood of abuse than

diazepam (Griffiths et al., 1984a,b). This conclusion, based upon

laboratory studies of abuse liability, is supported by data from the United

States (Griffiths et al., 1984b) and Sweden (Bergman and Griffiths 1986)

which suggest that diazepam abuse uniformly exceeded oxazepam abuse

on several epidemiological measures of drug abuse. The latter report

demonstrated that this conclusion is not an artifact of differential

prescription frequencies of diazepam and oxazepam which have similar

135
prescription rates in Sweden. The validity of human self-administration

methodologies in sedative abusers is supported by one study (Griffiths et

al., 1979) which showed that diazepam was self-administered to a lesser

extent than pentobarbital but to a greater extent than chlorpromazine.

This study is an example of the use of a negative control drug to validate

conclusions since chlorpromazine is generally accepted to have very

little or no potential for abuse.

The validity of sedative abuse liability assessment methods is supported

by these above-mentioned studies which have developed these methods

by testing drugs with known abuse liability profiles. The predictive

validity of these methods will be tested as new drugs under development

are correctly categorized by these methods as to their abuse liability.

Buspirone represents one such new drug which has been predicted to

have a reduced likelihood of abuse in comparison to diazepam (Cole et

al., 1982a). However, this study must be considered preliminary since it

examined only two doses of buspirone. This limited human evidence for

a reduced abuse liability of buspirone is often accepted less critically than

would otherwise be true since buspirone has a novel chemical structure

and pharmacological profile and does not potentiate ethanol (Ortiz et al.,

1987) and is not self-administered by monkeys (Balster and Woolverton

1982).

Concurrent Measures of Drug Effect and Performance

The quantitative measurement of drug effects other than those specifically

related to predictions of the likelihood of abuse can be of great value in

abuse liability assessment studies for several reasons. First, it is important

to have such concurrent measures in order to demonstrate that adequate

and comparable doses of the test compound have in fact been employed

in the study. This is particularly important if the test compound lacks

effects on the measures of the likelihood of abuse. Second, comparisons

of dose-response functions and relative potency differences between the

standard and test compounds across different measures strengthen any

conclusion that the test compound is or is not different in its likelihood

of abuse. Finally, these concurrent measures can be used to simultaneously

assess the deleterious consequences or the relative advantage of the test

compound in comparison to the standard drug. In order to strengthen

conclusions regarding drug comparisons, several studies have employed

concurrent measures including observer ratings of drug effect magnitude

and objective measures of psychomotor and cognitive performance.

The power of the use of concurrent measures in an acute dose-response

study is illustrated in figure 4. This study (Roache and Griffiths 1985)

compared placebo and a six-fold range of triazolam and pentobarbital

136
Figure 4: Triazolam and pentobarbital dose-response functions for staff ratings,

psychomotor performance and subject ratings of drug liking and estimated street

value. Y-axes: Peak ratings of staff-rated drug effect magnitude; peak degree of

psychomotor impairment (percent of pre-drug) on the circular lights task; peak

degree of subject-rated drug liking; and subject-estimated street value ($). X-axes:

Triazolam and pentobarbital dose (mg); “P” designates the placebo dose. The

relative potencies (RP) and 95 percent confidence limits (C.I.) are shown above each

panel exceptfor circular fights which shows an estimate of relative potency since the

data did not meet the criteria for relative potency determination. Data are means of

nine subjects tested at each dose condition. Darkened symbols indicate data points

significantly different (p < 0.05) than placebo, Duncan’s Multiple Comparisons

Procedure. Reprinted from, Griffiths et al., 1979, J Pharmacol Exp Ther 210:303-

310, 1979, with permission from Am. Soc. for Pharmacology Exp. Therapeutics.

137
doses using a within-subject cross-over design. The upper two panels

show that triazolam and pentobarbital produced comparable effects to

increase staff (observer) ratings of drug effect magnitude and to impair

circular lights (psychomotor) performance. In contrast, triazolamproduced

lesser effects than pentobarbital on subject ratings of drug liking and next

day estimates of street value. The relative potency of 256 on staff drug

effect ratings indicates that 256 mg of pentobarbital produced the same

effect as 1 mg triazolam on this measure. The lower relative potencies

(i.e., RP=122) on measures indicating likelihood of abuse indicate that it

took less pentobarbital (only 122 mg) to produce the same effect as 1 mg

of triazolam. Thus, the relative potency differences across these measures

indicate that at doses which produce comparable degrees of drug effect

and psychomotor impairment, triazolam would be less well liked and

have lower street value than pentobarbital. Clearly, the examination of

a range of doses of both drugs which are demonstrated to be comparable

on concurrent measures, strengthens conclusions regarding a reduced

likelihood of abuse of triazolam relative to pentobarbital.

Other studies have strengthened conclusions regarding drug comparisons

by employing concurrent objective measures of psychomotor and cognitive

performance. In a comparison of diazepam and oxazepam (Griffiths et

al., 1984a), a greater potency difference between the two drugs was

observed with measures predicting the likelihood of abuse than with

measures of psychomotor impairment. These relative potency differences

indicate that oxazepam has a lower likelihood for abuse than diazepam

at doses which produce comparable degrees of psychomotor impairment.

Another study (Roache and Griffiths 1987) reported that lorazepam was

relatively less potent than meprobamate in producing subject-rated drug

liking at doses which produced comparable degrees of psychomotor

impairment. The concurrent measures utilized in the comparisons of

triazolam and pentobarbital (Roache and Griffiths 1985) and lorazepam

and meprobamate (Roache and Griffiths 1987) showed that triazolam

and lorazepam had a greater potential than pentobarbital and meprobamate

to produce amnestic effects and impair the subjects’ recognition of their

own impairment. Overall, these studies have described a profile of

behavioral effects of benzodiazepines which are different than those seen

with traditional barbiturate and non-barbiturate sedatives and anxiolytics.

The profile indicates that in comparison to barbiturates and other sedatives,

benzodiazepines have a lesser likelihood of abuse but a greater potential

to produce certain types of performance impairment (Roache and Griffiths

1987).

138
Subjects and Laboratory Procedures

Most studies of sedative abuse liability assessment haveemployedsubjects

with histories of sedative, alcohol and/or narcotic drug abuse who were

maintained in residential laboratory environments (Fraser and Jasinski

1977; Griffiths et al., 1979; 1983; Jaffe et al., 1983). Other studies have

employed college students with recreational sedative abuse histories who

were maintained in laboratory environments for the day following drug

ingestion (Cole et al., 1982a,b). However, several studies assessing the

reinforcing effects of benzodiazepines in normal subjects have utilized

student and employed volunteers who did not remain in the laboratory but

continued their normal daily routines following drug ingestion (Johanson

and Uhlenhuth 1980; de Wit et al., 1984a,b; 1985; 1986b). Reinforcing

effects of pentobarbital and diazepam clearly have been demonstrated in

subjects with histories of sedative abuse living in residential laboratory

environments (c.f., Griffiths and Roache 1985). In contrast, reinforcing

effects of diazepam generally have not been observed in normal subjects

who were not maintained in controlled laboratory environments (de Wit

et al., 1985; 1986b). It is not clear whether the critical determinants of

these discrepant observations are subject drug history or environmental

context (Johanson and Uhlenhuth 1980). Both history and environmental

variables have been shown to influence the reinforcing effects of

benzodiazepines in laboratory animals (Ator and Griffiths 1987; Bergman

and Johanson 1985). Several studies have investigated procedural

variables possibly influencing the lack of reinforcing effects of diazepam

in the normal volunteer studies. One study (de Wit et al., 1985) found that

experimental variations in subject age and the time of day of drug

administration did not increase the reinforcing effects of diazepam.

Another study (de Wit et al., 1986a) found that anxious subjects were no

more likely to self-administer diazepam than werenormalcontrol subjects.

Another modification required normal subjects to spend four hours in the

laboratory following the evening ingestion of diazepam or pentobarbital

(de Wit et al., 1984c). This latter study also did not detect reinforcing

effects of diazepam or pentobarbital. Clearly, the inability to detect

reinforcing effects of pentobarbital, a standard drug with known abuse

potential, precludes the use of these procedures to quantify the abuse

liability of sedatives having a likelihood of abuse which is equal to or less

than that of pentobarbital.

A recent study (de Wit et al., 1988) modified the choice procedures

previously used in normal subjects and demonstrated that diazepam did

produce reinforcing effects in subjects with light (4.8 drinks per week) or

moderate (11.8 drinks per week) histories of current alcohol use. Three

139
important procedural modifications employed in this study include: the

specific recruitment of alcohol users; the creation of a social environment

where subjects participated in social groups during evening sessions and

were maintained in the laboratory over night; and the use of multiple dose

ingestion choice procedures. In contrast to the mostly negative results in

previous studies of normal subjects, this study suggested that

benzodiazepines may be reinforcers in subjects without significant drug

abuse histories under certain laboratory conditions. However, these data

also suggest that subject drug history may influence the reinforcing effects

of anxiolytics such as diazepam. Whereas diazepam was generally

preferred over placebo in both populations, a greater proportion (100

percent vs. 61 percent) of the moderate drinkers self-administered higher

doses (25.2 mg vs. 18.8 mg) of diazepam than did the light drinkers.

Compared to the light drinkers, the moderate drinkers also had greater

histories of marijuana, tobacco, hallucinogen and opioid use. The results

of a series of early studies (Beecher 1959) suggested that subject drug

history variables may also influence subjective responses to different

drugs. In those studies, normal subjects and patients hospitalized for

chronic disease rated amphetamine as producing a strong euphoric effect

while heroin, morphine, pentobarbital and placebo were rated as less

euphoric or unpleasant. In contrast, abstinent non-dependent narcotic

addicts not only rated amphetamine as producing euphoria but also rated

the opioids as producing euphoria. Thus, the ratings of subjects with

opioid abuse histories reflected the potential for abuse of opioid drugs

better than did the subject ratings of patients or normal subjects.

Overall, these data indicate that subject drug history variables may indeed

be important in assessing abuse liability. There is a great deal of face

validity in utilizing subjects with histories of drug abuse to determine

whether one drug has a greater or lesser likelihood of abuse than another

drug; for it is this population who will most likely abuse drugs having a

potential for abuse. However, the development of new methods for

studies in normal or light social drinkers may provide the opportunity to

better assess the likelihood of abuse of sedatives and anxiolytics in nonabuser populations.

PRINCIPLES GOVERNING MEANINGFUL ABUSE

LIABILITY ASSESSMENT

Based upon a review of existing methodologies for sedative abuse liability

assessment, five basic principles have emerged which seem to impact

one’s ability to draw meaningful experimental conclusions regarding

differences between individual compounds of the anxiolytic and sedative/

hypnotic drug classes.

140
Principle 1: Comparison to a Standard

A well established principle of any biological assay is that the unknown

sample must be compared to a standard tested under the same assay

conditions. In the biobehavioral assay of abuse liability assessment, this

means comparing the test compound to a standard drug of known abuse

liability under double-blind conditions. The best documented standard

sedatives include pentobarbital, secobarbital and methaqualone.

Depending upon what is known about the test compound and its planned

indication(s), studies also may make comparisons to other drugs currently

used for the same indication. In the case of benzodiazepines, diazepam

would be considered the prototypic standard although lorazepam and

triazolam have been reasonably well investigated.

Principle 2: Dose-Response Evaluation

In the abuse liability assay, one must examine a range of doses of the test

compound as well as the standard drug to permit quantitative and qualitative

conclusions. If only single doses of the standard and test compounds are

evaluated, meaningful conclusions may not be possible. If a single dose

of the test compound is compared to a range of doses of the standard, then

at least one could determine quantitatively, where that specific dose falls

on the standard curve. However, unless a meaningful range of doses of

the test compound are tested, one can always argue that the doses were

too low or too high. Another reason to test a range of doses is that higher

than therapeutic doses are likely to be used by drug abusers so it is not

sufficient to test only therapeutic doses. Qualitative and quantitative

conclusions regarding a lack of or lesser abuse liability, respectively, are

most likely possible in experiments examining a reasonable range of

doses which are demonstrated to be comparable.

Principle 3: Concurrent Measures and Relative Potency

Comparisons

In addition to examination of a range of doses, the simultaneous

examination of concurrent measures of drug effect in addition to measures

predicting the likelihood of abuse permits the demonstration of comparable

doses. For example, doses could be selected which produce comparable

effects on one dimension such as sedation, psychomotor or cognitive

impairment, muscle relaxation, and hypnotic or anxiolytic activity. With

demonstrated comparability on this standard dimension, conclusions

regarding greater or lesser abuse liability at those comparable doses become

meaningful. Relative potency estimations on the various concurrent

measures are a useful standard statistical measure enabling comparisons

across dimensions.

141
Principle 4: Systematic Replication

Although the available data obtained from abuse liability studies are

reasonably consistent with clinical observation, the predictive validity of

these methods has not been well established due to the limited range of

conditions studied and a general lack of studies with drugs which could

serve as negative controls (i.e., drugs clearly lacking abuse liability).

Therefore, confidence in predictions of the likelihood of abuse will be

improved as methods are better developed and a larger variety of drugs

are tested under a wider range of conditions. For now, no single method

can be identified as the best or most valid predictor of the likelihood of

abuse. As is true for any experimental conclusion, one can have greater

confidence in conclusions which are systematically replicated across a

range of experimental conditions and dependent measures. Thus, studies

can enhance the confidence of conclusions regarding the abuse liability

of a test compound by utilizing a multiplicity of measures and experimental

procedures.

Principle 5: Select Appropriate Subject Populations

The appropriateness of employing subjects with histories of drug abuse

to predict the likelihood of abuse of new compounds is self evident; this

is the population who would abuse a drug which has the potential for

abuse. Studies which have reasonably demonstrated differences between

individual sedatives and anxiolytics in regard to their abuse liability have

predominately employed non-dependent sedative abusers and alcoholics.

Most studies in normal non-drug abuser populations have not been able

to distinguish among individual sedatives in regard to their likelihood of

abuse and have not developed measures sensitive to standard drugs of

abuse such as pentobarbital. A recent study in light to moderate alcohol

users suggests the possibility that methods capable of differentiating

between individual sedatives and anxiolytics may be developed in future

studies of this or even more drug naive populations.

PROPOSED COURSE FOR THE ABUSE LIABILITY

TESTING OF NEW DRUGS

Human studies of abuse liability assessment can occur anywhere within

the course of development of a new sedative/hypnotic or anxiolytic. Of

course, the ultimate design of any study will be influenced by the known

pharmacological and safety profile of the new compound at the time of

the study design. For example, studies conducted in the earlier Phase I

or II development process may be limited to dose-ranging studies due to

142
limited information on human safety. Ultimately, however, valid

conclusions regarding the abuse liability of a new compound can only be

drawn if a meaningful range of doses of the new compound has been

compared with standard drugs of known abuse liability. The following

proposed course for abuse liability testing is general and idealized; the

specific studies would depend on the specific drug under development

and its known pharmcological profile. In addition to testing for the

likelihood of abuse, the use of concurrent measures may allow some of

these studies to serve dual purposes in the necessary Phase I and II safety

testing and in the demonstration of pharmacological profiles of the new

compound which may be favorable in comparison to frequently used

compounds (e.g., reduced sedative or amnestic liability).

The initial study with any new compound should be a dose-ranging study

in which various doses are administered acutely to evaluate the doseresponse function of the drug on measures of abuse liability and concurrent

measures as well. It would be preferable, at this point, to include a

standard drug of known abuse liability in order to enhance the value of

the study. In this and all studies of abuse liability, subject ratings used to

predict the likelihood of abuse should be employed including euphoria

and ARCI scales, drug-liking ratings, and possibly other measures of

mood or subject ratings indicating likelihood of abuse.

Once there is confidence regarding appropriate dose selection, a more

definitive study should compare an adequate range of doses of both the

new and standard compounds using established procedures and measures

of abuse liability. This study will typically be an acute dose-response

evaluation employing several subject ratings indicating likelihood of

abuse as well as concurrent measures such as subjective mood and/or

objective measures of sedation and performance. Once the basic doseresponse comparison to a standard is accomplished, several types of

follow-up studies could be conducted to expand the generality of the

findings. Follow-up studies may include repeated dose administration to

examine tolerance phenomena or drug interaction studies (e.g., alcohol

interactions) to assess potential polydrug abuse complications. Other

studies may include a comparison of the new drug to other standard drugs

of known abuse potential or to other drugs currently used for the probable

therapeutic indication. Due to the face validity of studies examining drug

self-administration behavior, another study may directly examine the

reinforcing effects of the new compound as compared to a standard drug

of known abuse liability. Because of the complexities of selfadministration studies and the limited number of doses which can be

feasibly tested, these studies should be considered only after undertaking

thorough acute dose-response evaluations.

143
REFERENCES

Ator, N.A., and Griffiths, R.R. Self-administration of barbiturates and

benzodiazepincs: A review. Pharmac Biochem Behav 27:391-398, 1987.

Balster, R.L., and Woolverton, W.L. Intravenous buspirone self-administration in

rhesus monkeys. J Clin Psychiatry 43:134-39, 1982.

Beecher, H.K. Measurement of Subjective Responses: Quantitative Effects of

Drugs. New York: Oxford University Press, 1959.

Bergman, J., and Johanson, C.E. The reinforcing properties of diazepam under

several conditions in the rhesus monkey. Psychopharmacology 86:108-

113, 1985.

Bergman, U., and Griffiths, R.R. Relative abuse of diazepam and oxazepam:

Prescription forgeries and theft/loss reports in Sweden. Drug Alcohol

Depend 16:293-301, 1986.

Bigelow, G.E.; Griffiths, R.R.; and Liebson, I.A. Effects of response requirement

upon human sedative self-administration and drug-seeking behavior.

Pharmac Biochem Behav 5:681-685, 1976.

Cole, J.O.; Hecht-Orzack, M.; Beake, B.J.; Bird, M.P.; and Bar Tal, Y.

Assessment of the abuse liability of buspirone in recreational sedative

users. J Clin Psychiatry 43:69-74, 1982a.

Cole, J.O.; Hecht-Orzack, M.; Benes, F.M.; Beake, B.J.; Bird, M.P.; Bar Tel, Y.;

and Ionescu-Pioggia, M. Benzodiazepine abuse: What are the data?

Psychopharmacol Bull 18:87-96, 1982b.

de Wit, H.; Johanson, C.E.; and Uhlenhuth, E.H. Reinforcing properties of

lorazepam in normal volunteers. Drug Alcohol Depend 13:31-41, 1984a.

de Wit, H.; Pierri. J.; and Johanson, C.E. Reinforcing and subjective effects of

diazepam in non-drug-abusing volunteers. Unpublished manuscript, 1988.

de Wit, H.; Uhlenhuth, E.H.; Hedeker, D.; McCracken, S .G.; and Johanson, C.E.

Lack of preference for diazepam in anxious volunteers. Arch Gen

Psychiatry 43:533-541, 1986a.

de Wit, H.; Uhlenhuth, E.H.; and Johanson, C.E. Lack of preference for

flurazepam in normal volunteers. Pharmac Biochem Behav 21:865-869,

1984b.

de Wit, H.; Uhlenhuth, E.H.; and Johanson, C.E. Drug preference in normal

volunteers: Effects of age and time of day. Psychopharmacology 87:186-

193, 1985.

de Wit, H.; Uhlenhuth, E.H.; and Johanson, C.E. Individual differences in the

reinforcing and subjective effects of amphetamine and diazepam. Drug

Alcohol Depend 16:341-360, 1986b.

de Wit, H.; Uhlenhuth, E.H.; Pietri, J.; and Johanson, C.E. Preference for

pentobarbital and diazepam in normal volunteer subjects. Fed Proc

43:931, 1984c.

Fraser, H.F. and Jasinski, D.R. The assessment of the abuse potentiality of

sedative/hypnotics (depressants) (Methods used in animals and man). In:

Martin, W.R., ed. Drug Addiction I. Morphine. Sedative-Hypnotic and

Alcohol Dependence. Handbook of Experimental Pharmacology. Vol. 45.

Heidelberg: Springer-Verlag, 1977, pp. 159-196.

144
Griffiths, R.R.; Bigelow, G.E.; and Liebson I.A. Human sedative selfadministration: Effects of interingestion interval and dose. J Pharmacol

Exp Ther 197:488-494, 1976.

Griffiths, R.R.; Bigelow, G.E.; and Liebson I.A. Human drug self-administration:

Double-blind comparison of pentobarbital, diazepam, chlorpromazine and

placebo. J Pharmacol Exp Ther 210:301-310, 1979.

Griffiths, R.R.; Bigelow, G.E.; and Liebson I.A. Differential effects of diazepam

and pentobarbital on mood and behavior. Arch Gen Psychiatry 40:865-

873, 1983.

Griffiths, R.R.; Bigelow, G.E.; Liebson I.A.; and Kaliszak, J.E. Drug preference

in humans: Double-blind comparison of pentobarbital, diazepam and

placebo. J Pharmacol Exp Ther 215:649-661, 1980.

Griffiths, R.R.; McLeod, D.R.; Bigelow, G.E.; Liebson I.A.; and Roache, J.D.

Relative abuse liability of diazepam and oxazepam: Behavioral and

subjective dose effects. Psychopharmacology 84:147-154, 1984a.

Griffiths, R.R.; McLeod, D.R.; Bigelow, G.E.; Liebson I.A.; Roache, J.D.; and

Nowowieski, P. Comparison of diazepam and oxazepam: Preference,

liking and extent of abuse. J Pharmacol Exp Ther 229:501-508, 1984b.

Griffiths, R.R. and Roache, J.D. Abuse liability of benzodiazepines: A review of

human studies evaluating subjective and/or reinforcing effects. In: Smith,

D.E. and Wesson, D.R. eds. The Benzodiazepines: Current Standards for

Medical Practice. Lancaster: MTP Press Limited, 1985, pp. 209-225.

Haertzen, C.A. Development of scales based on patterns of drug effects, using

the Addiction Research Center Inventory (ARCI). Psychol Rep 18:163-

194, 1966.

Healey, M.L. and Pickens, R.W. Diazepam dose preference in humans. Pharmac

Biochem Behav 18:449-456, 1983.

Addiction Research Center. National Research Council, Cambridge, MA.,

1977, pp. 133-168.

Jaffe, J.H.; Ciraulo, D.A.; Nies, A.; Dixon, R.B.; and Monroe, L.L. Abuse

potential of halazepam and of diazepam in patients recently treated for

acute alcohol withdrawal. Clin Pharamacol Ther 34:623-630, 1983.

Jasinski, D.R.; Griffith, J.D.; Pevnick, J.; Gorodetzky, C.; Cone, E.; and Kay, D.

Progress Report from the clinical pharmacology section of the NIDA

Jasinski, D.R.; Haertzen, C.A.; Henningfield, J.E.; Johnson, R.E.; Makhzoumi,

H.M.; and Miyasato, K. Progress Report of the NIDA Addiction Researach

Center. In: Harris, L.S., ed. Problems of Drug Dependence 1981:

National Institute on Drug Abuse Research Monograph No. 41.

Washington, D.C.: Supt. of Docs., U.S. Govt. Print. Off., 1982. pp. 45-52.

Jasinski, D.R.; Henningfield, J.E.; Hickey, J.E.; and Johnson, R.E. Progress report

of the NIDA Addiction Research Center, Baltimore, Maryland, 1982. In:

Harris, L.S., ed. Problems of Drug Dependence 1982. National Institute

on Drug Abuse Research Monograph No. 43. DHEW Pub. No. (ADM)

83-1264. Washington, D.C.: Supt. of Docs., U.S. Govt. Print. Off., 1983.

pp. 92-98.

Johanson, C.E., and Uhlenhuth, E.H. Drug preference and mood in humans:

Diazepam. Psychopharmacology 71:269-273, 1980.

McLeod D.R., and Griffiths, R.R. Human progressive-ratio performance:

Maintenance by pentobarbital. Psychopharmacology 79:4-9, 1983.

145
Ortiz, A.; Pohl, R.; and Gershon, S. Azaspirodecanediones in generalized anxiety

disorder: Buspirone. J Affect Dis 13:131-143, 1987.

Pickens, R.; Cunningham, M.R.; Heston, L.L.; Eckert, E.; and Gustafson, L.K.

Dose preference during pentobarbital self-administration by humans.

J Pharmacol Exp Ther 203:310-318, 1977.

Roache. J.D. and Griffiths, R.R. Comparison of triazolam and pentobarbital:

Performance impairment, subjective effects and abuse liability.

J Pharmacol Exp Ther 234:120-133, 1985.

Roache, J.D. and Griffiths, R.R. Lorazepam and meprobamate dose effects in

humans: Behavioral effects and abuse liability. J Pharmacol Exp Ther

243:978-988, 1987.

Roache, J.D. and Griffiths, R.R. Diazepam and triazolam self-administration in

humans: Concordance of subject ratings, performance and drug selfadministration. Unpublished manuscript, 1988.

Roache, J.; Meisch, R.; Henningfield, J.; and Jaffe, J. The effects of yohimbine

on triazolam self-administration in subjects with histories of sedative

abuse. In: Harris, L.S., ed. Problems of Drug Dependence 1987:

National Institute on Drug Abuse Research Monograph No. 8 1. DHEW

Pub. No. (ADM) 88-1564. Washington, D.C.: Supt. of Docs., U.S. Govt.

Print. Off., 1988. pp 332.

Woods, J.H.; Katz, J.L.; and Winger, G. Abuse liability of benzodiazepines.

Pharmacol Rev 39:251-413, 1987.

ACKNOWLEDGMENTS

Preparation of this chapter was supported in part by USPHS Grant

DA 03889 from the National Institute on Drug Abuse.

AUTHORS

John D. Roache, Ph.D.

Assistant Professor

Department of Psychiatry & Behavioral Sciences

and Department of Pharmacology

The University of Texas Health Science Center at Houston

and The University of Texas Mental Sciences Institute

Houston, Texas 77030

Roland R. Griffiths, Ph.D.

Professor of Behavioral Biology and Professor of Neuroscience

Department of Psychiatry & Behavioral Sciences

and Department of Neuroscience

The Johns Hopkins University School of Medicine

Baltimore, Maryland 21205

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CHAPTER 8

Drug Self-Administration Procedures:

Alcohol and Marijuana

Nancy K. Mello, Ph.D.

INTRODUCTION

Traditionally, drug self-administration procedures have been used in

animal models to evaluate the abuse liability of new drugs (Schuster and

Johanson 1974; Griffiths et al., 1980, Brady and Lukas 1984). Although

there are many variations on the basic experimental paradigm, usually the

reinforcing efficacy of a new drug is compared to a standard drug of

known abuse potential and to a placebo control in the same animal under

the same conditions. The behavioral measures include the rate of response for drug injections, the number of drug injections taken, and in

some instances, the number of responses an animal is willing to emit for

a single drug injection. Comparison of these behavioral measures permits a rankordering of the new compound against placebo control and the

standard drug with respect to relative abuse potential.

Clinical research on drug self-administration procedures has used very

similar operant behavioral techniques. But the primary focus of clinical

studies has usually been quite different from the animal studies of drug

abuse liability insofar as human research subjects are given access to

drugs that are known to be abused, such as alcohol, marijuana, opiates,

stimulants or sedatives. Subjects are volunteers with a history of drug use

or drug addiction and patterns of drug self-administration as well as the

effects of drug intoxication are observed. Clinical studies usually are

multidisciplinary and involve examination of a number of behavioral,

biological and social variables before, during and after a period of selfregulated drug intoxication. Clinical drug self-administration studies are

useful for the evaluation of new pharmacotherapies, as well as studies of

the basic behavioral pharmacology of abused drugs and interactions

between drugs. These applications of clinical drug self-administration

studies are summarized below.

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Pharmacotherapy Evaluation: Several new pharmacotherapies have been

developed for the treatment of opiate abuse and evaluated under controlled research ward conditions. Recently the efficacy of naltrexone, an

opiate antagonist, and of buprenorphine, an opioid mixed agonist-antagonist, for the pharmacologic treatment of opiate addiction has been

examined in human drug self-administration studies (Meyer and Mirin

1979; Mello&., 198 1, 1982). Although medical considerations limited

the number of heroin injections available each day, it was possible to

examine the effects of naltrexone and of buprenorphine (with their respective placebos) on heroin self-administration (Meyer and Mirin 1979;

Mello et al., 1981, 1982). Demonstration of the effectiveness of buprenorphine and naltrexone in suppressing heroin self-administration

suggested the potential effectiveness of these drugs for outpatient treatment of opiate-dependent patients.

Behavioral Pharmacology of Drug Abuse: A second application of drug

self-administration procedures in clinical studies is to examine the basic

behavioral pharmacology of drug use and abuse under controlled research ward conditions. In studies of alcohol and marijuana, subjects

were given unlimited access to drugs for several weeks while residing on

a clinical research ward. Subjects worked at an operant task for alcohol

or marijuana and a competing (non-drug) reinforcer such as money on

concurrent schedules of reinforcement. Behavioral measures included

rate of response, distribution of time spent working for drug and non-drug

reinforcers, and number and temporal distribution of drug units (drinks,

cigarettes) purchased.

One advantage of inpatient clinical studies is that drug use patterns and

drug effects can be observed directly, rather than relying on anecdotal or

retrospective reports. Hypotheses about drug effects and patterns of drug

use based on “street lore” can be examined objectively. A vast discrepancy between a subject’s recall of a drug intoxication experience and

objective measures during drug intoxication has been consistently observed in a number of laboratories (see Mello 1983 for review). The

observation that intoxication with alcohol and with opiates exacerbates

rather than alleviates feelings of depression, despondency, dysphoria,

and unworth greatly complicates our understanding of what is “reinforcing” about drug intoxication (Mello 1983, Mendelson and Mello 1985).

Yet, drug self-administration persists despite increased despondency and

anxiety. Clearly, simplistic concepts such as elevated mood and euphoria

do not adequately characterize drug effects during chronic drug selfadministration. These data complicate analysis and prediction of the

reinforcing properties of psychoactive drugs and raise continuing questions about the nature of drug reinforcement.

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Drug Interactions: Another advantage of inpatient clinical studies is that

interactions between drugs can be studied. For example, the effects of

intoxication with alcohol or opiates on tobacco smoking can be measured. Anecdotal reports that alcohol and marijuana act synergistically to

enhance intoxication can be examined directly by studying concurrent

use patterns. Since polydrug use appears to be an increasingly prevalent

pattern (Kreek 1987, 1989), the concurrent drug self-administration

paradigm should be especially valuable for determining how the availability of two or more drugs changes use patterns of a single drug.

The remainder of this review will describe basic techniques for the operant

analysis of human drug self-administration. Recent findings from human

drug self-administration studies will be summarized to illustrate selected

types of behavioral analyses. Some possible applications of these procedures for drug abuse liability assessment in humans will be described.

Finally, the concept of drug reinforcing efficacy and its implications for

the assessment of abuse liability will be discussed.

OVERVIEW OF OPERANT PROCEDURES FOR STUDIES OF

HUMAN DRUG SELF-ADMINISTRATION

In real life, drugs are not available without some expenditure of effort or

money and operant work-contingent drug self-administration is one

approach to simulating relatively unconstrained drug use patterns under

clinical research ward conditions. Operant techniques to study human

drug self-administration are derived from concepts and procedures for

the experimental analysis of behavior first described by B. F. Skinner

(Skinner 1938, 1953). Operant procedures permit direct observation of

the amount and frequency of drug self-administration and the behavioral

consequences of drug intoxication on operant performance.

A number of operant procedures have been used to examine human drug

self-administration since 1965 and the conceptual and technical evolution of these techniques has been reviewed elsewhere (see Bigelow et al.,

1975; Mello and Mendelson 1965, 1978, 1987). The feature common to

all of these operant procedures is that subjects must emit responses on a

specified schedule of reinforcement to obtain drugs or competing reinforcers such as money, television time, etc. In situations where subjects

are given unlimited access to drugs, the pattern of drug self-administration can be operationally defined by the following measures:

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(1) The number of drug self-administration occasions (per hour, per

day, per week).

(2) The drug dose selected on each occasion (e.g., number of drinks,

cigarettes or capsules.).

(3) The time of drug purchases within a day.

(4) The interval between successive drug self-administration occasions, i.e. the distribution of drug doses over an hour, a day, or a

week.

Operant procedures produce orderly sequences of responding which in

turn provide an objective index of the relative reinforcing consequences

of drugs or of competing reinforcers, such as money, at any point in time.

In situations where two drugs are available concurrently, effects of drug

use on choices between these alternative drug reinforcers can also be

examined to yield an index of relative reinforcing efficacy.

Although it is obvious that drug use and drug intoxication affect the

subsequent pattern of drug self-administration, it is useful to distinguish

between drug use patterns and drug effects. Behavioral measures of drug

effects on subjective states, performance tasks, social interaction variables and the acquisition of non-drug reinforcers often complement

evaluation of drug use patterns. One limitation of the study of spontaneous drug self-administration patterns is that precise time-dose-response

relationships between various drug-effect variables cannot be established

since the drug dose, frequency and inter-dose intervals will vary on an

unpredictable basis. Yet, this variability constitutes the drug self-administration pattern which is the primary dependent variable in many studies

of operant drug self-administration.

We have argued elsewhere that the pattern of drug self-administration is

an important dependent variable which may be central to our understanding of human substance abuse. Basic behavioral pharmacology has

repeatedly shown that the schedule of drug reinforcement, i.e., the dose

and frequency of drug availability, influences the effects of drugs on

behavior (Kelleher et al., 1976; Spealman et al., 1983). The self-imposed

schedule of reinforcement can be examined in individuals given an

opportunity to determine their own pattern of drug self-administration.

Eventually, the comparison of drug self-administration patterns across

drugs may help to identify some commonalities and differences in the

proximal determinants of patterns of heroin abuse, alcohol abuse, marijuana and tobacco use, etc.

The schedule of reinforcement and the type of operant manipulanda are

two basic factors which define any drug self-administration paradigm.

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The schedule of reinforcement specifies the number and/or pattern of

responses required for acquisition of a single drug dose or monetary unit.

Time-based schedules, such as Fixed Interval or Variable Interval schedules are very useful in clinical research because time is the most relevant

dimension on a clinical research ward. Time based schedules specify that

only the first response emitted after a fixed or variable time interval

counts as an “effective” response towards drug acquisition. Ratio schedules require a specified number of responses for reinforcement. Fixed

or Variable Ratio schedule response requirements can often be completed in a few minutes (depending upon the operant manipulanda) and

there is no uniformity within or between subjects in duration of operant

responding. Ratio and Interval schedules can also be combined to form

multiple schedules. In a multiple schedule, completion of each component is required for reinforcement. If a stimulus (light or sound) is presented upon completion of a schedule component, the schedule is described as a second order schedule. A more detailed description of the

possible permutations of schedules of reinforcement appears in Ferster

and Skinner 1957; Kelleher et al., 1975; Spealman and Goldberg 1978;

and Spealman et al., 1983.

One critical methodological consideration in studies of human drug selfadministration is the difficulty or complexity of the operant performance

required for drug acquisition. A variety of types of operant manipulanda

have been developed in different laboratories (see Mello and Mendelson

1987 for review). Operant manipulanda vary in terms of the conceptual

and physical demands of the required task. On the dimension of physical

effort, both strenuous tasks such as riding an exercycle and effortless

tasks, such as breaking a photocell beam have been used (Bigelow et al.,

1976; Nathan et al., 1970). More conceptually demanding tasks have

required performance on a complex matching-to-sample device (Mello

1973) and assembly of a wooden stool (Miles et al. 1974).

In our laboratory, the primary question has usually been to examine

spontaneous patterns of drug acquisition and use and their relationship to

biological and behavioral variables (Mello and Mendelson 1978, 1987).

Consequently, we have used very simple tasks where drug intoxication

could not impair performance and thereby compromise drug acquisition.

The operant performance of social drug users who do not meet DSM III-r

criteria for substance abuse and dependence could be disrupted during

intoxication (DSM III-r 1987). However, alcohol-dependent individuals

develop behavioral tolerance for alcohol which permits effective performance on quite complex tasks (Mello 1973; Mello and Mendelson

1987).

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For the purpose of illustration, operant studies of drug self-administration conducted at the clinical research facility of the Harvard-McLean

Alcohol and Drug Abuse Research Center will be described. These clinical

studies have involved use of a portable manipulandum shown schematically in figure 1. Each response on the manipulandum transmits a radiofrequency signal on a discrete bandwidth which activates computer-based

programming and recording circuitry in an adjacent room. Operant

response patterns were automatically recorded by the computer and both

the rate of response and inter-response times could be measured.

Subjects were required to press the button on the manipulandum on a

time-based schedule, a fixed interval l-second scheduleof reinforcement

(FI-1 sec). Only the first response after 1 second elapsed was recorded

as an effective response by the programming circuitry. A signal light

flashed each time an effective response was made. Subjects could earn

one purchase point for 300 effective responses on an FI 1-sec schedule.

This schedule is designated as a second-order FR-300 (FI-1 sec:S) and

required at least 5 minutes of sustained operant work for each purchase

point. The number of purchase points required depended on the specific

reinforcer. Although subjects always performed on the same basic schedule of reinforcement, the cost for each drug dose could be varied by

changing the number of purchase points required. The prices of different

drugs or of money reinforcers could be assigned a purchase point cost

which reflected the current prevailing market rates. One advantage of a

time-based schedule such as an FI-1 sec schedule, is that the price of a

single drug dose can easily be translated into time required at the operant

task. For example, a drug that cost three purchase points required 15

minutes of operant work; a drug that cost six purchase points required 30

minutes of operant work.

Subjects were allowed to work on this operant task at any time and a

record of their point accumulation was continuously available on a control

panel in the Day Room. Whenever a subject elected to purchase a drug,

a marijuana cigarette or an alcohol drink, the points spent were immediately deducted from the accumulated reinforcement points. Points

earned for drugs and for money were not interchangeable. The total

amount of money earned over the course of the study was given to the

subject at the end of the study.

We have used this simple procedure to study self-administration of alcohol, marijuana and heroin and the concurrent self-administration of

marijuana and alcohol. (Mello et al., 1978, 1981, 1982, 1985, 1989;

Mendelson et al., 1976a, b and c; Mendelson and Mello 1988). The

manipulandum and the task have been acceptable to volunteer subjects.

152
They have not been able to tamper with or to destroy this device. Subjects

are able to perform the operant task while talking, reading, watching

television and eating. Although this manipulandum can be used with

virtually any schedule of reinforcement, we have continued to use the FI

1-sec schedule to permit comparisons across successive studies with

different types of drugs. This task has been shown to yield reliable data

on drug self-administration patterns as well as rates of operant responding.

Figure 1: Portable operant

manipulandum used to study

heroin, marijuana and

alcohol self-administration.

Each response transmits a

radio frequency signal to the

programming circuitry.

Reprinted with permission

from M. A. Bozarth (ed.),

Methods of Assessing the

Reinforcing Properties of

Abused Drugs. NY: SpringerVerlag, 1987, p. 537.

Operant Manipulandum

OPERANT STUDIES OF ALCOHOL, MARIJUANA AND

POLYDRUG SELF-ADMINISTRATION

Selected studies of alcohol, marijuana and concurrent marijuana and

alcohol self-administration using the portable operant manipulandum

and a second order FR-300 (FI-1 sec:S) schedule of reinforcement are

summarized in this section. These studies illustrate the application of

operant procedures in clinical research on drug self-administration. In

each study described below, volunteer subjects provided Informed Consent

and lived on a clinical research ward for several weeks. Subjects were

observed during a drug-free baseline, a period of drug self-administration, and a post-drug baseline period. An own-control design is essential

for human drug self-administration studies since the use of “normal”

drug-naive subjects as a control group in the conventional sense is precluded by both medical and ethical considerations. Behavioral studies

were conducted simultaneously with physiological, biochemical, and

neuroendocrine studies designed to examine the biological effects of

chronic drug use.

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Operant Studies of Alcohol Self-Administration

Twenty-six women who were social drinkers worked at a simple operant

task for alcohol for 21 days (Mello et al., 1989) and the effects of chronic

drinking on menstrual cycle function were concurrently evaluated

(Mendelson and Mello 1988). Women could also work for money, a nondrug reinforcer, throughout the 35 day study. Subjects could earn 50¢ or

could purchase one drink for six purchase points which required about 30

minutes of work on the operant task. One drink was a 50 ml miniature

of distilled spirits, one 12 ounce can of beer or one 12.5 ounce glass of

table wine. Five of the 26 women were classified as heavy drinkers and

they consumed an average of 7.8 drinks per day. Twelve women were

classified as moderate drinkers and they consumed an average of 3.8

drinks per day. Nine women were classified as occasional drinkers and

they drank an average of two drinks per day.

Drinking patterns in individual women are shown in figure 2. It is apparent that individual drinking patterns fluctuated markedly from day to day.

The heavy and moderate drinker each had more days of peak alcohol

consumption than the occasional drinker. The heavy drinker drank more

than the moderate drinker on each peak consumption day, i.e., the peaks

were of higher amplitude.

In an effort to quantify these individual variations in daily drinking patterns, we used a computerized analysis of pulse-frequency and pulseamplitude to define the number of daily peaks in alcohol consumption

and the interval between successive peaks. Group data were consistent

with individual patterns shown in figure 2. The moderate drinkers had

more peaks in alcohol consumption (a group average of 6.3) than the

heavy drinkers who averaged 5.6 peaks over 21 days. The occasional

drinkers had significantly fewer peaks in alcohol consumption than the

moderate drinkers and averaged 4.5 peaks. The average number of drinks

comprising each peak was significantly greater for the heavy and the

moderate drinkers, than for the occasional drinkers and were respectively

6.3, 5, and 2.6 drinks per peak. Although peaks in alcohol consumption

occurred more frequently for the moderate and heavy drinkers (every 3.2

and 3.6 days) than for the occasional drinkers (4.6 days), these differences were not statistically significant.

A marked cyclicity in alcohol consumption has been previously observed

in clinical research ward studies of alcohol-dependent men where alcohol

acquisition was contingent upon performance on an operant behavioral

task (Mello and Mendelson 1972; Nathan and O’Brien 1971; Nathan et

al., 1970). Alcohol-dependent men often alternated between working for

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Figure 2: Alcohol purchases per day (closed circle) and total purchase points earned

for both alcohol and money per day (open circle) by an individual heavy, moderate

and occasional drinker over 21 days of alcohol availability. The total number of

alcohol purchases and the total number ofpurchasepoints earned by each subject are

shown at the center top of each graph.

155
alcohol for 2 to 3 days and drinking for 2 to 3 days (Mello and Mendelson

1972). These alternate periods of drinking and alcohol abstinent working

corresponded to many alcoholics’ self-reports of “spree” drinking in the

real world. The abrupt cessation of drinking and accompanying rapid fall

in blood alcohol levels were often associated with alcohol withdrawal

signs and symptoms. A marked cyclicity in alcohol administration has

also been seen in alcohol self-administration studies in a primate model

using both an intravenous (Winger and Woods 1973; Woods et al., 1971)

and an intragastric (Altshuler and Tally 1977) route of alcohol administration (see Mello 1979 for review). In contrast, figure 2 shows that days

of maximal drinking were significantly correlated with days of maximal

operant work in female social drinkers. Alcohol did not impair operant

performance in heavy, moderate or occasional social drinkers (Mello et

al., 1989).

Operant Studies of Marijuana Self-Administration

A number of studies of operant work-contingent acquisition of marijuana

have been conducted to evaluate the effects of marijuana on behavior and

physiological parameters (Mendelson et al., 1974, 1976; Miles et al.,

1974; Mello and Mendelson 1985). The behavioral effects often ascribed

to marijuana include apathy, lethargy, diminished “drive” and ambition,

decreased productivity and goal directedness, and indolence. Clinical

evidence suggests that these apparent motivational impairments may

reflect problems unrelated to marijuana use (Kolansky and Moore 1972;

Negrete 1983, Halikas 1974). The hypothesis that marijuana induces an

“amotivational” syndrome has persisted despite the lack of supporting

evidence in behavioral studies.

In each study where marijuana availability was contingent upon performance of an operant task, subjects worked far longer than was required to earn the marijuana smoked and usually accumulated points for

money. In one of the early studies, subjects were limited to earning a

maximumof 60,000 points on a Fixed Ratio schedule each day (Mendelson

et al., 1974). In that study, subjects consistently earned the maximum

number of points available and showed no evidence of a marijuanainduced impairment in work and/or motivation (Mendelson et al., 1974).

In subsequent studies, subjects were given unlimited access to marijuana

for 21 days contingent upon operant task performance under controlled

research ward conditions. When subjects could earn a 1 gram marijuana

cigarette (or 50¢) by 30 minutes of sustained performance on a simple

operant task, both men and women worked far more hours each day than

was necessary to earn the number of marijuana cigarettes they smoked

(Mendelson et al., 1976b; Mello and Mendelson 1985). Subjects contin156
ued to perform the operant task after smoking 10 or more marijuana

cigarettes per day. Women showed no marijuana dose-related effects on

operant performance (Mello and Mendelson 1985). The heavy, moderate

and occasional marijuana smokers smoked an average of 6.1 (±1.45),

2.72 (±0.16) and 0.90 (±0.22) marijuana cigarettes per day. These three

groups did not differ in operant purchase points earned, hours worked or

money earned. Some womencontinued to workformoney while smoking

15 to 20 marijuana cigarettes per day and the period of maximal operant

work coincided with the periods of maximal marijuana smoking (noon to

midnight) (Mello and Mendelson 1985). Illustrative data for women who

were heavy marijuana smokers are shown in figure 3. The concordance

between marijuana smoking and operant performance is similar to data

shown in figure 2 for social drinkers.

A lack of significant effects of high doses of marijuana on performance

is consistent across studies in men and women (Lessin and Thomas 1976;

Mendelson et al., 1974, 1976; Mello et al., 1978; Mello and Mendelson

1985; Miles et al., 1974). The hypothesis that marijuana induces an

“amotivational syndrome” wouldpredictthatmarijuana availability would

decrease operant performance and that subjects would not work for money

during marijuana intoxication. Consequently, these data are not compatible with the hypothesis that marijuana smoking produces an “amotivational” syndrome, since subjects continued to work for money, a conventional reinforcer, as well as for marijuana even during heavy marijuana

smoking.

Moreover, heavy marijuana users tended to increase marijuana smoking

during a 21 day period of marijuana availability (Mendelson et al., 1976;

Mello and Mendelson 1985). The major difference between men and

women studied under comparable conditions was that all men increased

marijuana smoking over time (Mendelson et al., 1976), whereas the female

moderate and occasional marijuana smokers either decreased marijuana

smoking or maintained a relatively stable pattern of marijuana use across

the 21 days of marijuana availability (Mello and Mendelson 1985).

Operant Studies of Concurrent Marijuana and Alcohol Self-Administration

Probably the most effective way in which continuous access drug selfadministration procedures can be used to compare the relative reinforcing properties of drugs is when two or more drugs are concurrently

available, contingent upon operant performance. There have been relatively few such studies and the primary behavioral question has usually

been to determine if the simultaneous availability of two drugs, such as

157
Figure 3: Daily patterns of marijuana purchases and total points earned by three

women classified as heavy marijuana smokers. The number of 1 gram marijuana

cigarettes, (1.8 to 2.3 percent THC) purchased each day are shown as closed

circles. The total number of points earned for marijuana and for money each day are

shown as open circles. The total number of marijuana cigarettes purchased and the

total number of points earned during the 21 days of marijuana availability are shown

at the top of each figure. These data were adapted from Mello and Mendelson 1985.

158
marijuana and alcohol, will result in a significant increase or decrease in

the use of one or both drugs (Mello et al., 1978). Patterns of drug use

during 10 days of concurrent access to marijuana and alcohol were

compared with consecutive 5 day periods when only alcohol or only

marijuana were available. Sixteen male volunteers with a history of

concurrent alcohol and marijuana use lived on a clinical research ward for

34 consecutive days. Subjects could earn money (50¢) or marijuana (a

1 g cigarette; 1.8-2.3 percent THC) by working at the simple operant

task on a Fixed Interval 1 sec schedule of reinforcement for 30 minutes.

Alcohol (30 ml) was available as wine, beer, or distilled spirits for 15

minutes of operant work.

Fourteen of the 16 subjects drank less alcohol when marijuana was

concurrently available and alcohol consumption remained depressed

throughout the 10 day period. Seven of the 14 subjects drank significantly less alcohol during concurrent marijuana availability than when

only alcohol was available (P < .05-.001). Figure 4 shows average alcohol and marijuana consumption by four heavy drinkers. Twelve subjects

smoked slightly more marijuana when alcohol was available but the

magnitude of this increase was not significant in ten instances. Only two

subjects increased use of both alcohol and marijuana during concurrent

alcohol and marijuana availability. Although alcohol and marijuana were

usually used together, there were no instances of adverse reactions or

other evidence of toxic drug interactions.

These data are not consistent with the notion that the simultaneous availability of marijuana and alcohol will lead to a significant increase in the use

of both drugs. Rather, alcohol consumption decreased when marijuana

was available and marijuana use tended to increase through time independently of concurrent alcohol availability (Mello et al., 1978). Subsequent studies of the acute effects of concurrent alcohol and marijuana use

suggest that pre-treatment with marijuana may delay gastric emptying

and therefore delay alcohol absorption and intoxication (Lukas unpublished observations).

Tobacco Smoking During Other Drug Use: The question of how the

availability of one drug affects the concurrent use of another drug has

most often been asked in connection with tobacco smoking during other

drug self-administration (see Mello and Mendelson 1986 for review). In

most instances, tobacco was freely available rather than contingent upon

performance of an operant task. Tobacco cigarette smoking usually

increases during intoxication with alcohol, opiates, and certain stimulants (Mello and Mendelson 1986). Increased tobacco smoking during

159
Figure 4: Average alcohol and marijuana purchases per day (mean ± S.E.) by four

individual subjects. Columns 1 and 2 show alcohol purchases when only alcohol was

available and when both alcohol and marijuana were available. Columns 3 and 4

show marijuana cigarette purchases when only marijuana was available and when

alcohol and marijuana were concurrently available. These data were adapted from

Mello et al.. 1978, table 1.

160
other drug intoxication has been consistently observed in studies using

different experimental paradigms. These findings are summarized schematically in figure 5.

Figure 5.

The interactions between tobacco smoking and alcohol consumption

have been most frequently studied. It has been consistently observed that

alcohol consumption is associated with increased cigarette smoking in

social drinkers as well as in alcohol-dependent individuals (Griffiths et

al., 1976; Mello et al., 1978, 1987; Henningfield et al., 1983, 1984; see

Mello and Mendelson 1986 for review), In social drinkers, both daily

alcohol consumption and administration of a single dose of alcohol

appear to facilitate cigarette smoking (Mello et., 1980a, 1987; Henningfield et al., 1984).

Heroin and methadone intoxication also are associated with increased

cigarette smoking by opiate addicts (Mello et al., 1980b, Chait and Griffiths 1984). Moreover, a gradual decrease in daily methadone maintenance dose was associated with decreased cigarette smoking (Bigelow

et al., 198 1). Administration of buprenorphine, an opioid mixed agonistantagonist, was also accompanied by significantly increased cigarette

smoking in heroin addicts (Mello et al., 1985) whereas opiate antagonists, such as naltrexone and naloxone, had no effect on total cigarettes

smoked or on smoking-related measures, including carbon monoxide

levels in expired air across the naloxone dose range studied (Mello et al.,

1980b; Nemeth-Coslett and Griffiths 1986).

In contrast to alcohol, opiates and certain stimulants, marijuana does not

appear to alter tobacco smoking in any systematic way (Mello and

Mendelson 1985; Nemeth-Coslett et al., 1986). Pre-treatment with a

single marijuana cigarette did not significantly change cigarette smoking

by volunteer subjects (Nemeth-Coslett et al., 1986). Cigarette smoking

161
during 21 days of operant work-contingent marijuana smoking was

examined in 16 women (Mello and Mendelson 1985). Cigarettes were

freely available upon request throughout the study. The amount and

temporal pattern of tobacco cigarette smoking during drug-free conditions did not change during concurrent marijuana use by either heavy or

moderate marijuana smokers (Mello and Mendelson 1985). Although it

might be expected that marijuana smoking and tobacco smoking would

be antithetical, both drugs were usually smoked in close temporal contiguity (Mello and Mendelson 1985). Concurrent studies of pulmonary

function indicated that single breath carbon monoxide diffusion capacity

was significantly lower in female marijuana smokers than in tobacco

cigarette smokers and non-smoker control subjects (Tilles et al, 1985).

The facilitator-y effect of alcohol, opioid agonists, opioid mixed agonistantagonists (Mello and Mendelson 1986) and some stimulants (Schuster

et al., 1979; Henningfield and Griffiths 1981) on cigarette smoking is

difficult to explain. Since these drugs have a broad spectrum of actions,

it is difficult to construct a plausible hypothesis concerning specific

pharmacological effects on cigarette smoking. These data illustrate the

difficulty in adequately specifying the nature of the reinforcer in polydrug

use. Simultaneous use of drugs which appear to have contradictory

pharmacological effects is especially puzzling (Mello 1983). Since

multiple drug use appears to be an increasingly common pattern (Kreek

1987, 1989), the way in which drugs interact to modulate use patterns is

an important area for further study.

ISSUES IN THE PREDICTION OF DRUG ABUSE LIABILITY

IN HUMANS

Clinical research on spontaneous drug use patterns and assessment of

drug effects during intoxication has shown that the behavioral effects of

drugs are very complex. Figure 6 graphically depicts some of the reported “positive” and “negative” effects of intoxication with alcohol,

marijuana, opiates, and other abused substances. If drug intoxication

were consistently associated with “positive” consequences and these

effects could be clearly described, then the prediction of the abuse liability of new drugs might be relatively simple. If a test drug produced more

“positive” than “negative” effects, would this necessarily predict drug

abuse liability? The answer is a qualified no. Chronic intoxication with

alcohol and heroin is often associated with increased dysphoria and anxiety

rather than with alleviation of depression or induction of tranquility or

elation (see Mello 1983 for review).

162
One of the most perplexing aspects of chronic alcohol and opiate abuse

is the discordance between the commonly anticipated and observed

changes in reports of subjective states (see Mello 1983 for review). Several

studies have shown that alcohol-dependent men tend to recall their anticipated positive reactions to alcohol rather than the depression, anxiety and

lowered self-esteem consistently observed during alcohol intoxication.

Clinical studies further suggest that alcohol-dependent men have a very

clear recollection of their first drink, but the first drink was memorable

because it was associated with intoxication and attendant nausea, vomiting and despondency, not with positive feelings. Similarly, the acute

effects of opiates, barbiturates, and nicotine in naive users may be associated with nausea, vomiting, anxiety and other adverse effects which

could not be considered positive or pleasurable in the usual sense (Mello

1983). Some opiate abusers report a more positive initial reaction to

opiates and other abused drugs, but these findings are the exception

(Haertzen et al., 1983). Yet, it is obvious that drug use continues despite

the initial aversive consequences and despite the many adverse consequences of chronic intoxication.

One implication of data on the dysphoric effects of drug intoxication is

that there is no simple formula for the prediction of drug abuse liability.

Mild to severe negative consequences of drug intoxication do not necessarily preclude drug abuse. Phencyclidine abuse is one compelling

example which illustrates that psychotic reactions, stupor, and life-threatening coma may not deter the phencyclidine abuser (Mello 1978).

Conversely, a preponderance of “positive” effects of drug intoxication

may not necessarily ensure abuse liability. It is difficult to think of an

example of a drug that induces only positive effects.

In contrast to chronic use, acute drug intoxication often may be associated with primarily positive effects. Transient positive changes in mood

often occur during the rising phase of the plasma drug concentration

curve. Opiates and cocaine may produce positive changes in feeling state

within seconds or minutes following intravenous administration. Alcohol may produce positive mood changes within 30 to 90 minutes after

drinking, during the rising phase of the blood alcohol curve. Positive

mood changes are often associated with transient increases in electroencephalogram (EEG) alpha activity (Lukas et al., 1987). However, during

the falling phase of the drug concentration curve, negative and dysphoric

changes in feeling state may occur. The falling phase of the blood alcohol

curve may be associated with increased anxiety and dysphoria. The

dysphoric crash after the cocaine “high” is more dramatic, but similar. It

appears that the negative effects of chronic intoxication are reflected in

microcosm in the falling phase of the plasma drug concentration (Mello

1983).

163
Figure 6: A schematic diagram illustrating the disparate effects of drug intoxication

reported by naive and experienced drug users (see Mello 1983).

164
The seemingly paradoxical findings summarized schematically in figure

6 prompt the hypothesis that the aversive consequences of drug intoxication are one important component of the total reinforcing complex. To

minimize or dismiss these clinical data is to ignore an important behavioral consequence of drug intoxication. Moreover, there is considerable

evidence from basic behavioral science that seemingly aversive events

can maintain behavior leading to their repeated administration (see Mello

1983; Spealman et al., 1983 for review). Aversive stimuli such as electric

shock can maintain response behavior leading to shock administration.

Response-produced shock illustrates an important principle that the same

stimulus event may have either reinforcing or punishing effects depending on the conditions under which it is presented. The parallels between

these models of aversive control of behavior and the dysphoric effects of

drug intoxication are provocative. It is possible that the seemingly aversive

component of drug intoxication also may be reinforcing under certain

conditions. As indicated in figure 6, a reinforcer is any event that maintains behavior leading to its administration. Reinforcement is a neutral

term with no inherent “positive” or “negative” connotations. Meaningful

analysis of the way in whichdrugs serve as reinforcers andcontrol behavior

leading to their self-administration requires examination of all the discernible behavioral consequences. Any or all of these consequences may

be reinforcing and may contribute to drug abuse liability. Systematic

study of the relationship between the behavioral effects of drug intoxication and subsequent drug use may eventually clarify this issue. Verbal

behavior is often minimally correlated with behavior, and drug users

inaccurately recall the effects of drugs during intoxication. Consequently,

rather than relying upon recall during sobriety, there is no substitute for

direct observation of drug self-administration behavior, and there is no

adequate alternative to evaluating drug effects during intoxication.

The prediction of drug abuse liability is even further complicated by

polydrug use. Simultaneous use of drugs with contradictory pharmacologic effects such as cocaine and heroin or cocaine and alcohol further

challenges any simplistic hypothesis about optimal drug effects. It is

possible that any drug or drug combination that has definite stimulus

properties and behavioral effects may have abuse potential. Clinical data

on the dysphoric effects of drugs and accounts of polydrug use which

involve concurrent use of, for example, stimulants and depressants have

prompted the speculation that a change in state per se may be the critical

reinforcing component of drug intoxication. The direction of that change

in state, up or down, may be far less important than the change itself.

Insofar as drugs are stimuli leading to some change in subjective state, it

may be useful to think of drug self-administration as a form of stimulus

165
self-administration (Mello 1977, 1978, 1983). This hypothesis implies

that any drug which has definite stimulus properties, that is, behavioral

effects for the user, is a drug which has abuse potential. Once we achieve

a better understanding of the behavioral consequences of drug intoxication and the factors that maintain drug use and abuse, procedures for

predicting abuse liability as well as procedures for treatment intervention

should be more effective.

REFERENCES

Altshuler, H.L., and Talley, L. Intragastric self-administration of ethanol by the

rhesus monkey: An animal model of alcoholism. In: Seixas, F., ed.

Currents in Alcoholism. New York: Grune & Staddon, 1977, pp. 243-

253.

American Psychiatric Association Task Force on Nomenclature and Statistics:

Diagnostic and Statistical Manual of Mental Disorders (DSM-III).

Washington, DC.: American Psychiatric Association, 1980, pp. 494.

Bigelow, G.; Griffiths, R.; and Liebson, I. Experimental models for the

modification of human drug self-administration: Methodological

developments in the study of ethanol self-administration by alcoholics.

Fed Proc 34(9):1785-1792, 1975.

Bigelow, G.; Griffiths, R.; and Liebson, I. Effects of response requirement upon

human sedative self-administration and drug-seeking behavior. Pharmacol

Biochem Behav 5:681-685, 1976.

Bigelow, G.E.; Stitzer, M.L.; Griffiths, R.R.; and Liebson, I.A. Human

methadone detoxification: Opioid self-administration behavior, cigarette

smoking and withdrawal signs and symptoms as a function of progressive

dose reductions. Fed Proc 40:296, 1981.

Brady, J.V., and Lukas, S.E., eds. Testing for Physical Dependence

Potential and Abuse Liability. National Institute on Drug Abuse Research

Monograph No. 52, DHHS Pub. No. (ADM) 84-1332. Washington, D.C.:

Supt. of Docs., U.S. Govt. Print. Off., 1984, pp. 153.

Chait, L.D., and Griffiths, R.R. Effects of methadone on human cigarette

smoking and subjective ratings. J Pharmacol Exp Ther 229(3):636-640.

1984.

Ferster, C.B., and Skinner, B.F. Schedules of Reinforcement. New York:

Appleton, Century, Crofts, 1957, pp. 741.

Griffiths, R.R.; Bigelow, G.E.; and Henningfield, J.E. Similarities in animal and

human drug-taking behavior. In: Mello, N.K., ed. Advances in

Substance Abuse. Behavioral and Biological Research Vol. 1.

Greenwich, CT.: JAI Press Inc., 1980, pp. l-90.

Griffiths, R.R.; Bigelow, G.E.; and Liebson, I. Facilitation of human tobacco

self-administration by ethanol: A behavioral analysis. J Exp Anal Behav

25(3):279-292, 1976.

166
Haertzen, C.A.; Kocher, T.R.; and Miyasato, K. Reinforcements from the first

drug experience can predict later drug habits and/or addiction: Results

with coffee, cigarettes, alcohol, barbiturates, minor and major

tranquilizers, stimulants, marijuana, hallucinogens, heroin, opiates and

cocaine. Drug Alcohol Depend 11:147-165, 1983.

Halikas, J.A. Marijuana use and psychiatric illness. In: Miller, L.L., ed.

Marijuana Effects on Human Behavior, New York: Academic Press,

1974, pp. 265-302.

Henningfield, J.E., and Griffiths, R.R. Cigarette smoking and subjective

response: Effects of d -amphetamine. Clin Pharmacol Ther 30(4):497-

505, 1981.

Henningfleld, J.E.; Chait, L.D.; and Griffiths, R.R. Cigarette smoking and

subjective response in alcoholics: Effects of pentobarbital. Clin

Pharmacol Ther 33:806-812, 1983.

Henningfield, J.E.; Chait, L.D.; and Griffiths, R.R. Effects of ethanol on cigarette

smoking by volunteers without histories of alcoholism.

Psychopharmacology 82:1-5, 1984.

Kelleher, R.T.; Goldberg, S.R.; and Krasnegor, N., eds. Control of Drug Taking

Behavior by Schedules of Reinforcement. Baltimore: Williams &

Wilkins, 1976, pp. 555.

Kolansky, H., and Moore, W.T. Effects of marijuana on adolescents and young

adults. J Amer Med Assoc 222:35-41, 1972.

Kreek, M.J. Multiple drug abuse patterns and medical consequences. In:

Meltzer, H.Y., ed. Psychopharmacology: The Third Generation of

Progress. New York: Raven Press, 1987, pp. 1597-1604.

Kreek, M.J. Multiple drug abuse patterns: Recent trends and associated medical

consequences. In: Mello, N.K., ed. Advances in Substance Abuse.

Behavioral and Biological Research. Vol. 4 . Greenwich, CT.: JAI Press,

1989, in press.

Lessin, P.J., and Thomas, S.A. Assessment of the chronic effects of marijuana on

motivation and achievement: A preliminary report. In: Braude, M.C. and

Szara, S., eds. The Pharmacology of Marijuana. New York: Raven

Press, 1976, pp. 681-683.

Lukas, S.E.; Mendelson, J.H.; Woods, B.T.; Mello, N.K.; and Teoh, S.K.

Topographic distribution of EEG alpha activity during ethanol-induced

intoxication in women. J Stud Alcohol 50:176-185, 1989.

Mello, N.K. Short-term memory function in alcohol addicts during intoxication.

In: Alcohol Intoxication and Withdrawal: Experimental Studies. Vol. 35,

Advances in Experimental Medicine and Biology. New York: Plenum

Publishing Co., 1973, pp. 333-344.

Mello, N.K. Stimulus self-administration: Some implications for the predictions

of drug abuse liability. In: Thompson, T., and Unna, K.R., eds.

Predicting Dependence Liability of Stimulant and Depressant Drugs.

Baltimore: University Park Press, 1977, pp. 243-260.

Mello, N.K. Control of drug self-administration: The role of aversive

consequences. In: Peterson, R.C., and Stillman, R.C., eds. Phencyclidine

(PCP) Abuse: An appraisal. National Institute on Drug Abuse Research

Monograph No. 21. DHEW Pub. No. (ADM)78-728. Washington, D.C.:

Supt. of Docs., U.S. Govt. Print. Off., 1978, pp. 289-308.

167
Mello, N.K. Animal models of alcoholism: Progress and prospects. In:

Davidson, R.S., ed. Modification of Pathological Behavior, Experimental

Analysis of Etiology and Therapy. New York: Gardner Press Inc., 1979,

pp. 273-333.

Mello, N.K. A behavioral analysis of the reinforcing properties of alcohol and

other drugs in man. In: Kissin, B. and Begleiter, H., eds. The

Pathogenesis of Alcoholism. Biological Factors. Vol. VII. New York:

Plenum Press, 1983, pp. 133-198.

Mello, N.K. Etiological theories of alcoholism. In: Mello, N.K., ed. Advances

in Substance Abuse. Behavioral and Biological Research. Vol. 3.

Greenwich, CT: JAI Press, 1983, pp. 271-312.

Mello, N.K., and Mendelson, J.H. Operant analysis of drinking patterns of

chronic alcoholics. Nature 206:43-46, 1965.

Mello, N.K., and Mendelson, J.H. Drinking patterns during work-contingent and

non-contingent alcohol acquisition. Psychosom Med 34:139-164, 1972.

Mello, N.K., and Mendelson, J.H. Marijuana, alcohol and polydrug use: Human

self-administration studies. In: Krasnegor, N., ed. Self-administration

Abused Substances: Methods for Study. National Institute on Drug Abuse

Research Monograph No. 20. DHEW Pub. No.(ADM) 89-73904.

Washington, D.C.: Supt. of Docs., U.S. Govt. Print. Off., 1978, pp. 93-

127.

Mello, N.K., and Mendelson, J.H. Operant acquisition of marijuana by women.

J Pharmacol Exp Ther 235(1):162-171, 1985.

Mello, N.K., and Mendelson, J.H. Cigarette smoking: Interactions with alcohol,

opiates and marijuana. In: Braude, M.C., and Ginzburg H.M., eds.

Strategies for Research on the Interaction of Drugs of Abuse. National

Institute on Drug Abuse Research Monograph No. 68. DHHS Pub. No.

(86-1453). Washington, D.C.: Supt. of Docs., U.S. Govt. Print. Off.,

1986. pp.154-180.

Mello, N.K., and Mendelson, J.H. Operant analysis of human drug selfadministration: Marijuana, alcohol, heroin and polydrug use. In: Bozarth,

M.A., ed. Methods of Assessing the Reinforcing Properties of Abused

Drugs. New York: Springer-Verlag. 1987, pp. 525-558.

Mello, N.K.; Lukas, S.E.; and Mendelson, J.H. Buprenorphine effects on

cigarette smoking. Psychopharmacology 86:417-425, 1985

Mello, N.K.; Mendelson. J.H.; and Kuehnle, J.C. Buprenorphine effects on

human heroin self-administration: An operant analysis. J Pharmacol Exp

Ther 223:30-39, 1982.

Mello, N.K.; Mendelson, J.H.; Kuehnle J.C.; and Sellers M. Human polydrug

use: Marijuana and alcohol. J Pharmacol Exp Ther 207:922-935, 1978.

Mello, N.K.; Mendelson, J.H.; Kuehnle, J.C.; and Sellers, M.L. Operant analysis

of human heroin self-administration and the effects of naltrexone. J

Pharmacol Exp Ther 216(1):45-54. 1981.

Mello, N.K.; Mendelson, J.H.; and Palmieri, S.L. Cigarette smoking by women:

Interactions with alcohol use and menstrual cycle phase.

Psychopharmacology 93:8-15, 1987.

Mello, N.K.; Mendelson, J.H.; Palmieri, S.; and Lex, B.W. Operant acquisition of

alcohol by women. Submitted, 1989.

Mello, N.K.; Mendelson, J.H.; Sellers, M.L.; and Kuehnle, J.C. Effects of alcohol

and marijuana on tobacco smoking. Clin Pharmacol Ther 27(2):202-209,

1980a.

168
Mello, N.K.; Mendelson, J.H.; Sellers, M.L.; and Kuehnle, J.C. Effects of heroin

self-administration on cigarette smoking. Psychopharmacology 67:45-52,

1980b.

Mello, N.K.; Mendelson, J.H.; and Teoh, S.K. Neuroendocrine consequences of

alcohol abuse in women. In: Hutchings, D.E., ed. Prenatal Abuse of Licit

and Illicit Drugs. An NY Acad Sci, 1989, (in press).

Mendelson, J.H., and Mello, N.K. Alcohol: Use and Abuse in America. Boston,

MA: Little, Brown and Company, 1985, pp. 395.

Mendelson, J.H., and Mello, N.K. Chronic alcohol effects on anterior pituitary

and ovarian hormones in healthy women. J Pharmacol Exp Ther 245:407-

412, 1988.

Mendelson, J.H.; Babor, T.F.; Kuehnle, J.C.; Rossi, A.N.; Bernstein, J.G.; Mello,

N.K.; and Greenberg, I. Behavioral and biological aspects of marijuana

use. An NY Acad Sci 282:186-210, 1976a.

Mendelson, J.H.; Kuehnle, J.C.; Greenberg, I.; and Mello, N.K. Operant

acquisition of marijuana in man. J Pharmacol Exp Ther 198:42-53,

1976b.

Mendelson, J.H.; Kuehnle, J.C.; Greenberg, I.; and Mello, N.K. The effects of

marijuana use on human operant behavior: Individual data. In: Braude,

. . M.C., and Szara, S., eds. The Pharmacology of Marijuana. New York:

Raven Press, 1976c, pp. 643-653.

Mendelson, J.H.; Rossi, A.M.; and Meyer, R.E., eds. The Use of Marijuana: A

Psychological and Physiological Inquiry. New York: Plenum Press,

1974.

Meyer, R.E., and Mirin, S.M. The Heroin Stimulus New York: Plenum Press,

1979, pp. 254.

Miles, C.G.; Congreve, G.R.S.; Gibbins, R.J.; Marshman, J.; Devenyi, P.; and

Hicks, R.C. An experimental study of the effects of daily cannabis

smoking on behavior patterns. Acta Pharmacol Toxicol 34:1-44, 1974.

Nathan, P.E., and O’Brien, J.S. An experimental analysis of the behavior of

alcoholics and nonalcoholics during prolonged experimental drinking: A

necessary precursor of behavior therapy. Behav Therap 2(4):455-476,

1971.

Negrete, J.C. Psychiatric effects of cannabis use. In: Fehr, K.O., and Kalant, H.,

eds. Cannabis and Health Hazards. Toronto, Canada: Addiction

Research Foundation, 1983, pp. 577-616.

Nemeth-Coslett, R., and Griffiths, R.R. Naloxone does not affect cigarette

smoking. Psychopharmacology 89:261-264, 1986.

Nemeth-Coslett, R.; Henningfield, J.E.; O’Keeffe, M.K.; and Griffiths, R.R.

Effects of marijuana smoking on subjective ratings and tobacco smoking.

Pharmacol Biochem Behav 25:659-665, 1986.

Schuster, C.R., and Johanson, C.E. The use of animal models for the study of

drug abuse. In: Gibbons, R.J.; Israel, Y.; Kalant, H.; Popham, R.E.;

Schmidt, W.; and Smart, R.G., eds. Recent Advances in Alcohol and

Drug Problems. Vol. 1. New York: Wiley and Sons, 1974, pp. 1-31.

Schuster, C.R.; Lucchesi, B.R.; and Emley, G.S. The effects of d-amphetamine,

meprobamate and lobeline on the cigarette smoking behavior of normal

human subjects. In: Krasnegor, N., ed. Cigarette Smoking as a

Dependence Process. National Institute on Drug Abuse Research

Monograph No. 23. DHEW Pub. No. (ADM)79-800. Washington, D.C.:

U.S. Govt. Print. Off,, 1979, pp. 91-99.

169
Skinner, B.F. The Behavior of Organisms. An Experimental Analysis. New

York: Appleton Century-Crofts, 1938, pp. 457.

Skinner, B.F. Science and Human Behavior. New York: Macmillan Company,

1953.

Spealman, R.D., and Goldberg, S.R. Drug self-administration by laboratory

animals: Control by schedules of reinforcement. An Rev Pharmacol

Toxicol 18:313-339, 1978.

Spealman, R.D.; Goldberg, S.R.; and McGivney, W.T. Schedule determinants of

the behavioral effects of opioids and opioid antagonists. In: Mello, N.K.,

ed. . Advances in Substance Abuse. Behavioral and Biological Research.

Vol. III. Greenwich, C.T: JAI Press, Inc: 1983, pp. 63-101.

Tilles, D.; Goldenheim, P.; Johnson, D.C.; Mendelson, J.H.; Mello, N.K.; and

Hales, C.A. Marijuana smoking causes a reduction in single breath carbon

monoxide diffusing capacity. Am J Med 80:601-606, 1986.

Winger, G.D.. and Woods, J.H. The reinforcing property of ethanol in the rhesus

monkey: I. Initiation, maintenance and termination of intravenous

ethanol-reinforced responding. In: Seixas, F.A., and Eggleston, S., eds.

Alcoholism and the Central Nervous System. An NY Acad Sci 215: 162-

175, 1973.

Woods, J.H.; Ikomi, F.I; and Winger, G. The reinforcing properties of ethanol.

In: Roach, M.K.; McIsaac, W.N.; and Creaven, P.J., eds. Biological

Aspects of Alcoholism. Austin: University of Texas Press, 1971, pp. 371-

388.

ACKNOWLEDGMENTS

Preparation of this review was supported in part by Grant Nos. DA 00101,

DA 04059 and DA 025 19 from the National Institute on Drug Abuse and

Grants Nos. AA 04368 and AA 06252 from the National Institute on

Alcohol Abuse and Alcoholism, ADAMHA.

AUTHOR

Nancy K. Mello, Ph.D.

Professor of Psychology (Neuroscience)

Alcohol and Drug Abuse Research Center

Harvard Medical School-McLean Hospital

115 Mill Street

Belmont, Massachusetts 02178

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CHAPTER 9

The Use of Choice Procedures for Assessing the

Reinforcing Properties of Drugs in Humans’

Chris E. Johanson, Ph.D.

Harriet de Wit, Ph.D.

INTRODUCTION

This presentation will review a series of studies that were conducted at

the University of Chicago beginning in 1978 on the reinforcing properties

of psychomotor stimulants, benzodiazepines, and alcohol in humans using

a preference procedure. These studies were conducted in collaboration

with several other investigators including E.H. Uhlenhuth, L. Chait, and

S. McCracken but they owe their initiation and continuation to the

encouragement of Charles R. Schuster. The initial purpose of these

human self-administration studies was to validate a choice methodology

that our group developed for use with rhesus monkeys. The procedure

with animals was designed to evaluate the relative reinforcing properties

of drugs as a means of more accurately predicting dependence potential

(e.g., Johanson and Schuster 1975; Johanson 1975). The validity of these

predictions was hard to evaluate because of the difficulties of obtaining

accurate survey data, such as that provided by the Drug Abuse Warning

Network (DAWN). However, if studies performed with normal human

volunteers using a choice, or preference procedure yielded predictions

that were comparable to those obtained with rhesus monkeys, this might

indicate that the approach of using animals was at least as useful for

predicting dependence potential as human studies (see Johanson et al.,

1987, for a discussion of validity issues). In addition to the desire to

validate animal models, there was renewed interest at that time in

developing new approaches using humans for the prediction of dependence

potential. This renewed interest was in part due to the legal changes

which had occurred in the mid-1970s that prohibited the use of prisoner

1

 The opinions expressed are those of the authors and do not necessarily reflect the

views of the Department of Defense of the Uniformed Services University of Health

Sciences.

171
volunteers as experimental subjects at the Addiction Research Center

(ARC) in Lexington, KY. This history is reviewed by Jaffe and Jaffe (this

volume).

It is important to state explicitly a major assumption of the studies to be

described. The assumption derives from the results of animal studies

which have shown that the drugs which animals self-administer, or which

function as positive reinforcers, are the same drugs that humans abuse

(Johanson and Balster 1978). Likewise, drugs which are not selfadministered, such as chlorpromazine, are drugs which are not considered

drugs of abuse for humans. Although there are exceptions in both

directions, the correlation between predictions that could be made on the

basis of results from animal studies and the actual abuse of drugs by

humans is so good that results from animal drug self-administration studies

are routinely used for making drug scheduling decisions at the international

level. This assumption of a direct relationship between reinforcing

properties and dependence potential was used as a basis for our human

choice studies. The assumption was broadened in subsequent studies

designed to assess risk factors predisposing certain individuals to abuse

a drug to include the notion that in order for a drug to be abused by an

individual, it must initially function as a reinforcer. All else being equal,

a human who finds a drug reinforcing will be more likely to abuse that

drug than an individual who does not. However, this condition of drug

reinforcement is necessary but not sufficient, since other factors (e.g.,

availability, peer pressure, punishment, cost) subsequently influence the

likelihood that an individual begins abusing a drug. Interestingly, many

of these other factors can be studied experimentally in humans as well as

animals but, to date, few studies have been attempted (e.g., Johanson

1977; Griffiths et al, 1974).

Although the major aim of the research was to simulate procedures used

in animals, an additional component of the design was to concurrently

measure actual drug-taking behavior, or self-administration, and subjective

drug effects. Previous studies in humans that had been conducted at the

ARC focused on evaluating the physiological and subjective effects of

drugs in drug-experienced participants. Martin, Jasinski and their

colleagues had published an extensive series of studies on the physiological

and subjective effects of classic drugs of abuse such as the opiates (Jasinski

1973; Jasinski et al. 1968, 1970; Martin et al. 1973), the amphetamines

(Jasinski et al. 1974; Martin et al. 1971; Martin 1973), and sedatives

(Jasinski 1973). The purpose of their investigations had been to provide

a complete pharmacological profile of these drugs to be used as standards

of comparison. Further, it was assumed that these profiles of action were

clues to understanding the mechanisms responsible for their abuse. The

172
extent to which other drugs shared characteristics provided a basis for

predicting their dependence potential as well as mechanism of action.

However, these studies had not attempted to correlate subjective and

physiological effects with actual drug-taking. Thus, in order to determine

their correspondence, we combined the approach used at the ARC of

measuring subjective effects with the approach in animals of assessing

self-administration behavior.

There are several ways in which the experimental design that has been

used in these preference studies can be distinguished from the approach

used by other investigators such as Roache and Griffiths (this volume)

and Fischman (this volume). First, normal human volunteers, rather than

present or past drug abusers were recruited for participation. Using this

type of population allows an estimate of the dependence potential of a

drug in initial drug users rather than in populations that have already

demonstrated a propensity for abusing drugs of a particular type. As will

be seen when subsequent studies are described, the use of normal human

volunteers allows certain types of experimental questions to be addressed

that could not be evaluated in participants who were already experienced

drug users. Conversely, there are experimental questions that cannot be

addressed using volunteers without extensive drug experience.

A second major difference in the experimental protocol was that for the

majority of studies, particularly the ones conducted initially, participants

did not remain in a laboratory environment after drug ingestion. Because

participants were allowed to leave, it was also necessary to use low and

infrequent doses of drugs. Allowing participants to return to their normal

day-today activities has probably had a major impact on the results and

it is possible that such results, generated outside the constraints of a

laboratory, may be more generalizable to naturalistic conditions. However,

it is also important to compare results across environmental conditions to

determine the importance of this variable, particularly since it is not

feasible to test certain classes of drugs outside the laboratory.

INITIAL STUDIES

We begin this review by describing in detail the first two experiments that

were conducted in order to illustrate the general methodology (Johanson

and Uhlenhuth 1980a,b). In addition, the results generated by these two

initial experiments formed the basis for two series of subsequent studies

that investigated the influence of different classes of variables on the

reinforcing properties of stimulants and depressants.

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One of the initial studies (Johanson and Uhlenhuth 1980a) was designed

to determine whether normal human volunteers would self-administer 5

mg d-amphetamine, a drug which has been shown in animal studies to

function as a positive reinforcer (Balster and Schuster 1973). The second

study evaluated the reinforcing properties of several doses of diazepam

(Johanson and Uhlenhuth 1980b). The reinforcing properties of this drug

have also been tested in animals. Although responding can be maintained

by this drug, the reinforcing properties of benzodiazepines in general are

not robust (Bergman and Johanson 1985; Ator and Griffiths 1987).

Therefore, by selecting two drugs that might lead to different results, the

specificity of the procedure could be evaluated.

Participants

The participants in the amphetamine experiment were 3 1 normal human

volunteers (10 female and 21 male) between the ages of 21 and 32. Ten

of these individuals also participated in the diazepam study. Candidates

were only accepted if they were considered normal and in good health,

based upon interviews and a physical examination, and were excluded if

they had any history of drug-related problems. The experimental protocol

was approved by the local institutional review board and participants

signed an informed consent which described the study in detail and

indicated all possible side effects across several drug classes. Each

participant agreed not to take other drugs except their normal amounts of

coffee and cigarettes 12 hr before and 6 hr after receiving drug. Volunteers

were paid for their participation.

Procedure

Each experiment consisted of three sessions per week over a 3-week

period for a total of nine sessions. During the first four sessions, the

participant reported to the experimental room in the morning. At that

time, he/she filled out mood forms that will be described later and received

a colored capsule for immediate ingestion. Approximately half of the

participants received drug during sessions 1 and 3 and placebo during

sessions 2 and 4. The order was reversed for the other half. For each

participant, each drug was dispensed in a capsule of a consistent and

distinctive color in order to facilitate identification. Capsule colors were

assigned randomly across participants to avoid the influence of color

preference. Each participant was instructed during the initial four sessions

to note the capsule colors and to try to associate each of the two colors

with the effects of the substances contained in them. After ingesting the

capsule, participants were free to leave. They took three additional sets

174
of mood forms with them, which they were to fill out 1, 3, and 6 hrs later.

During the last five sessions, the procedure was identical in every respect

except that the participants weregiven a choice of the two colored capsules

to ingest.

The amphetamine preference study consisted of a single 3-week

experiment comparing 5 mg d-amphetamine to placebo. In the diazepam

study, three separate experiments were conducted, in counterbalanced

order, comparing three doses of diazepam (2, 5, and 10 mg) to placebo.

The measure of preference, or choice, was the percentage of sessions that

active drug was selected. In the initial studies, these choice results were

analyzed using a two-tailed t-test, which assumes that by chance,

participants will choose one color on 50 percent of the choice sessions.

In later studies, a log-linear analysis was used because the 50 percent

assumption did not appear to be valid. Only significant results (p<.05)

will be described unless otherwise stated.

Subjective Effects: The only questionnaire that was used to assess mood

in the initial studies was an experimental version of the Profile of Mood

States (POMS; McNair et al., 1971). Thisversion consists of 72 adjectives

commonly used to describe momentary mood states. Participants indicate

how they feel at the moment in relation to each adjective on a 5-point

scale from “not at all” (0) to “extremely” (4). There are eight clusters of

adjectives which have been grouped using factor analysis. These clusters,

or scales, have been given names that reflect the adjectives includedin the

cluster (Anxiety, Depression, Anger, Vigor, Fatigue, Confusion,

Friendliness, and Elation). The value of each scale is determined by

adding the numbers checked for each adjective and dividing the total by

the number of adjectives in that cluster. Two additional scales (unvalidated)

were derived from other scales: Arousal = (Anxiety + Vigor) — (Fatigue

+ Confusion); Positive Mood = Elation — Depression.

The scores of the POMS scales were averaged for each participant at each

time period (prior to ingestion [0] and 1, 3, and 6 hrs post-ingestion)

separately across drug sessions and across placebo sessions. If a significant

(p < 0.05) drug x hour interaction was found, further statistical tests were

conducted to determine at which hours the scores for drug and placebo

were significantly different. In some cases, the subjective effects were

averaged across the entire 9-session experiment whereas in other studies,

only data from the sampling sessions were used in order to avoid possible

confounding because of expectancies. Unless specified otherwise, only

significantresults will be discussed and it should be assumed that changes

are described in relationship to placebo scores.

175
In subsequent studies, many additional questionnaires (e.g., Addiction

Research Center Inventory (ARCI), visual analog scales, measures of

liking, drug identification) were used to assess subjective effects. In

general, these questionnaires were analyzed like the POMS although in

some cases, t-tests and analyses were more appropriate. These additional

measures have been extremely important in assessing reliability of the

evaluation of subjective effects by providing verification across

instruments of a specific change in mood (e.g., Anxiety scale of the

POMS and “anxiety” as measured by a visual analog scale). However,

the results from these other mood scales will only occasionally be reported

and the reader is referred to the original publications.

Results

Figures 1 and 2 show the results

of the amphetamine and

diazepam studies. Amphetamine in this experiment was

chosen an average of four out

of five opportunities. In

contrast, 2 mg diazepam was

chosen at chance level whereas

at the higher doses of 5 and 10

mg, participants preferred the

capsule containing placebo.

However, one of the participants preferred both 5 and

10 mg diazepam over placebo Figure 1: The number of participants

on all five choice sessions. In (ordinate) who chose 5 mg d-amphetamine 0

additional experiments con- to 5 times (abscissa) during the 5 choice

ducted with this participant, he

sessions (Johanson and Uhlenhuth 1980a).

chose 5 mg diazepam over both 5 and 10 mg d-amphetamine on four of

the five choice sessions (data not shown). Thus, while the majority of

participants did not choose to self-administer diazepam, there may be

individuals who do prefer diazepam. As will be reviewed a little later,

subsequent studies with diazepam have attempted to determine whether

such individual differences are related to other variables or are predictable.

The subjective effects of amphetamine and diazepam were typical of

stimulants and depressants and the results indicated that the POMS was

a reliable and sensitive instrument for detecting mood changes of relatively

low doses and in a situation where the participants were not confined to

176
a laboratory environment. Amphetamine produced increases in Vigor,

Elation, Friendliness, Arousal, and Positive Mood and decreases in

Confusion. These effects were time-related, peaking at the 3 hr evaluation.

In the 2 mg diazepam experiment, there were no significant changes in

the POMS. In the experiments comparing the two higher doses of diazepam

to placebo, diazepam produced dose-dependent decreases in Vigor and

Arousal and increases in Confusion and Fatigue. These effects were most

pronounced after 1 hr and had disappeared after 3 hr for the 5 mg dose and

after 6 hr for the 10 mg dose.

In summary, the initial two studies indicated that amphetamine was selfadministered whereas in the same population, diazepam did not function

as a reinforcer. These results were similar to those found in animal

studies. In addition, there was a logical relationship between choice

behavior and subjective effects. Amphetamine produced changes in

mood that could be interpreted

as positive (e.g., increases in

Elation and Positive Mood)

feasible to use and that the

instrument measuring mood

effects was sensitive to

differences in dose, time

course, and type of drug. This

was particularly striking given

the low doses that had been

used and lack of control over

(ordinate) who chose diazepam during the

participants’ activities.

five choice sessions as a function of diazepam

dose.

whereas diazepam did not.

Methodologically, these

studies indicated that the

experimental design was

Figure 2: The percent of participants

REINFORCING PROPERTIES OF PSYCHOMOTOR

STIMULANTS

The results obtained with amphetamine, indicating that it functioned as

a positive reinforcer in normal volunteers even at a relatively low dose,

stimulated a series of studies that sought to investigate the reinforcing

properties of other psychomotor stimulant drugs (Johanson and Uhlenhuth

1978; 1982; Chait et al. 1987, 1988; Stem et al., 1989). This series of

studies illustrates one of the uses of the choice methodology, i.e., to

compare the reinforcing properties of a group of pharmacologically related

177
drugs. The assumption, as in the previous studies, is that such reinforcing

properties are a reflection of the dependence potential of these compounds.

This use of the choice methodology is reminiscent of the approach used

by the ARC of comparing the profile of different drugs within a

pharmacological class on a series of measures including subjective and

physiological ones (e.g., Martin et al., 1971). In the present case, however,

the comparison is made in terms of preference and profile of subjective

effects.

Seven stimulants as well as a higher dose of d-amphetamine have been

evaluated using the procedure described above in which number of choices

was used as the measure of reinforcing properties. All the drugs except

caffeine are marketed as anorectic agents but they differ in terms of their

purported central mechanism of action. These studies paralleled selfadministration studies in rhesus monkeys conducted concurrently at the

University of Chicago that evaluated the reinforcing properties of many

of these same drugs (Corwin et al. 1987; Woolverton et al., 1986; Johanson

and Schuster 1977). Table 1 lists the results across drugs and doses and

shows that amphetamine, benzphetamine, diethylpropion, and

phenmetrazine were preferred over placebo. Where more than one dose

was evaluated, there did not appear to be any dose-dependent effect. In

contrast, caffeine, fenfluramine and phenylpropanolamine (PPA) were

not preferred whereas mazindol was clearly avoided. In general, these

results paralleled those obtained with rhesus monkeys with the noteworthy

exception that mazindol maintains responding in rhesus monkeys (Wilson

and Schuster 1976; Corwin et al., 1987) but appeared to have aversive

properties in humans in the present study. It remains to be determined

whether this difference is due to route of administration (the monkey

studies used an intravenous route whereas drug was administered orally

in the human studies), species, or other procedural differences. The

results obtained in the discriminative stimulus studies (seebelow) indicate

that it is not likely that route of administration can account for the

discrepancy.

In addition to the differences in preference, there were also differences

in subjective effects across drugs. Although a variety of measures of

subjective effects have been used, particularly in the most recent studies

(e.g., Chait et., 1987), many of these (e.g., ARCI, VAS) have not been

used consistently across all studies. Therefore, the comparison will be

restricted to the POMS. A liking measure, which was obtained using a

100 mm visual analog scale, is also reported for those drugs for which it

was used because of the face validity of this question (see Fischman, this

volume). Finally, because different participants were used in each study,

an attempt to make quantitative comparisons does not appear justified so

178
Table 1: Preference for psychomotor stimulants in humans

Drug (mg)

Percent

Choice Reference

5 mg Amphetamine

10 mg Amphetamine

25 mg Benzphetamine

50 mg Benzphetamine

25 mg Diethylpropion

25 mg Phenmetrazine

50 mg Phenmetrazine

100 mg Caffeine

300 mg Caffeine

20 mg Fenfluramine

12mg PPA

25 mg PPA

50mg PPA

75 mg PPA

0.5 mg Mazindol

1 mg Mazindol

2 mg Mazindol

81 Johanson & Uhlenhuth 1980a

78 Johanson et al., 1983

65 Chait et al., 1987

71 Chait et al., 1987

63 Johanson & Uhlenhuth 1978

63 Chait et al., 1987

63 Chait et al., 1987

43 Stem et al., 1989

39 Stem et al., 1989

50 Johanson & Uhlenhuth 1982

43 Chait et al., 1987

38 Chait et al., 1987

42 Chait et al., 1987

39 Chait et al., 1988

13 Chait et al., 1987

13 Chait et al., 1987

12 Chait et al., 1987

that only qualitative results (i.e., whether a drug produced a significant

drug by hour interaction) will be reported.

As shown in table 2, the drugs that were preferred over placebo had

similar subjective effects. In particular, increases in Arousal and higher

liking scores characterized the drugs that were preferred, whereas the

remaining drugs either showed no significant subjective effects (e.g.,

fenfluramine) or only produced increases in POMS Anxiety. However,

increases in Anxiety were also seen with amphetamine and phenmetrazine.

The correspondence between choice and subjective effects has also been

demonstrated by comparing the subjective effects produced by

amphetamine in participants who consistently chose amphetamine

179
Table 2: Subjective effects of psychomotor stimulants2,3

POMS

AMP BENZ DEP4

PMT CAF FFL PPA MAZ

Anxiety + + + + +

Vigor + + +

Fatigue — — —

Friendliness + +

Elation +

Arousal + + + +

Positive Mood +

Liking5 Yes Yes NE Yes NE No No No

(choosers) with those that consistently chose placebo (non-choosers).

This type of comparison was originally made using the results from the

initial study (Johanson and Uhlenhuth 1980a). Perhaps due to the fact

that none of the 31 participants in that study chose placebo more than

three times out of five, no significant differences in subjective effects

were reported between 2-3 time choosers, 4 time choosers and 5 time

choosers. However, a follow-up study that included additional participants

(N=45, Uhlenhuth et al, 1981) reported sufficiently intriguing predrug

differences in POMS scores that a further analysis, using a different

group of participants, was conducted. The explicit purpose of this analysis

was to determine whether there were preexisting differences between

individuals that predicted preference (de Wit et al., 1986a). In that context,

2

Table entries are based upon whether a significant drug by hour interaction was

obtained on the ANOVA. Only scales for which one of the drugs produced a

significant effect are included. A "+" indicates that drug produced an increase relative

to placebo and "-" indicates a decrease. Results are reported for the highest dose or

overall drug for those drugs reported in Chait et al., 1987. See table 1 for dose(s) and

reference.

3

The profile of subjective effects has differed across replications with the same

drug, largely due to differences in sample size. None of these differences have been

qualitative but are largely differences in whether a trend reaches significance. In

addition, Schuster and Johanson (1988) have reported a similar comparison across

drugs, but it should be noted that their profile was obtained from drug discrimination

studies. Even so, the general results are remarkably similar to those obtained in drug

self-administration studies reported in this table.

4Analyses were only done using the Arousal scale (Johanson and Uhlenhuth 1978).

5A “yes” indicates that liking score for drug exceeded liking score for placebo, “no”

indicates similar levels of liking or a placebo score greater than drug, and “NE”

indicates that drug liking was not evaluated. See footnote2 for further details.

180
the results will be discussed in later sections of this paper, but because this

study also did extensive analyses that examined the relationship between

preference and subjective effects, this study is also important in

demonstrating the close correspondence between these two measures.

The participants (N=31) for the analysis were selected from a larger

group of 52 on the basis of their drug choices in an experiment that tested

preference between 5 mg dl-amphetamine and placebo (de Wit et al.,

1985; 1986b). In general, the procedure used in this study was similar to

the original study except that the ARCI which is described by Jasinski

and Henningfield (this volume) was also used to evaluate subjective

effects. As in the original study, there was a significant preference (63

percent) for amphetamine which is impressive given its dose (racemic

amphetamine is less potent than d-amphetamine). Relative to the previous

study (i.e., Johansonand Uhlenhuth 1980a) a greater numberof participants

chose placebo on all five choice opportunities, perhaps due to the use of

the racemic mixture. Therefore, it was possible to form two contrasting

groups for comparison by selecting participants from the extremes of the

distribution. The 20 participants who chose amphetamine on each of five

sessions were designated choosers, whereas the 11 who chose placebo on

all five sessions were designated non-choosers. The subjective responses

to dl-amphetamine differed markedly between the two groups, the drug

having in some cases opposite effects on mood. Relative to placebo

scores, amphetamine increased Depression and Anxiety scores in the

non-choosers whereas it decreased Depression scores and had no effect

on Anxiety scores in the chooser group (figure 3). In contrast, the drug

increased scores on Friendliness, Elation, Positive Mood, MBG, BG (not

shown) and A (not shown) scales in the choosers, while it had no effect

or decreased scores on these scales in the non-choosers (figure 4).

Therefore, it appears that there is a logical relationship between choice

and subjective effects. Amphetamine produced positive effects in the

choosers with no aversive-like effects whereas in non-choosers, the only

significant changes in mood are best described as negative.

In summary, psychomotor stimulants differ both in terms of preference

and subjective effects and as just demonstrated, there is a striking

correspondence between these two measures, at least under the conditions

reported. As a whole, the results correspond well with those obtained

using animal drug self-administration techniques and similar predictions

would be made from both types of approaches in terms of dependence

potential. While these similarities indicate the usefulness of the choice

procedure in humans for assessing dependence potential, validity

estimations are limited by the difficulty of comparing these results to

sound epidemiological evidence. This problem is discussed by Senay

(this volume) and Anthony and Trinkoff (this volume).

181
Figure 3: Subjective effects of 5 mg

dl-amphetamine in non-choosers

(AN; left panels) and choosers (AC;

right panels) on two scales (Depression and Anxiety) of the POMS. The

dashed lines refer to mean scores on

placebo sampling sessions, solid

lines refer to mean scores on amphetamine sampling sessions. Asterisks refer to points at which drug

and placebo scores differed significantly.

Figure 4: Subjective

effects of 5 mg dl-amphetamine in non-choosers (AN; left panels) and

choosers (AC; right

panels) on the MBG

scale of the ARCI and

three scales (Positive

Mood. Friendliness, and

Elation) of the POMS.

The dashed lines refer to

mean scores on placebo

sampling sessions, solid

lines refer to mean scores

on amphetamine sampling sessions. Asterisks

refer to points at which

drug and placebo scores

differed significantly.

182
DISCRIMINATIVE STIMULUS PROPERTIES OF

PSYCHOMOTOR STIMULANTS

Although the present review focuses on the use of choice procedures for

assessing the reinforcing properties of drugs in humans, Bigelow and

Preston (this volume) have made a clear case for the relevance of drug

discrimination methods in assessments of dependence potential. Our

group at the University of Chicago has also conducted a series of drug

discrimination studies using the same psychomotor stimulants evaluated

in the choice procedure and the results obtained in these studies contribute

to the overall assessment of the dependence potential of this group of

compounds (Chait and Johanson 1989; Chait et al., 1984, 1985, 1986a,

1986b).

The procedure used to assess the discriminative stimulus (DS) properties

of psychomotor stimulants in humans was designed to parallel typical

animal drug discrimination studies, with the substitution of a verbal

response for the usual lever-press or key-peck response. In addition, the

subjective effects of the drugs were concurrently measured, as described

for the choice studies, to be able to also evaluate the correspondence

between these two measures (see Schuster and Johanson 1988 for a

discussion of this issue).

The participants were recruited in the same manner and with the same

characteristics as participants in the self-administration studies. In all of

the studies (although there were minor variations in protocol), participants

were told that their job was to learn to discriminate between two different

capsules, “Drug A” and “Drug B,” based on the effects produced by each.

One of these capsules contained 10 mg d-amphetamine and the other

contained placebo. Participants reported to the laboratory in the morning

three days per week throughout a 7- to 9-week study. Upon arrival, they

filled out subjective effects questionnaires and then ingested a capsule.

As in the choice studies, they were then free to leave for the day, taking

additional questionnaires with them to fill out 1, 3, and 6 hr later. In the

first four sessions of the study (sampling phase) participants were allowed

to sample Drug A and Drug B, which were identified as such prior to

ingestion. The next seven sessions (training/assessment phase) participants

were given either Drug A or Drug B, i.e., amphetamine or placebo, in

random order, but were not told at the time of ingestion which drug they

were receiving. Six hours later they were instructed to telephone the

experimenter and report which drug (A or B) they believed that they had

received. If a participant’s report was correct, he/she received a monetary

bonus the next time they came to the laboratory. In order to progress to

183
the third, test phase, participants were required to correctly identify

amphetamine and placebo on six of the seven training days, or on five

consecutive training days.

In the four studies that have been conducted, 53 of the 100 participants

learned the discrimination as defined by the criteria above. Post-hoc

analyses revealed that all participants experienced subjective effects typical

of those for stimulant drugs although there was a tendency for the

discriminators to be more sensitive (Chait et al., 1989b). The 53 participants

that learned the discrimination entered the test phase. The test phase

consisted of test days interspersed with approximately the same number

of additional training days. Test days were exactly the same as training

days except that participants were not informed when they telephoned

whether or not their drug identification was correct. On test days both

responses were equally reinforced with money and participants received

no feedback as to which drug they had received. Participants did not

know when test days were scheduled and did not find out it was a test day

until after they had telephoned and reported their identification. During

each of the four studies, different drugs were evaluated during the test

phase as follows:

Study 1 (N=17): Placebo, 10 mg diazepam, 2, 5, and 10 mg

d-amphetamine.

Study 2 (N=27): Placebo, 10 mg d-amphetamine, 25 and 50 mg

phenmetrazine, and 20 and 40 mg fenfluramine.

Study 3 (N=20): Placebo, 10 mg d-amphetamine, 25 and 75 mg PPA

and 0.5 and 2 mazindol mg

Study 4 (N=36): Placebo, 10 mg d-amphetamine, 100 and 300 mg

caffeine, and 25 and 50 mg benzphetamine.

In Study 1, seven participants learned the discrimination between placebo

and 10 mg d-amphetamine. When tested with these training drugs, they

responded correctly. Participants identified 2 mg amphetamine as placebo

and at the 5 mg dose, the capsule was identified as placebo 50 percent of

the time across participants. Diazepam was identified as placebo by five

of the seven participants and produced a profile of subjective effects

typical for a benzodiazepine. In Study 2, 14 participants learned the

discrimination and identifiedphenmetrazine at both doses as amphetamine.

The low dose of fenfluramine was identified as placebo whereas the high

dose produced intermediate levels of amphetamine-appropriate

184
responding, reflecting both within- and between-subject variability. In

Study 3, 12 participants learned the discrimination and identified the high

doses of both mazindol and PPA as drug. The lower doses were identified

as placeboor the identifications werevariable. In Study 4, 20 participants

learned the discrimination and did not reliably identify either caffeine or

benzphetamine as amphetamine. Figure 5 summarizes these results for

the higher dose of each drug tested.

Figure 5: The percent of

participants who identified different psychomotor stimulant drugs

(BNZ=benzphetamine;

FFL=fenfluramine;

CAF=caffeine; MAZ=

mazindol; PPA=phenylpropanolamine; PMT=

phenmetrazine; AMP=

amphetamine) and diazepam (DZP) as amphetamine-like in the

drug discrimination experiments described in

the text. The dose of the

drug in mgs is also indicated. This dose was the

highest dose tested.

The profile of subjective effects of drugs (i.e., fenfluramine anddiazepam)

that did not substitute for amphetamine differed from amphetamine. On

the other hand, phenmetrazine and the high dose of PPA which substituted

for amphetamine produced subjective effects that were similar to

amphetamine. However mazindol, despite the fact that the high dose

substituted for amphetamine, as a DS produced subjective effects that

differed somewhat from those of amphetamine. More specifically,

mazindol’s subjective effects were restricted to increases in anxiety, an

effect also produced by amphetamine (Schuster and Johanson 1988).

Since these anxiety-increasing effects (as well as the more positive effects

such as increased Arousal) were also seen withphenmetrazine, it is possible

that they were the basis of the discrimination.

In summary, the results of the four studies described above indicate that

it is possible to train humans to discriminate 10 mg d-amphetamine from

placebo using a procedure that 1) does not require laboratory space, 2)

185
limits exposure to drugs by using low doses and a relatively short

experimental protocol, and 3) in many ways is comparable to procedures

utilized in animal studies. On the other hand, only half of the participants

learned the discrimination which may indicate that additional

methodological studies would be desirable to improve training.

Nevertheless, in those participants who learned the discrimination, the

results were similar to those seen in animals. That is, phenmetrazine,

mazindol and PPA, but not fenfluramine or benzphetamine, have been

shown to substitute for amphetamine as a DS in rhesus monkeys (de la

Garza and Johanson 1987). Furthermore, there is some indication that the

discrimination is responsive to dose and is also pharmacologically specific

since diazepam was identified as placebo. Finally, the subjective effects

produced by the drugs that shared DS properties with amphetamine were

similar but not identical.

Interestingly and relevant to the present context of utilizing drug

discrimination procedures in the assessment of dependence potential, the

results obtained in the self-administration studies and the drug

discrimination studies had some striking differences. Amphetamine and

phenmetrazine both were reinforcers and were similar as DS. On the

other hand, mazindol and PPA were not self-administered by humans yet

were discriminated as amphetamine. Their subjectiveeffects (see Schuster

and Johanson 1988 as well as table 2) were similar but certainly not

identical. Finally, benzphetamine was preferred in the choice procedure

but was not identified as amphetamine-like despite similar subjective

effects. These contrasts are intriguing and indicate the need for additional

studies in this area.

REINFORCING PROPERTIES OF OTHER

BENZODIAZEPINES

The failure to find that diazepam was preferred over placebo was surprising

because this drug had been shown in previous human studies using sedative

abusers to maintain self-administration behavior (see Roache and Griffiths,

this volume). However, animal studies have clearly demonstrated that

benzodiazepines are not robust reinforcers (Ator and Griffiths 1987).

These findings stimulated a series of studies todetermine whether various

pharmacological or environmental variables could modify the reinforcing

properties of diazepam. One group of studies was designed to assess the

reinforcing properties of benzodiazepines with different profiles of action

186
(de Wit et al., 1984a,b)6

. This is an example of altering a pharmacological

variable but can also be viewed as a systematic replication of the original

finding.

Using the same procedure, two additional benzodiazepines, flurazepam

and lorazepam, were tested. Flurazepam was selected because studies in

rhesus monkeys indicated that this drug had more robust reinforcing

properties, at least when tested in monkeys trained to self-administer

pentobarbital (Johanson 1987). Relative to diazepam, lorazepam has a

plasma half-life appreciably shorter (Greenblatt et al., 1976) which may

augment its reinforcing properties (Griffiths et al, 1981). Despite these

differences, neither flurazepam (15 and 30 mg) nor lorazepam (0.5, 1, and

2 mg) was preferred over placebo and in fact, as dose increased, placebo

choice increased. Like diazepam, the higher dose of flurazepam increased

Fatigue and decreased Vigor and Arousal scores on the POMS (de Wit

et al., 1984a). These effects peaked slightly later than those of diazepam.

Similar subjective effects were found for lorazepam but it was striking

that these effects increased over the 6-hr measurement period which does

not support the idea of a shorter duration of action (de Wit et., 1984b).

Taken as a whole, the studies with diazepam, flurazepam, and lorazepam

indicate that under the conditions of these experiments, benzodiazepines

have minimal reinforcing properties in normal human volunteers.

INDIVIDUAL DIFFERENCES IN REINFORCING

PROPERTIES OF DIAZEPAM

Although the extent of abuse of the benzodiazepines is not known with

certainty, there are numerous case histories of individuals who use

diazepamrecreationally. Furthermore, diazepam ranks high in emergency

room mentions reported by the DAWN system, which presumably

indicates that it is abused. Our failure to demonstrate reinforcing properties

in normal volunteers and the contrasting findings in sedative abusers

(Roache and Griffiths, this volume) indicated the need for additional

studies that would attempt to isolate variables that increase the reinforcing

properties of this class of drugs. One type of variable may be the behavioral

and/or pharmacological history of an individual. For instance, Barrett

(1987) has shown that the response of animals to pentobarbital canchange

dramatically following a history of morphine administration. Since history

6

 Additional studies have also been done with other sedative drugs such as alcohol.

However, because the use of these drugs necessitated a change in procedure, the

results will be reported in a subsequent section describing a series of studies

conducted within the confines of the laboratory.

187
is difficult to manipulate with human participants, we posed the question

in terms of whether there are preexisting individual differences (e.g.,

personality traits, history of barbiturate abuse) that place certain individuals

“at-risk” for finding benzodiazepines reinforcing. In identifying at-risk

factors, it should be noted that strong preference for a drug in an

experimental context is not an indicator that a specific research participant

(or someone with similar characteristics) will abuse that drug because

many environmental factors can inhibit such drug use. But relating

individual differences to different reinforcing effects of drugs under

laboratory conditions may shed light on factors involved in a high risk for

drug abuse. The study of the relationship between individual differences

and reinforcing properties demonstrates one of the advantages of using

non-drug abusing populations of participants. In addict populations who

have already indicated by their previous drug abuse history that a drug is

a reinforcer, it would be unlikely that individual differences in reinforcing

properties would emerge in an experimental context.

In addition to using post-hoc analyses for determining whether certain

characteristics are correlated with differences in reinforcing properties,

epidemiological studies may also provide clues concerning types of

individuals who appear at risk for abusing benzodiazepines. Thus, the

strategy in our studies was to determine whether the reinforcing properties

of diazepam were different in participants selected on the basis of certain

traits. In some sense studies using addict populations employ a similar

strategy, i.e., participants are preselected for their preference for the test

drugs. But determining that previous abuse of diazepam predicts that it

has reinforcing properties is circular, although such studies may be

extremely beneficial in determining whether new anxiolytics will substitute

for diazepam and thus have a similar dependence potential at least in

those already abusing sedatives.

Finally, it is important to use non-drug abusing populations for assessing

the relationship between subjective response to drugs and their reinforcing

properties. The subjective responses of previous heavy drug users are

undoubtedly altered by this previous history so their possible causal

relationship to drug-using behavior is hard to assess. Participants without

this history can show a range of response to the test drug and these

individual differences in subjective response may predict differences in

reinforcing properties and provide clues to risk factors.

188
Choosers vs Non-Choosers

In a previous section, individual differences between choosers and nonchoosers of amphetamine were described using a pool of 52 participants

(de Wit et al., 1986a). These same participants were also tested in a

preference experiment comparing 10 mg diazepam to placebo and, as in

the amphetamine experiment, variability wasobserved among participants

in terms of diazepam choice. The 27 participants who chose placebo on

all five sessions were designated non-choosers. Because the number of

5-time choosers was small (N=7), thediazepam-choosing group included

both 4- and 5-time choosers (N= 10). These two groups differed in their

response to diazepam. Diazepam decreased Arousal and increased Fatigue

in the non-choosers but produced no changes in these scales in the choosers.

Furthermore, in the absence of diazepam (i.e., placebo sessions), nonchoosers scored higher on Vigor, Friendliness and Elation on the POMS.

When diazepam was administered, these differences disappeared, i.e.,

the drug decreased Vigor, Friendliness and Elation in the non-choosers

and had no effect in the choosers. The relative insensitivity of the chooser

group to the effects of diazepam was also reflected in their inability to

correctly identify the drug as a tranquilizer. It appears that the choosers

were simply unable to discriminate diazepam and their consistent choice

of the capsule containing 10 mg diazepam, in the absence of discriminable

differences, had no pharmacological basis. In the context of searching for

characteristics that place individuals at risk, the low scores of choosers

on the Vigor, Friendliness and Elation scales in the absence of drug were

intriguing but not particularly helpful for purposes of prediction.

Furthermore, when demographic characteristics and personality test scores

were compared, there were no differences between choosers and nonchoosers.

Populations with Pre-Existing Anxiety

The idea that excessive drug use is an attempt to self-medicate is not new,

but has received relatively little experimental support (see Schuster&.,

1979). In fact, experimental studies in both humans and animals have

supported the view that most drugs of abuse produce direct positive

reinforcing effects that are unrelated to psychopathology. While selfmedication may not play a role in the misuse of drugs such as stimulants

with unequivocal positive reinforcing properties, the misuse of drugs like

diazepam that appear to have minimal reinforcing properties may depend

on other factors such as therapeutic efficacy. It is conceivable, therefore,

that diazepam might have reinforcing properties in participants with

increased levels of anxiety. Furthermore, if this is the case, these individuals

are at special risk because they are more likely to be prescribed diazepam.

189
To test the relationship between anxiety reduction and reinforcing

properties, four groups of volunteers were recruited differing in levels of

anxiety (de Wit et al., 1986b; McCracken et al., in press). Anxiety was

assessed using the Taylor Manifest Anxiety Scale (TMAS), the Spielberger

Trait Anxiety Inventory (STAI), the Hopkins Symptom Checklist (HSCL),

and a psychiatric interview. The control group (CTRL) consisted of

healthy adults with TMAS, STAI, and HSCL anxiety scores within a

normal range. A second group (ANX) had high scores on the TMAS and

STAI but did not meet DSM-III criteria for any anxiety disorder. The

third group (ANX-DSM) did meet DSM-III criteria for Generalized

Anxiety Disorder. A fourth group (ANX-Rx) was recruited at a later time

after it was determined that this third group, despite their diagnosable

anxiety did not wish to receive treatment. The ANX-Rx group was

identical to the ANX-DSM group except that they answered a recruitment

advertisement that asked for participants who were anxious and wished

to receive treatment for their disorder. Except for level of anxiety, the

four groups did not differ on any other measurable dimension.

Table 3 summarizes the sex, age, and anxiety questionnaire scores for the

four groups. The HSCL anxiety score was highest in the ANX-Rx and

ANX-DSM groups, intermediate in the ANX group, and lowest in the

CTRL group. The STAI and TMAS scores, which were used as selection

criteria for the ANX but not the other anxiety groups, differentiated all of

these groups from the CTRL group and tended to increase across groups

(see table 3). In addition, on the Anxiety scale of the POMS, all anxious

groups had higher scores under non-drug conditions. The concordance

of these measures, particularly those that were not used as criteria for

recruitment, indicate the reliability of the anxiety classification of the

participants.

Table 3: Demographic and anxiety ratings7

CTRL ANX ANX-DSM ANX-Rx8

N 12 11 13 14

Mean Age 26 27 27 32

Sex (M/F) 6/6 4/7 4/9 6/8

Mean STAI 29.9 44.7 49.1 53.9

Mean TMAS 9.2 22.8 27.1

Mean HSCL 0.15 0.58 0.95 1.02

7

 Results are shown for 4 groups: CTRL=control group; ANX=group with higher

ratings on the STAI and HSCL but who did not meet criteria for DSM-III Generalized

Anxiety Disorder; ANX-DSM=group who did meet criteria for DSM-III Generalized

Anxiety Disorder; and ANX-Rx=group that also met criteria for DSM-III Generalized

Anxiety Disorder but who also answered advertisement that indicated that they

wished treatment.

8

 TMAS was not administered.

190
As shown in figure 6, none of the groups of anxious individuals preferred

diazepam to any significantly greater extent than found in Johanson and

Uhlenhuth (1980b). Despite predrug differences in anxiety scores between

the CTRL and the anxious groups, anxiety scores of all groups decreased

following the administration of 10 mg diazepam. Thus, diazepam did

exert a measurable anxiolytic effect, but this did not affect preference for

the drug. Changes in the other subjective effects also showed no differences

related to group and were similar to those reported in the previous

experiment (Johanson and Uhlenhuth 1980b). Clearly, these results do

not support the hypothesis that highly anxious individuals are at-risk for

abusing benzodiazepines because of an increase in reinforcing properties

as a function of reduced anxiety. This is not to say, however, that these

individuals are not at-risk becauseof theirincreasedprobability of chronic

exposure to anxiolytics. That is, afterrepeated administration, itispossible

that reinforcing properties will emerge, perhaps due to the development

of tolerance to sedative properties, the development of physical

dependence, or increased sensitivity to effects that are not observed

following acute administration. Recruiting participants with a long history

of treatment with benzodiazepines might help to determine whether

long-term changes occur.

Figure 6: Choice results for different populations of participants differing in preexisting

levels of anxiety in a comparison between 10 mg diazepam and placebo. The ordinate

is the percentage of participants who chose diazepam and the abscissa indicates the

different populations (CTRL=control group; ANX=group with higher ratings on the

STAI and HSCL but who did not meet criteria for DSM-III Generalized Anxiety

Disorder; ANX-DSM=group who did meet criteria for DSM-III Generalized Anxiety

Disorder; and ANX-Rx=group that also met criteria for DSM-III Generalized Anxiety

Disorder but who also answered advertisement that indicated that they wished

treatment.)

191
Older Populations

One population of individuals that has a greater incidence of long-term

benzodiazepine use is older people (Mellinger et al., 1984). This may

indicate that the reinforcing properties of benzodiazepines are greater in

these individuals, placing them at-risk for abusing benzodiazepines. In

order to determine whether older people are more likely to find diazepam

reinforcing, we designed a study using participants who were older than

those that had previously been used in our experiments (de Wit et al.,

1985). Participants were recruited who were between 40 and 55. It would

have been desirable to recruit even older participants but the increased

probability of medical complications prohibited this strategy. Except for

the age of the participants, the experimental protocol was identical to that

previously described in all other respects. Individuals participated in

three separate 9-week experiments comparing 5 mg dl-amphetamine and

both 5 and 10 mg diazepam to placebo.

Age did not significantly alter the proportion of participants who chose

either amphetamine or diazepam (5 and 10 mg). As in earlier studies,

amphetamine was chosen overall more often than placebo, 5 mg diazepam

as often as placebo, and 10 mg diazepam significantly less often than

placebo. The participants’ relative drug liking scores were consistent

with their choice behavior. That is, most participants both chose and

liked amphetamine more than placebo, whereas most participants preferred

placebo to diazepam on both liking ratings and the choice measure. Drug

identification was also similar across the two groups. Amphetamine was

labelled as either “stimulant” or “placebo” by most participants, whereas

diazepam was most often correctly labelled as “tranquilizer.” Finally,

although there was some evidence that older people were more sensitive

to the subjective effects of amphetamine, their response to diazepam did

not differ from the control group. At the 10 mg dose of diazepam, Vigor,

Friendliness, Elation, Arousal, Positive Mood, BG, MBG and A scores

were significantly decreased, whereas Fatigue, Confusion, PCAG and

LSD scores were increased. The effects of both 5 and 10 mg were greatest

1 hr after drug ingestion, replicating the previous study.

Concluding Remarks

In summary, the studies designed to determine whether there are

populations that might be at-risk for abusing benzodiazepines found no

evidence that the reinforcing properties of diazepam were greater for

these individuals. Thus, even thoughdiazepam effectively lowered anxiety

192
levels in several groups of anxious volunteers, these participants still

preferred placebo to drug. There was some evidence that a subset of the

group of anxious individuals who were seeking treatment reacted

differently to diazepam but the number of individuals in this subset was

too small for meaningful comparisons (see McCracken et al., in press).

In addition, older people also did not prefer diazepam to placebo and like

younger participants, preferred placebo over 10 mg diazepam. Finally,

a closer examination of those individuals who chose 10 mg diazepam

four to five times only showed that as a group, these participants tended

to be less sensitive to the mood-altering properties of diazepam. Thus,

while it is likely that there are individual characteristics that place some

individuals at-risk for abusing diazepam, the only experimental evidence

as of 1986 was that individuals with a previous history of sedative abuse

self-administered diazepam above placebo levels (Griffiths et al., 1979).

It was our hope that additional research would reveal other types of

predictors more useful than an already established history of abuse.

THE EFFECTS OF ENVIRONMENTAL CONTEXT ON THE

REINFORCING PROPERTIES OF SEDATIVES

In our previous studies, participants reported to the laboratory in the

morning to take their capsule and were then free to conduct their normal

activities outside the laboratory. Although these conditions have the

advantage of being relatively naturalistic, other environmental demands

on the participants during the day may rule against their selection of

sedative drugs. That is, even at the relatively low doses of diazepam used

in these previous studies, their sedative properties may have interfered

with the participants’ ability to work or study during the day, and this

negative effect may have overridden the positive properties of the drug.

In addition, the strategy of allowing participants to leave the laboratory

makes it difficult to evaluate the reinforcing properties of prototypic

sedative drugs of abuse such as alcohol (imagine having your subjects

show up for work with alcohol on their breath) and limits the doses of

sedatives that can be administered. In studies by Griffiths and his

colleagues (Griffiths et al., 1979) that have shown that diazepam is a

positive reinforcer, doses up to 200 mg have been used. Although the

participants in those studies were undoubtedly tolerant to the sedative

effects of benzodiazepines because of previous experience with that class

of drugs, it is possible that reinforcing properties only occur at higher

doses. All of these considerations led to additional studies designed to

minimize the impact of diazepam’s sedative properties on drug choice.

193
The Effects of Time of Day on the Reinforcing Properties of

Diazepam

In order to minimize the possible disruptive effects of diazepam on the

evaluation of its reinforcing properties, alterations were made in the

environmental context of its administration. In the first study (de Wit et

al., 1985), the experimental protocol was identical to the previous

experiments except that participants reported to the laboratory in the late

afternoon so that peak drug effects occurred in the early evening, a time

more consistent with recreational drug use (“cocktail hour”), i.e., when

other demands on the participants’ attention are presumably less.

Participants in this study were tested in three separate experiments

evaluating preference for 5 mg &hetamine, 5 mg diazepam, and 10

mg diazepam, and their results were compared to a control group tested

concurrently which received drug at the usual morning time. Despite this

change, however, preference for diazepam remained low, i.e., as in

previous experiments, placebo was clearly preferred over 10 mg diazepam,

and 5 mg diazepam and placebo were equally chosen. As a whole, the

subjective effects produced by diazepam were similar in both the

experimental and control group. However, there were some differences

in subjective effects in the group tested in the late afternoon. For instance,

not surprisingly, Fatigue scores on the POMS were higher for the afternoon

group regardless of the drug administered. The subjective effects produced

by 5 mg &hetamine were less pronounced and there was also a

tendency for both a slightly lower preference for amphetamine in both the

choice test and the liking ratings, suggesting that the later time of drug

administration attenuated the reinforcing properties of amphetamine.

Some participants even reported that this low dose interfered with their

normal sleeping patterns, an effect that may have contributed to their

decreased preference and liking. Nevertheless, experiencing the effects

of diazepam at this later time did not influence its reinforcing properties.

The Effects of Remaining within the Laboratory on the

Reinforcing Properties of Diazepam

The persistent avoidance of diazepam across experimental conditions

that involved participants not remaining within the laboratory environment

may be attributable to the population that was recruited for these

investigations. Most of the participants in the previous studies were

students and others had busy schedules. Such people may find sedative

effects aversive regardless of the time of day. Even though individuals

who were employed evenings or nights were not accepted into the late

afternoon study, the participants may have planned evening activities

194
requiring concentration, such as studying. The participants in these studies

also did not report recreational sedative use and most particularly were

relatively light alcohol drinkers (see table 4). Thus, they may generally

avoid sedative drugs because of work/study demands. To circumvent

this problem, two additional strategies were used to assess the reinforcing

properties of diazepam: 1) recruit non-drug abusing populations who

have demonstrated that they do not avoid sedative drugs in their normal

day-to-day routine, and 2) arrange the environmental conditions so that

this property of sedative drugs has no significant functional consequence.

The former strategy will be discussed in a later section. The latter strategy

involved having participants remain within a laboratory environment,

paying them for their time, but not allowing them to engage in taskrelated activities. Allowing participants to remain within the laboratory

also allowed the administration of higher doses of diazepam.

In the first study (reported in de Wit et al., 1989a), experimental sessions

were conducted over a 4-hr period in the evening and participants remained

in the laboratory. The testing environment consisted of comfortably

furnished rooms with a couch and upholstered chairs, and a television,

movies, radio, audio tapes, and games were available. Participants could

engage in leisure activities of their choice but they were not allowed to

work or study. There were five experimental sessions, conducted at one

week intervals, and participants were tested in pans. Thefirstfour sessions

were sampling sessions with 20 mg diazepam alternating with placebo.

During the fifth session, participants were given a single choice between

the two distinctively colored capsules. Except for remaining in the testing

Table 4. Average alcohol consumption across studies

#Drinks per

Group N Choice9 Week (SD) Reference

Control 12 25

ANX 11 5

ANX-DSM 13 30

ANX-Rx 13 37

Older 11 38

Afternoon 13 32

Choosers 10 94

Non-Choosers 27 0

Laboratory 11 27

5.6 (4.3)

7.1 (6.7)

4.1 (2.9)

4.7 (5.6)

3.0 (2.7)

4.9 (4.2)

3.9 (3.3)

4.7 (5.6)

6.4 (8.5)

de Wit et al., 1986b

de Wit et al., 1986b

de Wit et al., 1986b

McCracken et al., in press

de Wit et al., 1985

de Wit et al., 1985

de Wit et al., 1986a

de Wit et al. 1986a

Unpublished10

9

 Percent choice for 10 mg diazepam over placebo.

10 Portions of this study are reported in de Wit et al., 1989a

195
rooms, the protocol was similar to the previous studies in other respects.

For instance, participants reported to the laboratory, filled out subjective

effects questionnaires, and ingested a capsule. During the course of the

evening, additional questionnaires were filled out at regular intervals.

Despite these changes in the experimental conditions, preference for

diazepamremained low. Eight of the 11 participants (73 percent) preferred

the placebo capsule to the capsule containing 20 mg diazepam and the

subjective effects produced by diazepam were typical of sedative-like

drugs.

The Effects of Remaining within the Laboratory on the

Reinforcing Properties of Diazepam: Multiple Drug

Administrations

One of the problems of conducting the experiments within the laboratory

setting relative to the studies where participants were free to leave was

that it required more time to complete studies with similar numbers of

participants and the time demands per participant increased. In fact, one

of the reasons for using only a single choice session in the previous

diazepam choice study was to reduce the individual time demand factor.

However, based upon an analyses of previous choice data obtained with

five choice sessions, it was determined that initial choice did not reliably

predict overall choice but that the first threechoice sessions did. Therefore,

it was necessary to increase the number of sessions to seven (four sampling

and three choice), lengthening the experiment even more. All of these

changes made it difficult to test a wide range of doses, i.e., conduct

multiple experiments with each participant. In order to increase the

efficiency of the experimental protocol, the choice procedure was altered

to allow participants to sample a wider range of doses (de Wit et al.,

1988a). In most respects, the protocol was similar to the laboratory study

just described except for two additional choice sessions. However, during

sampling, the total dose of 20 mg diazepam was administered in five

divided doses (4 mg each) separated by 30 min intervals. This cumulative

dosing procedure allowed participants to experience the effects of low as

well as higher doses of the drug. On choice sessions, participants first

indicated which drug they wished to take on that session, and they were

required to ingest one dose at that time. For the remainder of the session,

they were given options every 30 mins to take up to six additional doses

of the same drug (a total of 28 mg). Thus there were two measures of

preference: 1) the number of sessions on which participants chose diazepam

over placebo, and 2) the number of doses of diazepam they ingested

within a session. A further change in procedure was that the four

participants in each group were acquainted prior to the study and the drug

administered during sampling was the same for all of them.

196
This change in procedure had a remarkable effect upon diazepam choice.

Overall, diazepam was chosen on 67 percent of the sessions. Eleven (61

percent) of the 18 participants chose diazepamon all three choice sessions

while five (28 percent) exclusively chose placebo (see figure 7). On

sessions when they chose diazepam, participants ingested an average

dose of 15.6 mg (3.9 capsules). When they chose placebo, participants

took on average only 1.6 capsules. Individuals who took diazepam on all

three sessions also took more doses (16.4 mg) of the drug within sessions

than the 1(4 mg) or 2 (10 mg) time chooser. Further analyses were done

after dividing the participants into two groups based upon the amount of

drug (i.e., mg’s) they ingested during choice sessions (see figure 7). The

low dose choice group chose diazepam over placebo on one out of three

sessions, taking an average dose per choice session of 4.9 mg, or 1.2

capsules, whereas the high dose choice group chose diazepam on all three

choice sessions and ingested an average dose of 18.8 mg per session, or

4.7 capsules. The low dose choice group also chose about as many

“doses” of placebo as diazepam. Using a measure of psychomotor

performance, we showed that diazepam decreased performance but there

were no differences between the two groups in this effect. Despite the

increased choice of diazepam as well as the emergence of a group of

participants who consistently chose diazepam, the subjective effects of

20 mg diazeparn given in divided doses were typical for sedatives, i.e.,

decreases in Vigor, Arousal, Positive Mood and Elation, and increases in

Fatigue and Confusion of the POMS, and these effects were the same for

both the low and high dose choice groups. There were no indications of

any subjective effects even in the group of consistent choosers that could

be considered positive (this finding should be compared to the results

with alcohol reported below). This is a striking example of a divergence

between preference and measures of subjective effects and is a warning

that both of these measures are necessary for a complete assessment of

a drug’s effects.

Figure 7: The number of

participants who chose

diazepam on 0 to 3 of the

choice sessions in the

multiple dose experiment.

The shaded area indicates

the participants in the high

dose choice group. The

remaining participants

(open bars) were in the low

dose choice group.

197
At the present time, it is not clear why diazepam choice increased

dramatically. As just discussed, the increased preference does not seem

to be related to altered subjective effects. A major difference between the

present study and others was the use of the divided cumulative dose

regimen. This allowed participants to experience a wider range of doses

during the sampling sessions and regulate their dose during the choice

sessions. It is interesting to note that even in the participants who chose

diazepam on every session, their dose preference was below the 20 mg

experienced during sampling. The use of the flexible choice paradigm

may have allowed participants to select a dose (approximately 16 to 18

mg) that was maximally reinforcing. However, both 10 and 20 mg

diazepam have been tested in previous experiments and it is difficult to

believe that the failure to test doses of 16 to 18 mg contributed to the

failure to demonstrate reinforcing properties in those previous studies.

On the other hand, having control over time of dose administration may

be an important factor, although additional studies are clearly needed to

evaluate this possibility. In addition, the present study also differed in

two other respects unrelated to the dosing regimen. First, the participants

were tested in groups of four who were acquainted prior to the experiment.

This strategy was used to increase participation as well as create a more

social and relaxed atmosphere than would have existed if strangers were

tested together, as in the previous laboratory study. In addition, all

individuals within a group of four received drug or placebo on the same

sampling session. It is known that drug use is influenced by social variables

and it would be interesting to vary these social variables in future studies.

THE REINFORCING PROPERTIES OF ALCOHOL

In addition to diazepam, we have also tested the reinforcing properties of

alcohol. These studies necessitated the use of a laboratory setting because

of our unwillingness to have participants continue to engage in their

normal activities under the detectable influence of alcohol. We were

interested in evaluating the reinforcing properties of alcohol because this

drug is a prototypic sedative drug of abuse but also because it is known

that individuals differ in their subjective response to alcohol. This study,

therefore, sought not only to determine the reinforcing properties of this

drug in comparison to diazepam but also to determine the relationship

between alcohol self-administration and mood effects in light to moderate

social drinkers who did not have a history of heavy alcohol consumption.

Individuals with a history of alcoholism or alcohol-related problems were

not accepted because of the possibility of an altered response. Sessions

198
were conducted three evenings per week in the comfortable setting

previously described and efforts were made to minimize any possible

disruptive effects that might be produced by alcohol by only allowing the

participants to engage in leisure activities. As in the diazepam experiment,

groups of three to four individuals participated concurrently, with a total

of 29 participants. However, these participants were not acquainted prior

to the study. The dose of

alcohol was 0.5 g/kg and half

of the participants in each

group received drug and half

placebo during the four

sampling sessions.

Overall, alcohol was only

preferred on 50 percent of the

choice sessions and there were

marked individual differences

in preference. That is, as

shown in figure 8, one subset

of participants never chose the

alcohol-containing drink,

others chose it once or twice,

and another subset chose

alcohol on all three sessions.

These subsets also differed in

their subjective response to

alcohol as measured by the

POMS. Comparing across the

two extreme groups (consistent choosers and nonchoosers) showed that alcohol

increased Elation, Vigor,

Arousal and Positive Mood

scores, and decreased Fatigue

in the choosers whereas in the

non-choosers alcohol decreased Elation, Vigor and

Arousal and increased

Confusion scores. Interestingly, on a test of psychomotor

performance, alcohol decreased performance similarly

regardless of preference. In

Figure 8: The percentage of participants that

chose alcohol on 0 to 3 of the choice sessions in

both the single dose procedure (top panel) and

the multiple dose procedure (bottom panel).

The stippled area indicates consistent 3-time

choosers in the single dose experiment and

high dose choosers in the multiple dose

experiment. The open bars indicate consistent

placebo choosers in the single dose experiment

and low dose choosers in the multiple dose

experiment.. The solid bars indicate inconsistent

choosers in the single dose experiment.

199
general, those participants who always chose the alcohol-containing

beverage were more likely toconsume drugs recreationally. For instance,

those participants consumed an average of 14.1 alcohol drinks per week

whereas the remaining participants consumed less than 8 per week.

The second study with alcohol (de Wit et al., 1989b) used the multiple

dose procedure previously described for diazepam. As in the previous

study, one of the purposes of this study was to examine individual

differences, i.e., whether there was any preexisting characteristic or

difference in response to the ingestion of alcohol that could be related to

choice. We believed that the multiple dose procedure was especially

relevant for studies with alcohol since this drug is known to have biphasic

effects dependent on dose and is typically used recreationally in divided

doses. Therefore, by using the cumulative dosing procedure, participants

would be exposed to both low and high doses. It was expected that if

sedative properties produced by doses that were too high for a particular

individual had mitigated against choosing alcohol in the previous study,

in the multiple dose procedure these types of individuals would choose

alcohol, thereby increasing overall choice, but they would then select

fewer additional doses of the alcohol to consume during the remainder of

the choice session. Furthermore, the procedure permitted participants to

consume the drug in a naturalistic manner.

The protocol was similar to the diazepammultiple dose experiment except

that the interval between alcohol doses was decreased to 15 min. Five

doses of 0.1 g/kg were available during two sampling sessions and placebo

was available during the other two sampling sessions. As in the diazepam

experiment, choice involved two separate behaviors. The first was an

initial selection of alcohol or placebo and the second was the selection of

additional doses of the same beverage throughout the remainder of the

session. Participants were permitted to take up to 10 additional doses, or

a total cumulative dose of 1.1 g/kg. All other aspects (e.g., activities

available; testingfourfriendsinagroupintheevening within a comfortable

laboratory setting; number, length, and spacing of the experimental

sessions; administration of subjective effects questionnaires; etc.) of the

protocol were the same as in the diazepam cumulative dose experiment.

Relative to the previous study with alcohol, drug choice increased as was

predicted. Participants chose the alcohol-containing beverage on an

average of 75 percent of the choice sessions (figure 8) and only two

participants chose placebo more than alcohol. Overall. the number of

doses of alcohol ingested during choice sessions after it was selected was

8.3 or 0.83 g/kg, a dose higher than that administered during the sampling

200
sessions. The participants were divided into two groups, low and high

dose choosers (note that these groups are not comparable to the consistent

choosers and non-choosers compared in the previous alcohol study). It

had been predicted that choosers of alcohol, which in the present

experiment includes the majority of participants (only two chose placebo

more than alcohol), could be divided into a group that chose doses of

alcohol equal to or above 0.5 g/kg and a group that chose alcohol but kept

their dose low to avoid the aversive sedative effects. While there were

certainly two distinct groups (the average number of doses per session

taken by the high dose choice group was 9.1 and for the low dose choice

group, it was 5.4), overall alcohol dose in the low dose group was still

above the dose used in the previous study, 0.5 g/kg. In addition, the two

groups did not differ in terms of normal alcohol consumption, with means

of 8.6 drinks per week for the low dose choice group and 8.7 in the high

dose choice group. Thus it might be argued that the participants in the

multiple dose experiment were not differentially sensitive to the effects

of alcohol as were the participants in the singledose experiment. However,

the analyses of the subjective effects produced by the fixed (but

administered in divided doses) dose of 0.5 g/kg during sampling still

showed opposite effects. In the high dose choice group, this dose of

alcohol increased scores on Elation, Vigor, Arousal and Positive Mood,

Table 5. Subjective effects of alcohol

SINGLE DOSE MULTIPLE DOSE

POMSSCALE Chooser Non-Chooser11 High Dose Low Dose12

Elation

Vigor

Arousal

Positive Mood

Fatigue

Confusion

11These results are from the nine participants in the single-dose alcohol study who

consistently chose 0.5 g/kg alcohol (choosers) and the nine participants who consistently

chose placebo on all 3 choice sessions (non-choosers). Total number of participants

in the experiment was 29.

12 These results are from the six participants who selected the highest number of

alcohol doses when alcohol was selected and the six participants who selected the

lowest number out of a total of 12 participants. Five of the former group selected

alcohol on all three choice sessions with one choosing alcohol on two of the sessions.

The other six participants chose alcohol on 3 (N=1). 2 (N=3), 1 (N=1) or 0 (N=1)

choice trials.

201
relative to placebo. In contrast, in the low dose choice group, the drug

decreased scores on Vigor, Arousal and Positive Mood. Alcohol also

decreased Fatigue and Confusion scores in the high dose choice group,

but it increased scores on these scales in the low dose choice group. The

subjective effects of the low dose choice group were strikingly similar to

those found for consistent non-choosers in the previous study (table 5)

despite the amazingly high (66 percent) degree of choice of the low dose

choice group in the present study. It appears, therefore, that across

individuals, there are robust differences in subjective response to alcohol.

These differences are somewhat predictive of choice since participants

who experienced stimulant-like effects from alcohol in both experiments

were 3-time choosers. However, participants who experienced sedative

effects from the fixed dose of 0.5 g/kg varied in their alcohol choice

across the two experiments.

Although it appears that changes in subjective effects cannot account for

the differences in overall choice between the two experiments, there were

many other factors which may have contributed to the higher degree of

preference for alcohol in the multiple dose experiment. For instance, it

is possible that the participants’ ability to regulate their dose during the

choice phase increased alcohol’s reinforcing properties. Furthermore, in

addition to the self-control allowed by the procedure, the use of divided

doses is also more similar to the way that alcohol is ingested in naturalistic

settings. However, this would not seem to be a factor for the diazepam

experiment. Finally, the social conditions (i.e., group of friends all

receiving the same substance during sampling sessions) discussed in the

multiple dose diazepam experiment may have influenced the results.

REINFORCING PROPERTIES OF DIAZEPAM IN

PARTICIPANTS WITH A HIGHER LEVEL OF ALCOHOL

CONSUMPTION OUTSIDE THE LABORATORY

As previously discussed, the sedative properties of diazepam may make

it a less efficacious reinforcer in certain settings. A major aim of the

laboratory studies was to create an environment that minimized the

functional consequences of these sedative effects. A second strategy was

to select participants whose previous drug use history may indicate that

they are either tolerant to these effects or at least they do not uniformly

avoid drugs with sedative effects (e.g., alcohol). This strategy involved

selecting participants who consumed higher levels of alcohol on a regular

basis. We noted that participants in previous experiments were light

drinkers of alcohol (table 4). The results of the initial alcohol experiment

202
showed that alcohol was preferred to a greater extent in participants who

consumed at least 14 drinks per week, although this differential effect

was not noted in the follow-up study. Nevertheless, epidemiological

studies have indicated that individuals with alcohol problems are more

likely to use as well as abuse benzodiazepines (Busto et al., 1983; Woods

et al., 1987) so preference for alcohol might easily be a risk factor. Thus,

it was reasoned that the reinforcing properties of diazepam might be

higher in participants with a higher level of alcohol consumption.

Twelve participants were selected who met at least two of the following

criteria for alcohol consumption: 1) consumes at least seven drinks per

week, 2) consumes at least three drinks on a single occasion at least once

a week, and 3) consumes alcohol on at least four days of the week.

Individuals with any history of drug- or alcohol-related problems were

not accepted. In all respects the experimental protocol was identical to

the multiple dose procedure described above for diazepam and alcohol.

On average, these 12 participants consumed 11.8 drinks/week in

comparison to participants in the original diazepam multiple dose

experiment that consumed 4.8 drinks/week, which is similar to the level

of alcohol consumption for all of the prior experiments (table 4).

In striking contrast to all previous studies with diazepam, all twelve

participants chose diazepam on all three choice sessions (de Wit et al.,

1989a). In addition, they chose an average dose of 25.2 mg per choice

session, or 6.3 out of the 7 available doses which is much higher than the

average for the 3-time choosers in the previous multiple dose diazepam

experiment (16.2 mg). In some respects, the subjective effects of 20 mg

diazepam during the sampling sessions in the present study were similar

to those reported in the multiple dose experiment in light alcohol drinkers

(figure 9). For instance, scores on Confusion and Fatigue increased

whereas scores on Arousal decreased. However, there was also evidence

that more moderate drinkers of alcohol experienced more positive effects

following diazepam. Scores on Vigor, Elation (not shown), Positive

Mood and Friendliness increased relative to placebo. Thus, there was a

strange mixture of apparent positive and negative subjective effects.

Participants reported increases in Fatigue, for instance, whereas they also

reported increases in Vigor. To some extent, this mixture might be

attributable to differences in time course (see figure 9). Nevertheless,

increases in positive mood states such as Elation and Friendliness after

diazepam have not previously been observed in individuals without a

history of drug abuse. Even in the original multiple dose diazepam study,

those participants who preferred diazepam on every occasion did not

show such subjective effects. These findings suggest that even moderate

203
Figure 9: Hourly mean POMS scores for diazepam and placebo sampling sessions

far the experiment with light alcohol drinkers (Study 1: left portion of each panel) and

far the experiment with moderate alcohol drinkers (Study II; right portion of each

panel). Asterisks indicate significant differences between drug placebo means

at each hour for scales on which significant drug-by-hour interactions were obtained.

204
users of alcohol may be more likely to experience euphoric effects from

diazepam. Moreover, both the relatively greater frequency of these

individuals’ choice of drug and the higher doses ingested on choice sessions

indicate that the drug serves as an effective positive reinforcer. Thus both

the positive subjective responses to the drug during the sampling phase

and participants’ drug-taking behavior during the choice phase were

indicative of relatively greater liability for abuse.

Unfortunately, it is impossible to attribute the consistent choice of

diazepam at relatively high doses to any single variable. The participants

in this study were selected because they were heavy andregularconsumers

of alcohol but they also differed on other preexisting variables compared

to those volunteers that participated in previous studies. For instance,

they were slightly older and fewer were students. In addition to drinking

greater amounts of alcohol, their current and lifetime use of other drugs

such as marijuana, tobacco, hallucinogens and opiates was greater,

although by no means were these individuals drug abusers or did they

have any drug-related problem. Finally, their attitude towards

recreationally-used drugs was more positive. It is also difficult to assess

the importance of the procedure. The use of the multiple dose protocol

increased diazepam preference in a previous study with light drinkers.

While it is possible that this variable was a major determinant of the

results in the heavier alcohol consumers, this cannot be determined in the

absence of another experimental group of heavier alcohol consumers

tested under the single dose procedure. Furthermore, in both diazepam

experiments using themultiple dose procedure the influence of the social

variable of testing participants in a group of friends has not been

determined. Despite the difficulty of unequivocally determining the

major variable that increased the reinforcing properties of diazepam,

these results do indicate that some individuals, under certain experimental

conditions, find diazepam reinforcing and report mood effects that could

be interpreted as positive. How the interaction between preexisting

characteristics, such as moderate alcohol consumption, the experimental

context of repeated drug administrations in a highly social environment,

and the acute behavioral and subjective responses to diazepam occurs is

not clear and will require additional studies to delineate the factors that

may place some individuals at risk for abusing benzodiazepines.

205
REFERENCES

Ator, N.A., and Griffiths, R.R. Self-administration of barbiturates and

benzodazepines: A review. Pharmacol Biochem Behav 27:391-398,

1987.

BaIster, R.L., and Schuster, C.R. A comparison of d-amphetamine, lamphetamine and methamphetamine self-administration in rhesus

monkeys. Pharmacol Biochem Behav 1:67-71, 1973.

Barrett, J.E. Nonpharmacological factors determining the behavioral effects of

drugs. In: Meltzer, H.Y., ed. Psychopharmacology. The Third Generation

in Progress.. New York: Raven Press, 1987, pp. 1493-1501.

Bergman, J., and Johanson, C.E. The reinforcing properties of diazepam under

several conditions in the rhesus monkey. Psychopharmacology 86:108-

113, 1985.

Busto, V.; Simpkins, E.M.; Sellers, B; Sisson, R.; and Segal, 0. Objective

determination of benzodiazepine use and abuse in alcoholics. Brit J

Addict 78:429-435, 1983.

Chait, L.D., and Johanson, C.E. The discriminative stimulus and subjective

effects of caffeine, benzphetamine and d-amphetamine in humans.

Psychopharmacology 1989, in press.

Chait, L.D.; Uhlenhuth, E.H.; and Johanson, C.E. An experimental paradigm for

studying the discriminative stimulus properties of drugs in humans.

Psychopharmacology 82:272-274, 1984.

Chait, L.D.; Uhlenhuth, E.H.; and Johanson, C.E. The discriminative stimulus

and subjective effects of d -amphetamine in humans. Psychopharmacology

86:307-312, 1985.

Chait, L.D.; Uhlenhuth, E.H.; and Johanson, C.E. The discriminative stimulus

and subjective effects of d-amphetamine, phenmetrazine, and fenfluramine

in humans. Psychopharmacology 89:301-306, 1986a.

Chait, L.D.; Uhlenhuth, E.H.; and Johanson, C.E. -l-he discriminative stimulus

and subjective effects of phenylpropanolamine, mazindol, and d

amphetamine in humans. Pharmacol Biochem Behav 24:1665-1672,

1986b.

Chait, L.D.; Uhlenhuth, E.H.; and Johanson, C.E. The reinforcing and subjective

effects of several anorectics in normal human volunteers. J Pharmacol

Exp Ther 242:777-783, 1987.

Chait, L.D.; Uhlenhuth, E.H.; and Johanson, C.E. Phenylpropanoiamine:

Reinforcing and subjective effects in normal human volunteers.

Psychopharmacology 96:212-217, 1988.

Chait, L.D.; Uhlenhuth, E.H.; and Johanson, C.E. Individual differences in the

discriminative stimulus effects of d-amphetamine in humans. Drug Dev

Res 1989, in press.

Corwin. R.L.; Woolverton, W.L.; Schuster, CR.; and Johanson, C.E. Anorectics:

Effects of food intake and self-administration in rhesus monkeys. Alcohol

Drug Res 7:351-361, 1987.

de Wit, H.; Pierri C.E.; and Johanson, C.E. Reinforcing and subjective effects of

diazepam in non-drug-abusing volunteers. Pharmacol Biochem Behav

1989a, in press.

206
de Wit, H.; Pierri, J.; and Johanson, C.E. Assessing individual differences in

ethanol preference using a cumulative dosing procedure.

Psychopharmacology 1989b, in press.

de Wit, H.; Uhlenhuth, E.H.; and Johanson, C.E. Lack of preference for

flurazepam in normal volunteers. Pharmacol Biochem Behav 21:865-869,

1984a.

de Wit, H.; Johanson, C.E.; and Uhlenhuth, E.H. Reinforcing properties of

lorazepam in normal volunteer subjects. Drug Alcohol Depend 13:31-41,

1984b.

de Wit, H.; Uhlenhuth, E.H.; and Johanson, C.E. Drug preference in normal

volunteers: Effects of age and time of day. Psychopharmacology 87: 186-

193, 1985.

de Wit, H.; Uhlenhuth, E.H.; and Johanson, C.E. Individual differences in the

reinforcing and subjective effects of amphetamine and diazepam. Drug

Alcohol Depend 16:341-360, 1986a.

de Wit, H.; Uhlenhuth, E.H.; Hedeker, D.; McCracken, S.; and Johanson, C.E.

Lack of preference for diazepam in anxious volunteers. Arch Gen

Psychiat 43:533-541, 1986b.

Garza, R. de la, and Johanson, C.E. The discriminative stimulus properties of

intragastrically administered d-amphetamine and pentobarbital in rhesus

monkeys. J Pharmcaol Exp Ther: 243:955-962, 1987.

Greenblatt, D.J.; Schillings, R.T.; Kriakopoulos, A.A.; Schrader, R.I.; Sisenwine,

S.F.; Knowles, J.A.; and Ruelius, H.W. Clinical pharmacokinetics of

lorazepam. Clin Pharmacol Ther 20:329-339, 1976.

Griffiths, R.R.; Bigelow, G.E.; and Liebson, I.A. Suppression of ethanol selfadministration by contingent time-out from social interactions of

alcoholics. Behav Research Ther 12:327-334, 1974.

Griffiths, R.R.; Bigelow, G.E.; and Liebson, I. Human drug self-administration:

Double blind comparison of pentobarbital, diazepam, chlorpromazine, and

placebo. J Pharmacol Exp Ther 210:301-310, 1979.

Griffiths, R.R.; Bradford, L.D.; Lukas, S.E.; Brady, J.V.; and Snell, J.D. Selfinjection of barbiturates and benzodiazepines in baboons.

Psychopharmacology 75:101-109, 1981.

Jasinski, D.R. Assessments of the dependence liability of opiates and sedativehypnotics. In: Goldberg L., and Hoffmeister F., eds. Psychic

Dependence. Bayer-Symposium IV. Berlin: Springer, 1973, pp. 160-170.

Jasinski, D.R.; Martin, W.R.; and Hoeldtke R.D. Effects of short and long term

administration of pentazocine in man. Clin Pharmacol Ther 16:645-652,

1970.

Jasinski, D.R.; Martin W.R.; and Sapira J.D. Antagonism of the subjectivebehavioral, pupillary, and respiratory depressant effects of cyclazocine by

naloxone. Clin Pharmacol Ther 9:217-222, 1968.

Jasinski, D.R.; Nutt, J.G.; Griffith J.D. Effects of diethylpropion and damphetamine after subcutaneous and oral administration. Clin Pharmacol

Ther 16:645-652, 1974.

Johanson, C.E. Several pharmacological and environmental variables affecting

drug preference in rhesus monkeys. Pharmacol Rev 27:343-355, 1975.

207
Johanson, C.E. The effects of electric shock on responding maintained by

cocaine injections in a choice procedure in the rhesus monkey.

Psychopharmacology 53:277-282, 1977.

Johanson, C.E. Benzodiazepine self-administration in the rhesus monkey.

Pharmacol Biochem Behav 26:521-526, 1987.

Johanson, C.E., and Balster, R.L. A summary of the results of a drug selfadministration study using substitution procedures in rhesus monkeys.

Bull Narc 30:43-54, 1978.

Johanson, C.E., and Schuster, C.R. A choice procedure for drug reinforcers:

Cocaine and methylphenidate in the rhesus monkey. J Pharmacol Exp

Ther 193:676-688, 1975.

Johanson, C.E., and Schuster, C.R. A comparison of cocaine and diethylpropion

under two different schedules of drug presentation. In: Ellinwood, E.H.,

and Kilbey, M.M. eds., Cocaine and Other Stimulants. New York:

Plenum Press, 1977, pp. 545-570.

Johanson, C.E., and Uhlenhuth, E.H. Drug self-administration in humans. In:

Krasnegor, N., ed., Self-Administration of Abused Substances: Methods

for Study. National Institute on Drug Abuse Research Monograph No.

20. DHEW Publication No. (ADM) 78-727. Washington, D.C.: Supt.

Docs.. Govt. Print. Off., 1978 pp. 68-85.

Johanson, C.E., and Uhlenhuth, E.H. Drug preference and mood in humans:

d-amphetamine. Psychopharmacology 71:275-279, 1980a.

Johanson, C.E., and Uhlenhuth, E.H. Drug preference and mood in humans:

Diazepam. Psychopharmacology 71:269-273, 1980b.

Johanson, C.E., and Uhlenhuth, E.H. Drug preference in humans. Fed Proc

41:228-233, 1982.

Johanson, C.E.; Kilgore, K.; and Uhlenhuth, E.H. Assessment of dependence

potential of drugs in humans using multiple indices. Psychopharmacology

81:144-149, 1983.

Johanson, C.E.; Woolverton, W.L.; and Schuster, C.R. Evaluating laboratory

models of drug dependence. In: Meltzer, H.Y., ed.. Psychopharmacology.

The Third Generation of Progress. New York: Raven Press, 1987,

pp. 1617-1625.

Martin, W.R. Assessment of the abuse potentiality of amphetamines and LSDlike hallucinogens in man and its relationship to basic animal assessment

programs. In: Goldberg, L., and Hoffmeister, F., eds. Psychic

155.

Dependence Bayer Symposium IV. New York: Springer, 1973, pp. 146-

Martin, W.R.; Jasinski, D.R.; Haertzen C.A.; Kay, D.C.; Jones, B.E.; Mansky,

P.A.; and Carpenter R.W. Methadone- a reevaluation. Arch Gen Psychiat

28:286-295, 1973.

Martin, W.R.; Sloan, J. W.; Sapira, J.D.; and Jasinski, D.R. Physiologic,

subjective and behavioral effects of amphetamine, methamphetamine,

ephedrine, phenmetrazine, and methylphenidate in man. Clin Pharmacol

Ther 12:245-258, 1971.

McCracken, S.G.; de Wit, H.; Uhlenhuth, E.H.; and Johanson, C.E. Preference

for diazapam in anxious adults. Clinical Pharmacol Ther 1989, in press.

208
McNair, D.M.; Lorr, M.; and Droppleman, L.F. Manual for the profile of mood

states. Educational and Industrial Testing Service, San Diego, 1971.

Mellinger, G.D.; Baiter, M.B.; and Uhlenhuth, E.H. Prevalence and correlates of

the long-term regular use of anxiolytics. J Amer Med Assoc 251:375-

379, 1984.

Schuster, CR., and Johanson, C.E. Relationship between the discriminative

stimulus properties and subjective effects of drugs. In: Colpaert, F.C., and

Balster, R.L., eds. Transduction of Mechanisms of Drug Stimuli, Berlin:

Springer-Verlag (Psychopharmacology Supplementum Series), 1988, pp.

161-175.

Schuster, C.R.; Renault, P.F.; and Blain, J. An analysis of the relationship of

psychopathology to non-medical drug use. Psychiatric Factors in Drug

Abuse Pickens, R.W., and Leonard, L.L., eds. New York: Grune and

Stratton, 1979, pp. 1-19.

Stem, K.A.; Chait, L.D.; and Johanson, C.E. Reinforcing and subjective effects

of caffeine in humans. Psychopharmacology 1989, in press.

Uhlenhuth, E.H.; Johanson, C.E.; Kilgore, K.; and Kobasa, S.C. Drug preference

and mood in humans: Preference for d-amphetamine and subject

characteristics. Psychopharmacology 74:191-194, 1981.

Wilson, M.C., and Schuster, C.R. Mazindol self-administration in the rhesus

monkey. Pharmacol Biochem Behav 4:207-210, 1976.

Woods, J.H.; Katz, J.L.; and Winger, G. Abuse liability of benzodiazepines.

Pharm Rev 39:251-419, 1987.

Woolverton, W.L.; Johanson, C.E.; de la Garza, R.; Ellis, S.; Seiden, L.S.; and

Schuster, C.R. Behavioral and neurochemical evaluation of

phenylpropanolamine. J Pharmacol Exp Ther 237:926-930, 1986.

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ACKNOWLEDGMENTS

This research was funded by grants from the National Institute on Drug

Abuse.

AUTHORS

Chris E. Johanson, Ph.D.

Associate Professor

Department of Psychiatry

Uniformed Services University of the Health Sciences

4301 Jones Bridge Road

Bethesda, Maryland 20814

Harriet de Wit, Ph.D.

Associate Professor

Drug Abuse Research Center

Department of Psychiatry

University of Chicago Pritzker School of Medicine

5841 S. Maryland Avenue

Chicago, Illinois 60637

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CHAPTER 10

Relationship Between Self-Reported Drug Effects and

Their Reinforcing Effects: Studies with Stimulant

Drugs

Marian W. Fischman, Ph.D.

INTRODUCTION

Traditional approaches to characterizing a drug’s profile of action and

assessing its abuse liability in humans have utilized a variety of selfreport measures (e.g., Martin et al., 1971; Jasinski 1977). Researchers

have predicted the abuse liability of the unknown compound based on the

extent to which the profile of self-reports generated by an unknown drug

is similar to that of a known drug of abuse (Fischman 1977). It has been

assumed that “positive,” “euphoria-like” effects are an indirect measure

of a drug’s reinforcing effects (Jasinski et al., 1974). Standardized

questionnaires have been employed in determining the pattern of responses associated with the behavioral and physiological effects of

pharmacologic agents and the profiles of drug effects thus obtained have

provided a major basis for the prediction of the abuse liability of a broad

range of compounds.

It has been argued (Schuster et al., 1981) that humans, asked to give a

verbal response about the effect of a drug, are really utilizing the

discriminative stimulus properties of the drug in the same way as animals

required to differentiate between two drugs by depressing different levers.

In both cases, the self-reporting response is an operant, maintained by its

consequences. The monkey or rat is given careful lever press training to

differentially respond todifferent drug stimuli, while humans have learned

to apply labels (e.g., sleepy, happy, friendly, etc.) through differential

reinforcement of these verbal responses as they grow up. In addition,

non-human research subjects can also be shaped to respond to labels

when given an appropriate conditioning history (Lubinski and Thompson

1988). Most humans have a relatively common conditioning history in

211
this regard, and the generality of such histories can be attested to by the

generally similar verbal reports obtained within drug classes over a wide

range of human subjects. The generality of these drug classes appears to

extend across species since laboratory animals trained to respond

differentially to different classes of drugs do so in a manner concordant

with the differential profiles of self-reports generated by these same classes

of drugs when administered to experienced drug users (see Schuster et al.,

1981). The care with which these self-reported subjective effects data

should be collected is obvious if one remembers that operant behavior,

which, of course, includes verbal behavior, can be altered through

manipulation of the contingencies associated with that behavior. The

formal properties of verbal behavior are maintained by social contingencies

(e.g., Wolfert and Hayes 1988; Greenspoon 1955), and tight control over

these contingencies is essential for generating replicable results.

The Addiction Research Center Inventory (ARCI), a frequently-used

instrument for evaluating self-report of drug effects, was developed with

the underlying hypothesis that different classes of abused drugs produce

different spectra of self-reported effects. The resultant drug-related scales

were empirically derived using prototypic drugs from each of the classes

being categorized. Thus, there are sedative-related scales such as the

Pentobarbital Chlorpromazine Alcohol Group (PCAG) Scale, stimulant

scales such as the Benzedrine Group (BG) Scale, etc. There is, in addition,

a composite drug effects scale, often referred to with the term “euphoria,”

(e.g., Jasinski et al., 1974) that seems to show increases with all drugs of

abuse. Scores on the Morphine Benzedrine Group (MBG) Scale increase

in a dose related fashion after administration of narcotic analgesics,

barbiturates, or stimulant drugs. It has been suggested that to the extent

that drugs produce this “euphoria” measured by the MBG scale of the

ARCI, they will be abused “on the street.” In fact, Jasinski et al. (1984)

have stated that scores on a drug “liking” scale (Fraser et al., 1961) and

“MBG scale scores are the hallmark subjective effects of abused drugs

and define a drug as a euphoriant” (p. 197). Other drug rating scales have

been developed or adapted from pre-existing scales, and have been used

to measure self-reports in much the same way as the ARCI (e.g., Profile

of Mood States, McNair 1971; “liking,” de Wit et al., 1986).

These early studies evaluating drugs for abuse liability in humans did not

measure the most salient feature of abuse -- the actual drug taking behavior.

Screening drugs for abuse liability in laboratory animals, on the other

hand, has concentrated on evaluating their ability to maintain responding

leading to their delivery. The validity of such procedures is obvious; if

we want to know something about a drug’s potential to maintain selfadministration, we can obtain the clearest data by studying that behavior.

The development of a methodology utilizing chronically implanted

212
intravenous catheters for drug delivery over 20 years ago (Clark et al.,

1961; Weeks 1962), and its utilization in the screening of many

psychotropic compounds has demonstrated a good correspondence

between those compounds self-administered by laboratory animals and

those abused by humans (Johanson and Balster 1978). It is only relatively

recently that we have begun to correlate these reinforcing properties of

drugs with their discriminative stimulus properties, in either laboratory

animals or human volunteer subjects (Bigelow and Preston, this volume).

Schuster and his colleagues (1981) surveyed the drug self-administration/

subjective drug effects literature for studies utilizing self-report ratings

on the MBG scale of the ARCI to measure the effects of drugs that were

also reported in the non-human self-administration literature. A review

of the literature from 1970-76 indicated that it is often the case that drugs

which readily serve as reinforcers in human and non-human research

subjects also cause effects which lead to self-reports related to “euphoria.”

This, however, is not always the case, and it is the premise of this paper

that these two actions of a drug can dissociate under a number of conditions.

This will be discussed by utilizing data collected with stimulant drugs,

specifically with cocaine. Cocaine is the example being used because

although it is not a new drug, its effects were relatively unknown until

recently, and it was only in the mid 1970s that we began to study its effects

in humans.

LABORATORY RESEARCH

Single Dose Studies

Initial studies evaluated the physiological and behavioral effects of cocaine,

attempting to correlate self-reported effects with cardiovascular changes,

and relating these effects to cocaine plasma level. Normal healthy human

volunteers, ranging in age from 21-45, and each with a history of cocaine

use participated. Prior to acceptance in the study each volunteer passed

an initial screening consisting of an extensive drug history interview, a

psychiatric interview, and a complete physical examination. All of the

subjects were admitted to an inpatient Clinical Research Center on the

day prior to the first experimental session, where they were carefully

monitored to insure that no drugs were taken other than those administered

during the experimental session. Each subject signed a consent form

which described the study, outlined the possible risks, and indicated that

psychotropic drugs and/or saline would be administered, possibly on a

daily basis, on all ten of the test days. When not participating in test

sessions, subjects were free to engage in non-drug recreational activities

of their own choice on the ward but were not allowed to leave the hospital.

Subjects were tested individually, once daily, in experimental sessions

213
lasting 2.5 or 3.5 hours, and were monitored from an adjacent room.

Subjects had intravenous lines inserted and were fitted with physiological

recording equipment such as heart rate electrodes, a blood pressure cuff,

and Manning bellows to measure respiration rate. Cocaine HCl dissolved

in saline or physiological saline alone was injected over a 60 second

period, and physiological measures were periodically collected. In

addition, subjects answered two standard questionnaires before and

repeatedly after drug or saline injection.

The Profile of Mood States (POMS) (McNair et al., 1971) is a 72 item 5-

point adjective rating scale which yields scores on eight clusters: Anxiety,

Depression, Anger, Vigor, Fatigue, Confusion, Friendliness, and Elation.

Two derived scores were also used. Arousal scores were obtained by

adding together the scores for Vigor and Anxiety and subtracting the

scores for Confusion and Fatigue, and Positive Mood scores were obtained

by subtracting the Depression from the Elation score. This version of the

POMS has been described by Fischman and Schuster (1980). A second

questionnaire was a short form of the 550-item ARCI (Haertzen 1966),

consisting of 49 items compiled by Martin et al. (1971) which have been

shown to be sensitive to the effects of a number of different stimulant

drugs. The questions were taken from the Morphine Benzedrine Group

(MBG) Scale, the Pentobarbital-Chlorpromazine-Alcohol Group (PCAG)

Scale, the LSD Scale, the Benzedrine Group (BG) Scale, and the

Amphetamine (A) Scale.

Early work with cocaine evaluated the drug as if it were an unknown

compound, and initial single dose studies assessed its similarity to

amphetamine (Fischman et al., 1976). It was assumed that similar profiles

of action to a prototypic stimulant drug of abuse, amphetamine, might

predict a similar abuse liability profile (Fischman 1977). The profile of

cocaine’s action in these initial intravenous studies indicated that cocaine

is similar to d-amphetamine in both its cardiovascular and self-reported

effects. Further, cocaine had measurable but not toxic effects in the 16-

32 mg intravenous dose range, a dose range subjects rated as comparable

to that they were taking outside of the laboratory.

Figure 1 presents heart rate data from nine subjects tested with single

intravenous doses of cocaine. Heart rate increased significantly after 16

and 32 mg cocaine, peaking at 8-12 minutes after injection, and returning

to baseline levels within 30-40 minutes. This decrease, seen also with

self-reported data measured with the POMS and ARCI (Fischman et al.,

1983b), parallels the decrease in cocaine blood levels seen after single

doses (Javaid et al., 1978). These data are presented in figures 2 and 3.

214
Figure 1: Median percent change in heart rate for one hour after injection of saline

or 4 to 32 mg cocaine. Percent change was calculated for each dose of cocaine with

reference to its own 30-minute predrug baseline. Saline function representsdata collected on day 8 of experimental series; shaded area indicates the semi-interquartile

range ofthosedata. (From Fischman et al., 1976, copyright 1976, American Medical

Association.)

Figure 2: Effects of a single dose of 16 or 48 mg cocaine or saline on scores of the

MBG scale of the ARCI and the Vigor scale of the POMS. Data represent the mean

of four subjects. (Data taken from Fischman et al., 1983b).

In single doses, as with cardiovascular changes, there is a predictable increase in measures of variables such as Arousal, Vigor, and Friendliness,

ratings of “high” (Fischman et al., 1983a, 1983b) and other stimulatedor “euphoria”-like reports such as the MBG scale of the ARCI, which

peak at 5-10 minutes after i.v. injection, and generally begin to return to

baseline within 30 to 60 minutes. Subjects state that they would be ready

to take another dose of the drug during this 30 to 60 minute interval.

215
Interestingly, subjects

were unable to differentiate between cocaine and

d-amphetamine when the

two drugs were administered under blind conditions, providing additional evidence for cocaine’s comparability to

amphetamine. These subjects were required to

identify the drug received

within the first 60 minutes

after injection, and therefore were not able to dis- Figure 3: Mean cocaine plasma level for 10 subjects

criminate on the basis of administered 32 mg intravenous cocaine. (Data

duration of effect. Further, taken from Javaid et al., 1978).

subjects were given no training with the two drugs in question, relying

only on their training outside of the laboratory, which was neither systematic nor necessarily accurate. Street drug is often cut with a variety of

other substances, and frequently has low concentrations of the drug people

believe they have purchased. It is likely, therefore, that subjects given

discrimination training in the laboratory would be able to differentially

respond to these two drugs.

The profile of cocaine’s action in the single dose intravenous studies

suggested that cocaine had high abuse liability - rapid onset of action with

major subjective effects at doses that singly had relatively small

physiological effects, and a reasonably short duration of action. A short

duration of action that allows for repeated dosing provides repeated

opportunities for the initial rapid drug onset, or “rush,” which experienced

users claim is the “best part” of the drug’s effect. Under this single dose

paradigm, it is clear that self-reported “positive” effects (i.e., stimulantlike) indicate that cocaine has a significant abuse liability. Epidemiological

studies have recently verified that cocaine and the amphetamines are

extensively used and abused (see review by Fischman 1987).

Self-Administration Studies

Although the single dose paradigm with drug administered by the

experimenter is a useful procedure for evaluating profile of action,

including toxicity, it provides little information about the effects of the

drug when it is relatively freely available and users can take it as they

would outside of the laboratory. The next step in evaluating cocaine’s

216
abuse liability therefore, was to develop a self-administration procedure

which could provide information about patterns of intake and the effects

of the drug when taken under subject-controlled administration conditions.

In this manner the physiological and self-reported effects of cocaine

could be compared to blood levels engendered during cocaine selfadministration. The procedure developed here was adapted from that

developed by Johanson et al. (1975) to test drug choice in rhesus monkeys.

Normal healthy volunteer subjects with histories of cocaine use participated

for 2 weeks in daily experimental sessions lasting 2-3 hours (Fischman

and Rachlinski 1989). During each experimental session subjects sat in

a comfortable reclining chair facing a CRT screen and a response console

containing a computer keyboard and three 1.7 x 1.7 mm touch sensitive

plates. Thirty minutes prior to the daily test session, each subject had two

Minicath infusion sets inserted, one into each arm. As in earlier studies,

these were connected via extension tubing to bags of 0.9 percent

physiological saline which was slowly dripped in order to maintain the

patency of the intravenous connection. Drug or saline was injected through

one catheter, and the other was used to withdraw blood for later cocaine

blood level analysis (see Javaid et al., 1983). Each test session consisted

of a 30-minute pre-drug baseline recording period followed by a 1- or 2-

hour drug choice session. Physiological and behavioral measures were

taken repeatedly during each test session. All subjects were monitored

for 1 hour after the end of the choice session.

During the 30 minutes immediately preceding the beginning of each

choice session, baseline electrocardiogram (ECG) and blood pressure

measures were collected, and a series of questionnaires was presented on

the CRT in front of them, one item at a time, paced by the subject’s

responses on the computer keyboard. These questionnaires included the

POMS and the ARCI as well as a set of Visual Analog Scales, which

consisted of six 10 cm lines, presented one at a time, labeled “not at all”

on the left side and “extremely” on the right side of the screen. The lines

were labeled consecutively “stimulated,” “high,” “anxious,” “sedated,”

“down,” and “hungry.” Subjects could indicate how they felt in relation

to each descriptive adjective by moving the cursor to a specific place on

each line.

Subjects were given a choice between cocaine (4, 8, 16 or 32 mg) and

saline or between two doses of cocaine periodically during each test

session. They were told that one solution (solution A or solution B) would

be associated with the left touch plate on the console in front of them, and

a second solution (solution A or solution B) would be associated with the

right touch plate. Although the drug/position association would hold

within a daily test session, it could vary between test sessions. Solution

A was always a cocaine dose; solution B was a lower dose of cocaine or

217
saline. Subjects could choose an intravenous injection by tapping on one

of the two touch plates, with the first tap indicating an irreversible choice

and the required number of taps varying from 10 to 200. When the

response requirement was completed, the questionnaires were presented,

one item at a time on the CRT. After completion of these, which took

approximately 4 minutes, a blood sample was taken for cocaine blood

level analysis, and the chosen solution was injected over a 1 minute

period. In some studies another drug choice was again immediately

available, while in other studies a timeout, during which no drug was

available, was inserted between each drug choice trial.

Subjects reliably chose cocaine in doses of 4, 8, 16 and 32 mg/injection

over saline. This was true whether the response cost for an injection was

10 responses or 200 responses. They also chose 32 mg cocaine over 16

mg. Interestingly, in the single dose studies described above, subjects

rated the 16 and 32 mg doses comparably, and somewhat larger than the

average dose of stimulant they were accustomed to taking outside of the

laboratory (Fischman et al., 1976). In addition, no self-reporteddifferences

between 16 and 32 mg were obtained using the ARCI or the POMS. In

the present self-administration study, 16 and 32 mg injections of cocaine

also engendered similar profiles of self-reported effects. Only scores on

the LSD scale of the ARCI and the Anxiety, Vigor, and Arousal scales of

the POMS revealed significant differences between these two doses. It

is important to note that, despite similarities in the self-reported effects

of these two doses, when allowed to choose between them, subjects

showed a clear preference for the higher dose.

Subjects self-administered cocaine in a regular pattern, spacing injections

every 6-10 minutes during the one hour session, when no timeout occurred.

Figure 4 presents data from a single subject (#50) on day 6 of a study in

which the choice was between 32 mg and saline. This subject chose 32

mg on all six of the choices she made, with cocaine plasma levels reaching

1100 ng/ml. Regular rates of cocaine intake have also been reported for

non-human research subjects with lever pressing maintained by injections

of cocaine (Johanson 1980). This subject showed a maximal heart rate

after the initial dose of 32 mg cocaine, when heart rate, 55 beats/min prior

to cocaine, reached 80 beats/min. This represents a 45 percent increase

in heart rate 8 minutes after intravenous injection of 32 mg cocaine.

Plasma levels of cocaine were approximately 540 ng/ml at this time.

Heart rate remained around 70 beats/min, a 27 percent increase above

baseline, until approximately 20 minutes after the start of the session,

prior to the third cocaine injection. After that, despite an increase in

plasma level from 710 ng/ml to 1100 ng/ml over the remaining portion

of the session, heart rate returned to levels that were 10-12 percent of

baseline, and within the range of variability for this subject. MBG scores

218
session and just prior to the third dose of cocaine administered. MBG

scores remained level or decreased after this, falling to a low of eight by

the end of the session.

Figure 4: Data from Subject #50 give the

choice between saline and 32 mg cocaine

Arrows represent choices of 32 mg cocaine.

Cocaine plasma levels, heart rate and MBG

scores are presented for thar session.

Subjects’reports of cocaine’s

effects during this self-administration procedure were

generally similar to those

obtained with other stimulant

drugs (Martin et al., 1971) and

with other drug administration

procedures (e.g., Fischman, et

al., 1976, 1983 a,b). There

were increases on the BG,

MBG and LSD scales, as were

also reported for a number of

other psychomotor stimulant

drugs (Martin et al., 1971) and

for cocaine (Fischman, et al.,

1976).

POMS data also reflected the

similarity between cocaine

and other psychomotor stimulants in the self-report data

engendered. Johanson and her

colleagues (Johanson and

Uhlenhuth 1980; de Wit et al.,

1986), studying the effects of

oral drug, have generally

found increases in Vigor,

Confusion, Elation, Arousal

and Positive Mood scores as

well as decreases in Fatigue

scores after amphetamine as

well as phenmetrazine (Chait

et al., 1985). Sixteen and 32

mg cocaine similarly caused

increases in those scores as

well as additional scales such

as Anxiety and Friendliness.

The route of administration

probably accounts for this

increased sensitivity of the

current procedure.

219
Of particular interest in the current study were the differential effects of

the lower doses of cocaine and saline on drug self-administration. This

was especially evident when the response cost for an intravenous injection

was raised to 200 responses. Subjects reliably chose 8 mg cocaine over

4 mg, and both doses were reliably chosen over saline. Neither self-report

data nor cardiovascular measures indicated any differential effects of

these lower intravenous doses. Subjects continued to self-administer 4

mg even when a timeout was introduced between drug choices. The

“euphorigenic” effects of the self-administered drug, generally assumed

to be a major determinant of abuse liability (Jasinski et al., 1984), appear

not to be necessary to predict cocaine’s reinforcing function. This

dissociation between the verbal report data and the self-administration

data provides important evidence for the sensitivity of this choice paradigm.

Figure 5 presents mean scores on the

MBG scale during cocaine choice

sessions. These scores increased

significantly (p<0.01) and remained

elevated through the first few

injections of 16 mg and 32 mg cocaine,

but then decreased even though plasma

cocaine concentration continued to rise

during repeated cocaine injections.

The data presented here do not

represent a ceiling effect. The maximal

score for this scale is 16, and mean

scores of 13.9 have been reported after

single intravenous doses of 48 mg

cocaine (Fischman et al., 1983b).

Similar inverted u-shaped curves were

collected for reports of feeling “high”

and “stimulated.” An example of the

self-reported effects data collected

during a single session are presented

Figure 5: The effects of repeated

doses of 16 or 32 mg cocaine on the

MBG scale of the ARCI. Mean

change from base-line scores are

presented after each injection of 16

or 32 mg cocaine. (Taken from Fischman and Rachlinski, submitted,

1989.)

in figure 4, where MBG scores peaked at 13, a considerably larger score

than the mean shown in figure 5. The data from this single subject during

a single session are quite similar in shape to the mean data presented in

figure 5.

These data point to the development of tolerance within a single session.

The development of acute tolerance, defined as a decrease in

responsiveness to cocaine within a single session, was also reported to

occur when a single intravenous injection of cocaine was administered 1

hour after subjects were allowed to inhale 96 mg of cocaine powder

(Fischman et al., 1985). When self-administered repeatedly within a

220
session, 16 and 32 mg exerted maximal and significant cardiovascular

and self-reported effects following the first injection, with subsequent

injections exerting smaller or no effects. This was true despite a steadily

increasing cocaine plasma level, achieving peaks of almost 1000 ng/ml

following the final injection. Subjects exhibited no residual tolerance to

the self-reported effects of cocaine 22 hours later, when the next test

session was carried out. Neither baseline levels nor response to the initial

dose of cocaine were influenced by the previous day’s dosing regimen.

This was the case for both the two dose experimenter-initiated regimen

(Fischman et al., 1985) and for the repeated dose self-administration

paradigm (Fischman and Rachlinski 1989).

Cocaine caused increases in heart rate comparable to those reported in

other studies evaluating the effects of this drug administered intravenously

(Fischman et al., 1976, 1985). As with most of the self-report measures,

16 and 32 mg did not produce signicantly different effects on heart rate

although 8 and 16 mg did. The effects of repeated injections of 4 mg

cocaine were no different than repeated injections of saline. Heart rate

changes paralleled those measured on most of the self-report questionnaire

scales. Maximal effects were measured after the second injection of 8,

16 or 32 mg cocaine, with no further increases seen. As with the verbal

report data, these results do not represent a ceiling effect. For example,

mean heart rate for the first 6 minutes after the second injection of 16 mg

averaged 95 beats per minute, a significant increase from the mean baseline

of 74 beats per minute, but clearly below maximal levels. Peak heart rates

after this injection reached 120-135 beats per minute for some subjects

while for others they remained below 100 beats per minute. The data

clearly indicate a decrease in cocaine’s heart rate increasing effects when

repeated doses are administered within a relatively short period of time.

These effects are also shown, in figure 4, for a single subject.

Ambre et al., (1988) carefully demonstrated acute tolerance to the heart

rate increasing effects of cocaine using a constant intravenous cocaine

infusion to maintain a steady state cocaine plasma level for 4 hours.

Tolerance to the chronotropic effect was incomplete, however, since heart

rate remained stable but elevated above baseline levels. Rating of “high,”

however, declined to baseline by approximately 270 minutes after the

onset of cocaine administration. Kumor et al. (1988), on the other hand,

reported little evidence of tolerance development to cocaine’s heart rateand blood pressure-increasing effects in subjects maintained at a stable

blood level. It is possible, however, that the drop in heart rate and blood

pressure they reported after 15 minutes might represent a partial

development of acute tolerance. The data from a number of studies

(Fischman et al., 1985, 1989; Foltin et al., 1989; Ambre et al., 1988) thus

are generally supportive of the development of an acute tolerance to

221
cocaine’s effects, some of which were collected under self-administration

conditions comparable to those seen outside of the laboratory. Acute

tolerance development might be an important factor for those who “binge”

on cocaine.

Generalization to Other Drugs

Cocaine is not simply another amphetamine. It is, in fact, a local anesthetic

with stimulant properties, and it is logical to ask whether its local anesthetic

properties affect cocaine’s profile of effects. For example, do these qualities

contribute to its reinforcing effectiveness? Data from the animal laboratory

have shown that at least some of the synthetic local anestheticscanmaintain

self-administration in non-human research subjects (Ford and Balster

1977; Hammerbeck and Mitchell 1978; Johanson 1980). The data on

local anesthetic self-administration in non-humans have been puzzling

since, in general, drugs which serve as reinforcers in animals do so in

humans, and it is assumed that this property of reinforcing effectiveness

is an important factor for a drug’s dependence potential. Despite these

reports of local anesthetic self-administration in non-humans, however,

they do not appear to be commonly abused by humans.

We used the same general approach in collecting abuse liability information

about the local anesthetics that we did with cocaine. Volunteer subjects

were tested with a range of intravenous doses of one drug, procaine, from

the group of those self-administered by monkeys, and one drug, lidocaine,

from the group of those that were not self-administered (Fischman et al.,

1983a,b). The effects of these two drugs were compared to those of

cocaine, a local anesthetic with substantial abuse potential. We were

particularly interested in the profile of self-reported effects engendered

by these drugs, as self-report profiles have been related to abuse potential

in the past.

Matched intravenous doses (16, 32, and 48 mg) of cocaine, procaine and

lidocaine were administered, one dose per day, in a balanced order, and

physiological and self-reported effects of these three drugs weremeasured.

In addition, subjects were asked to identify the drug they were administered

each day, choosing among “placebo,”“cocaine,” or “other.” Only cocaine

had significant cardiovascular effects, causing dose-related increases in

heart rate and blood pressure. Lidocaine produced no consistent effects

on self-report questionnaires, and all doses were identified as “placebo.”

Apreviousstudy, however, reported that cocaine and lidocaine engendered

similar ratings of “high” when these two drugs were topically administered

in solution intranasally in matched doses of 0.19, 0.38 and 0.75 mg/kg

(Van Dyck et al., 1979). However, in that study, no statistical analysis of

the data were reported, and it was likely that cocaine’s effects were not

significantly different from placebo (see Fischman 1984). The similarity

222
between cocaine and lidocaine on ratings of “high” in the study by Van

Dyck et al. (1979) may have been the result of the absence of any drug

effect, as might be anticipated given the low doses of cocaine tested. In

the present study no dose of procaine produced self-reported effects

different from placebo, excepting that subjects identified the 48 mg dose

of procaine as cocaine. Assuming that the 48 mg dose might have been

a threshold dose of procaine, 96 mg procaine was also administered, and

it too was identified as cocaine. In addition, although there were no

significant effects of either dose on responses on the POMS or ARCI, 96

mg procaine caused a significant increase in scores on the “high” and

“stimulated” scales.

These data indicate that procaine and cocaine share some stimulus

properties, not including cardiovascular changes or effects measured by

the POMS and ARCI, but perhaps including the potential stimulus cues

measured by the “high” and “stimulated” responses, cues shared by many

drugs. To the extent that changes in “high” and “stimulated” suggest a

possible reinforcing function this implies that procaine might be expected

to function as a reinforcer in humans. The next study directly investigated

this possibility by allowing subjects to self-administer procaine or lidocaine

using the choice paradigm (Fischman 1981).

No subject self-administered lidocaine at greater than chance levels. As

has been shown with rhesus monkeys, lidocaine does not maintain

responding leading to its administration. As with the rhesus monkeys,

however, procaine did maintain responding (Johanson 1980; Woolverton

and Balster 1982). All subjects chose 48 mg intravenous procaine over

saline on at least 75 percent of their choices, but when subjects were

allowed to choose between 8 mg cocaine and 48 mg procaine, all subjects

chose the cocaine. Eight mg of cocaine was also reliably chosen over 96

mg procaine.

It appears that cocaine and procaine have some overlapping stimulus

properties which do not include heart rate changes, nor scores on several

standard questionnaires, but do include something classified by subjects

in the category of “getting high.” Clinical data also suggest that procaine

infusions are often accompanied by reports of mood changes in patients

(Ostfeld et al., 1977; Zung et al., 1974). Despite these similarities, procaine

is not thought to be abused by humans. This discrepancy could be due to

several factors. First of all, it has a short duration of action, with an

elimination half life of approximately 8 minutes compared with a 40-60

minute half-life for cocaine. A very short duration of action requires

frequent injection, which is inconvenient for humans to arrange. Potency

differences are also relevant. There appears to be a 6-10 fold potency

differential between cocaine and procaine when the animal self223
administration and discriminative stimulus property data are examined

(Woolverton and Balster 1982). The need for both frequent injections

and substantial amounts of drug might well be a reason for its lack of

street use. Secondly, it is possible that procaine is a reinforcer and is being

used on the street in its own right. Procaine is commonly misrepresented

as cocaine or mixed with the cocaine that is sold on the street (Hammerbeck

and Mitchell 1978). It has also been described as used to cut heroin. This

may be a situation in which the presumably inactive substance used as

filler is not, in fact, inactive.

Drug Interactions

If self-reported drug effects provide information which can predict abuse

liability, it should be possible to shift these verbal reports of cocaine’s

effects with a drug which is useful as a pharmacological intervention in

treating cocaine abusers. Kleber and his colleagues have reported that

cocaine abusers who are administered desipramine and maintained in

behavioral treatment remain in treatment and are abstinent significantly

more than those given only the behavioral treatment (Gawin and Kleber

1984).

Seven normal healthy volunteer subjects were tested daily and given the

opportunity to self-administer doses of cocaine or saline approximately

once every 12 minutes to a maximum of seven injections within a 90

minute period (Fischman and Foltin 1988). As with the choice study

described above, subjects could choose saline or a dose of cocaine by

responding on the left or right lever. The lever associated with cocaine

or saline remained constant within a day, but could change from day-today.

Sessions began with a 30 minute baseline period. Stimulus lights signalled

the availability of a drug choice, and the initial response on one of two

levers indicated an irreversible choice. Next, 200 responses were followed

by injection of the chosen solution, if medically indicated. Finally the

self-report drug effects questionnaires were presented and blood was

occasionally withdrawn for cocaine levels.

Seven choice opportunities were presented during a typical session. The

self-administration protocols were carried out over a 14-day interval

while subjects resided in the hospital. A 3-4 week desipramine outpatient

maintenance period was then carried out. During this period subjects

reported to the laboratory daily, and bloods were withdrawn to monitor

desipramine blood levels twice weekly. Blood levels were maintained at

approximately 125 ng/ml during the remainder of the study. After the

outpatient desipramine maintenance period, subjects were returned to the

hospital and a second 14-day choice phase was begun with desipramine

blood levels maintained at approximately 125 ng/ml.

224
Desipramine had no effect on cocaine-taking behavior, with a mean of

approximately six injections requested during sessions in which cocaine

was available. Response rates and latency to first response were also

unchanged. We were, however, not always able to administer the injections

requested because of medical considerations (i.e., diastolic blood pressure

above 100 mg Hg or heart rate above 131 bpm), and this was more

generally related to the desipramine maintenance. Thus, fewer cocaine

injections were administered during desipramine maintenance.

Decreases in cocaine craving have been anecdotally reported for cocaine

abusers being treated with desipramine. In an effort to operationalize

“craving” a visual analog scale labeled “I want cocaine” was administered

as part of the battery of self-report questionnaires answered repeatedly

during each session. Before desipramine maintenance, subject’s scores

on this scale were close to the maximum of 100. During desipramine

maintenance, scores on this scale were substantially and significantly

lower.

Cocaine’s stimulus properties were evaluated through the use of selfreported drug effects. As discussed above, a number of self-report scales

are reliably increased after administration of cocaine and other

psychomotor stimulant drugs. Desipramine had the effect of attenuating

scores on many of the stimulant-related scales including Arousal, Positive

Mood and Vigor on the POMS, and BG and MBG on the ARCI. Prior to

desipramine maintenance, these scores were increased by the initial dose

of cocaine in a dose-related fashion. Such effects have been found

previously for cocaine as well as for other psychomotor stimulant drugs,

such as amphetamine (Fischman and Rachlinski 1989; Johanson and

Uhlenhuth 1981). During desipramine maintenance, cocaine engendered

significantly lower scores on these scales.

A second pattern of effects on other self-report scales was also evident.

Desipramine maintenance resulted in lower placebo scores and

significantly higher scores in response to cocaine on the Confusion and

Anger scales of the POMS and the ARCI LSD scale, a measure of dysphoric

drug effects.

Although desipramine maintenance, under these controlled laboratory

conditions, does not appear to affect cocaine self-administration, it does

appear to modify some of cocaine’s subjective effects as reported by our

subjects. It is possible that, in a more elaborate choice paradigm,

desipramine-induced changes in the reinforcing effectiveness of cocaine

might be identified, perhaps by allowing subjects to choose another

reinforcer in preference to cocaine. If such a change does, in fact, occur,

desipramine maintenance of cocaine abusers might make it possible for

them to learn to respond to other stimuli in the environment, thereby

225
engendering something other than cocaine-seeking or cocaine-taking

behavior. The data we have collected are consistent with such a hypothesis.

CONCLUSIONS

The data discussed in this paper suggest a generally good correlation

between cocaine self-administration and its stimulant-related, “positive”

effects. There are, however, areas in which these two measures clearly

diverge, and these areas provide interesting topics for future research. It

is clear that the laboratory self-administration model provides a sensitive

paradigm for detecting those drugs which can maintain behavior leading

to their delivery. Changing the response requirement for a drug injection

increases the likelihood that small differences in dose will become more

relevant in determining drug choice. However, it is possible that under

these conditions subjects will work to self-administer drug, no matter

how small the dose. They will, on the other hand, often stop responding

when saline is their only choice, as we recently showed in the desipramine

maintenance study. It is possible that laboratory conditions provide cues

for drug-taking which do not exist outside of the laboratory. Thus, although

the choice self-administration model appears to be generally valid for the

identificationofreinforcingeffectiveness, itmightnoteffectively address

relative reinforcing effectiveness because no other reinforcers are

competing and no other behavior is required. Bigelow et al. (1974, 1975),

for example, manipulated contingencies such as social variables and

showed that they could have an effect on drug self-administration. What

would happen in these cocaine self-administration studies, for example,

if drug self-administration had an effect on earning power, decreasing it

slightly? We know, for example, that subjects required to perform a

simple learning task show increased cardiovascular responsivity as

evidenced by increased heart rate and blood pressure during the time they

are performing the task (Capriotti et al, 1988; Foltin et al, 1988). Cocaine

also increases heart rate and blood pressure. The two in combination

cause even greater increases, and when alcohol is added to this paradigm,

mean heart rates in excess of 60 percent of baseline have been measured

(Fischman and Foltin 1988). Unfortunately, there are no data available

on cocaine self-administration when subjects also have to perform tasks

in order to earn money, nor on self administration when subjects are

consuming other substances as well. These might be necessary to better

predict the conditions under which subjects take cocaine outside of the

laboratory.

The relationship between drug self-administration and self-reported effects

of the drug being administered appears to be complex, with self-reports

providing partial predictive power about the abuse liability of any drug.

226
It is clear, however, that they do not substitute for measuring the actual

drug taking behavior, and in the absence of a good measure of the drug

taking behavior we cannot be certain about whether a drug will support

self-administration, or about the conditions under which selfadministration will occur. It is only by evaluating these effects within a

behavioral context that we can fully understand and predict abuse liability.

REFERENCES

Ambre, J.J.; Belknap, S.M.; Nelson, J.; Ruo, T.I.; Shin, S.-G.; and Atkinson, A.J.

Acute tolerance to cocaine in humans. Clin Pharm Ther 44:1-8, 1988.

Bigelow, G.; Griffiths, R.R.; and Liebson, I. Experimental models for the

modification of human drug self administration: Methodological

developments in the study of ethanol self administration by alcoholics.

Fed Proc 34:1785-1792, 1975.

Bigelow, G.; Liebson, I.; and Griffiths, R.R. Alcoholic drinking: Suppression by

a brief time-out procedure. Behav Res Ther 12:107-115, 1974.

Capriotti, R.M.; Foltin, R.W.; Brady, J.V.; and Fischman, M.W. Effect of

marijuana on the task-elicited physiological response. Drug Alc Depend

21:183-188, 1988.

Chait, L.D.; Uhlenhuth, E.H.; and Johanson, C.E. The discriminative stimulus

and subjective effects of d-amphetamine in humans. Psychopharmacology

86:307-312, 1985.

Clark, R.; Schuster, C.R.; and Brady, J.V. Instrumental conditioning of jugular

self-infusion in the rhesus monkey. Science 133:1829, 1961.

de Wit, H.; Uhlenhuth, E.H.; and Johanson, C.E. Individual differences in the

reinforcing and subjective effects of amphetamine and diazepam. Drug

Alc Depend 16:341-360, 1986.

Fischman, M.W. Evaluating the abuse potential of stimulant and depressant drugs

in man. In: Thompson T., and Unna, K., eds. Predicting Dependence

Liability of Stimulant and Depressant Drugs. Baltimore: University Park

Press, 1977, pp. 261-284.

Fischman, M.W. Differential effects of cocaine, lidocaine and procaine in

humans. Paper presented, Annual Meeting of the Committee on Problems

of Drug Dependence, San Francisco, 1981.

Fischman, M.W. The behavioral pharmacology of cocaine in humans. In:

Grabowski, J., ed. Cocaine: Pharmacology. Effects and Treatment of

Abuse. National Institute on Drug Abuse Monograph No. 50, DHHS

(ADM)84-1326. Washington, D.C.: U.S. Govt. Print. Off., 1984, pp. 72-

91.

Fischman, M.W. Cocaine and the amphetamines. In: Meltzer, H.Y., ed.

Psychopharmacology: The Third Generation of Progress. New York:

Raven Press, 1987, pp. 1543-1553.

Fischman, M.W., and Foltin, R.W. Effects of desipramine maintenance on

cocaine self-administration. Psychoupharmacology 96:S20, 1988.

227
Fischman, M.W., and Foltin, R.W. Laboratory evidence for mechanisms of

cocaine-induced toxicity in humans. In: Czechowicz, D., ed. Clinical

Applications of Cocaine Research: From Bench to Bedside. National

Institute on Drug Abuse Research Monograph, Washington, D.C.: U.S.

Govt. Print. Off., in press.

Fischman, M.W., and Rachlinski, J.J. Cocaine self-administration in humans.

Psychopharmacology, submitted.

Fischman, M.W., and Schuster, C.R. Cocaine effects in sleep-deprived humans.

Psychopharmacology 72:1-8, 1980.

Fischman, M.W.; Schuster, C.R.; and Hatano, Y. A comparison of the subjective

and cardiovascular effects of cocaine and lidocaine in humans. Pharmacol

Biochem Behav 18:123-127, 1983a.

Fischman, M.W.; Schuster, C.R.; Javaid, J.I.; Hatano, Y.; and Davis, J. Acute

tolerance development to the cardiovascular and subjective effects of

cocaine. J Pharmacol Exper Ther 235:677-682, 1985.

Fischman, M.W.; Schuster, C.R.; and Rajfer, S. A comparison of the subjective

and cardiovascular effects of procaine and cocaine in humans. Pharmacol

Biochem Behav 18:711-716, 1983b.

Fischman, M.W.; Schuster, C.R.; Resnekov, L.; Shick, J.F.E.; Krasnegor, N.A.;

Fennell, W.; and Freedman, D.X. Cardiovascular and subjective effects of

intravenous cocaine administration in humans. Arch Gen Psychiatry

33:983-989, 1976.

Foltin, R.W.; Fischman, M.W.; Pedroso, J.J.; and Pearlson, G.D. Intranasal

cocaine self-administration. Drug Alc Depend, 1989, in press.

Foltin, R.W.; McEntee, M.A.; Capriotti, R.M.; Pedroso, J.J.; and Fischman, M.W.

Effect of cocaine on the task-elicited physiological response. Pharmacol

Biochem Behav, 1988, in press.

Ford, R.D., and Balster, R.L. Reinforcing properties of intravenous procaine in

rhesus monkeys. Pharmacol Biochem Behav 6:289-296, 1977.

Fraser, H.F.; Van Horn, G.D.; Martin, W.R. Wolbach, A.B.; and Isbell, H.

Methods for evaluating addiction liability. (a) “Attitude” of opiate addicts

toward opiate-like drugs, (b) A short-term “direct” addiction test. J

Pharmacol Exp Ther 133:371-387, 1961.

Gawin, F.H., and Kleber. H.D. Cocaine abuse treatment. Arch Gen Psychiatry

41:903-909, 1984.

Greenspoon, J. The reinforcing effect of two spoken sounds on the frequency of

two responses. Am J Psychology 68:409-416, 1955.

Haertzen, C.A. Development of scales based on patterns of drug effects using the

addiction research center inventory (ARCI). Psychological Reports

18:163-194, 1966.

Hammerbeck, D.M., and Mitchell, C.L. The reinforcing properties of procaine

and d-amphetamine compared in rhesus monkeys. J Pharmacol Exp Ther

204:558-569, 1978.

Jasinski, D.R. Clinical evaluation of sedative-hypnotics for abuse potential. In:

Thompson, T., and Unna, K.R., eds. Predicting Dependence Liability of

Stimulant and Depressant Drugs. Baltimore: University Park Press, 1977,

pp. 285-290.

Jasinski, D.R.; Johnson, R.E.; and Henningfield, J.E. Abuse liability assessment

in human subjects. Trends Pharmacol Sci 5:196-200, 1984.

228
Jasinski, D.R.; Nutt, J.G.; and Griffith, J.D. Effects of diethylpropion and damphetamine after subcutaneous and oral administration. Clin Pharmacol

Ther 16:645-652, 1974.

Javaid, J.I.; Fischman, M.W.; Schuster, CR.; Dekirmenjian, H.; and Davis, J.M.

Cocaine plasma concentration: Relation to physiological and subjective

effects in humans. Science 202:227-228, 1978.

Javaid, J.I.; Muss, M.; Fischman, M.W.; Schuster, C.R.; and Davis, J.M.

Kinetics of cocaine in humans after intravenous and intranasal

administration. Biopharm Drug Disp 4:9-18, 1983.

Johanson, C.E. The reinforcing properties of procaine, chloroprocaine and

proparacaine in rhesus monkeys. Psychopharmacology 67:189-194, 1980.

Johanson, C.E. Assessment of the dependence potential of cocaine in animals.

In: Grabowski, J., ed. Cocaine: Pharmacology, Effects and Treatment of

Abuse. National Institute on Drug Abuse Research Monograph No. 50,

DHHS Pub. No. (ADM) 84-1326. Washington, D.C.: U.S. Govt. Print.

Off., 1984, pp. 54-71.

Johanson, C.E., and Balster, R.L. A summary of the results of a drug selfadministration study using substitution procedures in rhesus monkeys.

Bull Narc; 30(3):43-54, 1978.

Johanson, C.E., and Schuster, C.R. A choice procedure for drug reinforcers:

Cocaine and methylphenidate in the rhesus monkey. J Pharmacol Exp

Ther 193:676-688, 1975.

Johanson, C.E., and Uhlenhuth, E.H. Drug preference and mood in humans:

d-amphetamine. Psychopharmacology 71:275-279, 1980.

Johanson, C.E., and Uhlenhuth, E.H. Drug preference and mood in humans:

Repeated assessment of d-amphetamine. Pharmacol Biochem Behav

14:159-163, 1981.

Kumor, K.; Sherer, M.; Thompson, L.; Cone, E.; Mahaffey, J; and Jaffe, J.H.

Lack of cardiovascular tolerance during intravenous cocaine infusions in

human volunteers. Life Sci 42:2063-2071, 1988.

Lubinski, D., and Thompson, T. An animal model of the interpersonal

communication of interoceptive (private) states. J Exp Anal Behav 48:1-

15, 1987.

Martin, W.R.; Sloan, J.W.; Sapira, J.D.; and Jasinski, D.R. Physiologic,

subjective and behavioral effects of amphetamine, methamphetamine,

ephedrine, phenmetrazine, and methylphenidate in man. Clin Pharm Ther

12:245-258, 1971.

McNair, D.M.; Lorr, M.; and Droppleman, L.F. Profile of Mood States (manual).

Education and Industrial Testing Service, San Diego, 1971.

Ostfeld, A.; Smith, CM.; and Stotsky, B.A. The systemic use of procaine in the

treatment of the elderly. A review. J Amer Geriatr Soc 25:1-19, 1977.

Paly, O.; Jatlow, P.; Van Dyke, C.; Jeri, F.R.; and Byck, R. Plasma cocaine

concentrations during cocaine paste smoking. Life Sciences 30:731-738,

1982.

Schuster, C.R.; Fischman, M.W.; and Johanson, C.E. Internal stimulus control

and subjective effects of drugs. In: Johanson, C.E. and Thompson, T., eds.

Behavioral Pharmacology of Human Drug Dependence. National Institute

on Drug Abuse Research Monograph No 37. DHHS Pub. No. (ADM) 81-

1137. Washington, D.C.: U.S. Govt. Print. Off., 1981, pp. 116-129.

229
Van Dyke, C.; Jatlow, P.; Ungerer, J.; Barach, P.; and Byck, R. Cocaine and

lidocaine have similar psychological effects after intranasal application.

Life Sc 24:271-274, 1979.

Weeks, J. Experimental morphine addiction: Method for automatic intravenous

injections in unrestrained rats. Science 138:143, 1962.

Woolverton, W.L., and Balster, R.L. Behavioral pharmacology of local

anesthetics: Reinforcing and discriminative stimulus effects. Pharmacol

Biochem Behav 16:491-500, 1982.

Wulfert, E., and Hayes, S.C. Transfer of a conditional ordering response through

conditional equivalence classes. J Exp Anal Behav 50:125-141, 1988.

Zung, W.W.K.; Granturco, D.; Pferffer, E.; Wang, H.S.; Whanger, A.; Bridge, T.

P.; and Potkin, S.G. Pharmacology of depression in the aged: Evaluation

of gerovital-H, as an antidepressant drug. Psychosomatics 15:127-131,

1974.

ACKNOWLEDGMENT

The studies described were supported by grant DA-03818 from the

National Institute on Drug Abuse and grant M01 RR 00035-27 from the

National Institutes of Health.

AUTHOR

Marian W. Fischman, Ph.D.

Associate Professor of Psychiatry

and Behavioral Science

Department of Psychiatry

and Behavioral Sciences

The Johns Hopkins University School of Medicine

600 North Wolfe Street

Baltimore, Maryland 21205

230
CHAPTER 11

Case Reports and the Assessment of

Drug Abuse Liability

Edward C. Senay, M.D

INTRODUCTION

The focus of this paper is on unsolicited, unstructured case reports in

Phase 4 of new drug development. Formal case reports as a part of Phase

2 and 3 are not considered. As far as I am aware, formal case reports in

Phase 2 or 3 have not, to date, incorporated scales for detecting addictive

behavior patterns even simply considered as a category of non-occurrence.

Pocock (1983) speaks of “Phase 4 trials” as “promotion exercises aimed

at bringing a new drug to the attention of a large number of clinicians,

typically in general practice.” Pocock states: “This latter type of inquiry

has limited scientific value and hence should not be considered part of

clinical trial research.” I cannot agree with this position with respect to

potential for abuse liability, a term which I will sometimes use to indicate

both potential for inducing physical dependence and abuse liability, more

narrowly defined. History appears to teach that both science and an

extended non-scientific experience are necessary before we begin to

appreciate the true profile of the abuse liability of a new psychoactive

drug. The basic argument of this paper is that, to date, unsolicited,

unstructured case reports have been the single most important means of

detecting abuse liability.

Case reports in this paper refer to either Phase 4 clinical trials as defined

by Pocock or to the much more important part of Phase 4 - the ordinary

clinical encounter between doctor and patient which is either transmitted

to an authority such as the Food and Drug Administration (FDA) or

perhaps toajoumal. The case report I want to focus on is usually unsolicited

and it is not structured as a formal case report would be in Phase 2 or 3.

The clinicians Phase 4 case report usually does not cover the full range

of possible symptoms as would a structured Phase 2 or 3 report and, in

particular, the clinicians report is often lacking in the category of nonoccurrence.

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Case reports, in Phase 4, are the vehicle for completing the book, so to

speak, on a given drug for it is in this Phase that some drug effects, usually

negative, are appreciated which were not apparent in previous phases of

drug development. The conditions in Phase 4 are natural; no blinds are

utilized; psychological factors related to status of assignment to drug or

placebo are not present and usual clinical conditions prevail. It is also

important to remember that in Phase 4 both clinician and patient usually

believe that the drug is safe as the authorities have placed their imprimatur

on the drug.

Phase 4 experience involves most or all of the relevant cases which might

be appropriate for the drug in question with no artificial testing induced

boundaries and also, as in the use of benzodiazepines for relief of ordinary

life stress, we acquire experience with non-indicated uses. Phase 4 case

reports then are the final detection line for all the potentials of a drug

including indications for which it has been developed and for many,

perhaps, unanticipated indications and problems including abuse liability.

With respect to potential for abuse liability, Phase 4 studies may have to

involve truly enormous numbers of patients before the true profile of a

drug is revealed. The benzodiazepines are the most recent example, for

it was not until these drugs had been used in tens of millions of cases that

their potentials for abuse liability were appreciated. Unsolicited and

unstructured case reports were the vehicle by which these potentials were

first detected. The importance of Phase 4 is underscored by the fact that

after 28 years and use in billions of instances we still do not have a

complete profile of the potential for abuse liability of this class of drugs.

For example, we do not know with scientific certainty that all members

of this class have equal potential for inducing physical dependence

although the preponderance of current evidence indicates that all members

of this class are equal in this respect.

LIMITATION OF CASE REPORTS

After citing the importance of case reports in the long process of

appreciating the abuse liability of a psychoactive drug it is important to

understand that there appears to be a spectrum underlying ordinary clinical

experience. One end of this spectrum is defined by very clear reporting

which is congruent with evidence derived from scientific study. The

other end of this spectrum is defined by reports which are not congruent

with scientific evidence and which appear to have more to do with the

need of people to find some meaning in existence than with pharmacology.

I will start in the middle of this spectrum.

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Any clinician can see only a small fraction of the extant cases of a

given disorder and, therefore, may not see much of the variance

Benzodiazepines were used in millions if not billions of instances

over a period of some twenty years before there was general

recognition in the medical and scientific community of the potential of

these drugs for inducing physical dependence (Marks 1985). If, as

now appears to be an incontrovertible fact, these drugs can induce

physical dependence in ordinary doses for relatively brief periods e.g.,

4 months of daily doses, how could this propensity have gone

unnoticed for close to 20 years of massive use? One factor of probable

relevance is that most clinicians see a variety of patients and, in many

instances, for brief periods of time. Even clinicians, like myself, who

see a narrow spectrum of patients can have only a very limited

exposure to the total group of patients, for whom we provide services.

For example, over a 20 year span I estimate that I have admitted to

treatment an average of ten heroin addicts per week for approximately

4.5 weeks each year. Mathematically, then, I have been exposed to

9,000 patients. If there are 750,000 to one million addicts in the U.S.

alone then I have been exposed to a small fraction of the world’s

heroin addicts. Even groups of clinicians cannot be exposed to

substantial fractions of problems like substance abuse disorders which

have a lifetime prevalence of 15 percent in the entire population of the

U.S. and a somewhat lesser but still substantial prevalence in many

countries in the rest of the world.

Placebo effects: “expectation” and drug fads

“Expectation” and the limits of clinical sensitivity: Clinical observation

is, of course, confounded by a number of factors of which placebo effects

are quite powerful. Beecher cited a figure of 30 percent placebo effect for

the analgesic properties of morphine (Beecher 1955). The average clinician

probably does not appreciate the power of this effect for it is almost

always hidden in ordinary clinical life and the average clinician has other

things to occupy his or her attention. The significant contribution of

“expectation” to variance in opioid withdrawal was demonstrated in a

double blind study we carried out in which complaints of narcotic

withdrawal did not differ between groups of addicts being withdrawn and

a group of addicts not being withdrawn (Senay et al., 1977). “Expectation”

resulted in no differences in complaints but a second factor, namely, rate

of withdrawal caused large differences in behavior as those being

withdrawn at a rapid rate used more heroin and dropped out of the study

at significantly higher rates than groups being withdrawn at slower rates

or not being withdrawn at all. The culture of heroin addiction pays respect

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to the contribution of “expectation” as many addicts will volunteer that

the “headtrip” aspect of withdrawal is important, but neither addicts nor

acute clinical observers would be able to separate out effects on

complaining versus those on behavior. There is a boundary on clinical

sensitivity, and detection of effects beyond that boundary requires scientific

method.

The limits of both clinical sensitivity and scientific method can be seen

in the following. It is a common clinical experience to encounter a patient

who is so frightened of withdrawal from a drug of dependence that their

fear takes on phobic proportions. They are literally unable to think about

participating in a withdrawal program. One usually advises and obtains

consent for a blind detoxification. But the clinician cannot separate

expressions of the phobia about withdrawal from pharmacologically

induced withdrawal effects. Covi et al. (1973) tried to combine scientific

method with an individual case report when he hospitalized a patient who

had taken chlordiazepoxide 45 mg daily for 20 weeks. Under double

blind conditions the chlordiazepoxide was abruptly discontinued, but

Covi could not determine if the resulting syndrome was attributable to

withdrawal, to a return of symptoms for which the patient had originally

been treated or to a phobia about withdrawal.

Drug fads and drug reputations: Another factor which confounds

ordinary clinical experience is that of drug fads - attribution of desirable

effects to a drug which have nothing to do with its pharmacologic effects

or drug reputations - attribution of undesirable effects which again have

nothing to do with the pharmacology of the drug. First, I would like to

examine drugs which are what they are said to be. Methadone, for example,

has long been said by addicts to “get in your bones.” There is no scientific

evidence for such an effect. The most probable explanation is that many

addicts in methadone maintenance treatment in attempting to withdraw

from methadone experience narcotic withdrawal which is moderate to

severe in degree. Bone aches are prominent in these degrees of severity

and are not prominent in mild degrees of withdrawal. “On the street”

many addicts never obtain enough heroin to experience such degrees of

severity of withdrawal, hence the attribution of bone aches to the

methadone. Another illustration of drug reputations was evidenced in the

early work with 1-alpha-acetyl-methadol; patient acceptance of the drug

was trouble free in most centers experimenting with the drug but in one

center the drug was “bad-rapped” and the experimenters could not get

any addicts to accept the drug.

In the late seventies in Chicago the combination of tripelennamine and

pentazocine, so-called “T’s and Blues,” largely replaced heroin in

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confirmed, hard-core heroin addicts (Senay 1985). Rational reasons for

thechangewere: 1) low cost, a “set” of “T’s and Blues” could be purchased

for 5 dollars and a potent dose of heroin cost around 20 dollars and 2)

certainty, with “T’s and Blues” addicts knew that they were going to get

potent drugs; addicts reported that heroin purchases were entirely

unreliable hence the shift to “T’s and Blues.” Fad aspects of the “T’s and

Blues” phenomena were in evidence when many addicts maintained that

intravenous use of “T’s and Blues” would relieve heroin withdrawal. In

the general hospital I have seen more than one heroin addict, who concealed

the fact of his addiction, thrown into severe narcotic withdrawal when he

received pentazocine for post-operative analgesia and so believe that

pentazocine is indeed a potent narcotic antagonist when given to someone

with true physical dependence on opioids. Many addicts in my clinic,

however, steadfastly maintained that “T’s and Blues” would “take their

sick off.” Their “sick” i.e., their withdrawal, was most likely placebo

effect withdrawal of the kind discussed above and would yield to any

intervention in which the addict had strong belief.

The inclusion of a small amount of naloxone in the pentazocine capsule

together with a new shape and color combined to end rather dramatically

the “T’s and Blues” epidemic in Chicago. A few addicts stayed away

from “bananas” or “footballs”, as the new formulation came to be known

on the street, because shooting them led to severe narcotic withdrawal,

but most addicts reported that they gave up on the new form of Talwin

because the new drug didn’t seem to have any intoxicating effect. As one

of them said to me, “footballs don’t have any drive to them.” There were

also fears that the new form of Talwin had destructive effects on sexual

function and that hallucinations were more likely with the new drug.

Probably such fears motivated a return to heroin for some addicts, but the

reports of most of the addicts who had experimented with the new

formulation did not seem to confirm such effects. There were dramatic

changes in the perception of Talwin and as one who witnessed the birth,

growth and death of the T’s and Blues epidemic in Chicago, I believe that

changes in perception were as potent as pharmacologic factors related to

the inclusion of the naloxone in the rapid demise of an epidemic which

had lasted for many years.

Another illustration of placebo or “fad” phenomena is in the epidemic use

of antidepressants among heroin addicts in New York City in the late

seventies. Street lore attributed enhanced intoxicating qualities to the

combination of tricyclic antidepressants and opioids and use to “boost”

intoxication from heroin or methadone became quite frequent. The

following table contains data on methadone maintenance patients and the

drugs they were using (Kaul and Davidow 1981). One notes that use of

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antidepressants as adjunctive drugs was more frequent than use of heroin

in 1977-79 in the methadone maintenance patients studied in New York

City. It is likely that most of these addicts had a choice and elected the

antidepressants in preference to heroin. It is striking that rates of adjunctive

use of tricyclic antidepressants were not far from those obtained for

cocaine. Tricyclic antidepressants are abused in Chicago and in other

communities, but on an occasional basis, and they do not rival the popularity

of heroin or cocaine.

Table 1. Relative incidence of various abused drugs among methadone

patients’ as determined by immunoassay techniques2,3

.

Percent positives

Drugs 1974 1975 1976 1977 1978 1979

Cocaine 7.4 17.6 17.8 19.4 26.3 26.0

Heroin (opiates) 14.2 14.2 10.4 7.9 13.6 13.9

Barbiturates 7.8 8.8 14.6 5.2 10.5 10.0

Amphetamines 4.4 3.2 6.2 5.5 13.2 13.2

Tricyclic

antidepressants ANA ANA ANA 15.4 18.4 19.0

Benzodiazepines ANA ANA ANA 11.2 14.9 17.3

Phencyclidine(PCP) ANA ANA ANA ANA 10.2 10.8

1

 Range of sampling in any given year was from 1,000 to 7,500 random patients

screened.

2

 RIA and EMIT methodology.

3

 ANA = assay not available (developed) at the time.

(Permission to reprint from Kaul & Davidow, 1981 by Marcel Dekker, Inc.)

It is possible that heroin addicts in New York City know something about

the pharmacological interaction between tricyclic antidepressants and

opioids that addicts in other cities do not know but the preponderance of

evidence available at this time suggests a drug fad. Kaul and Davidow

write, “The concurrent use of 2 or more drugs is usually governed by the

need for mood changes required at any given time. Substitution of one

drug of choice for another is not necessarily the trend among drug users.

They will add other drugs to their armamentarium for kicks.”

Next I would like to review drug fads and drug reputations when the drug

believed to be ingested is probably not the drug the taker believes it to be.

In Chicago we witnessed a near epidemic of “THC” or as it was also

called “TAC.” The acronym “THC” was taken from tetrahydrocannabinol. Street usage rapidly made THC into TAC or TIC, and

it was a popular drug with non-heroin drug using youth in Chicago. The

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drug “TAC” sold as “the essence of marijuana” was, of course,

phencyclidine. The usual street report was that TAC gave a marijuana

high but stronger than that associated with the usual street “‘joint.” It is

quite possible that marijuana and phencyclidine have similar intoxicating

properties, particularly at lower doses, but it is equally plausible that

placebo effects accounted for the identification of phencyclidine as

marijuana.

Two examples from the useful end of the spectrum of clinical reporting:

For usual clinical purposes reports from heroin addicts on admission to

treatment are accurate enough to make good estimates on first dose of

methadone; a dose which may differ by 20 to 25 mg depending on the

history. We studied 220 addicts coming into treatment and administered

placebo or 10 mg of methadone and took baseline and 2 hour pupillary

photographs under controlled light conditions (Senay and Schick 1978).

Following a dose of 10 mg of methadone, all normals will have a pupillary

constriction of 1 mm or more and no methadone maintainance patients

taking 30 mg of methadone or more a day will have apupillary constriction

as great as 1 mm. We found that roughly one fourth of the addicts identified

by all the usual criteria, including urines positive for morphine, had

pupillary constrictions of greater than 1 mm indicating that they were

minimally physically dependent, if they were physically dependent at all.

The history could be used to predict those having minimal dependence.

This study is consistent with other studies in which addict populations

were tested with naloxone. Roughly one quarter of the addicts tested in

these studies did not get precipitated withdrawal. Unfortunately these

studies did not match drug use history with outcome of naloxone testing.

The accounts of addicts can give an internally coherent dynamic account

of their addictive behaviors in which drug effects are consistent with

current scientific evidence. In particular, I recall the history of a woman

involved in an accident in which suicidal psychology on the part of this

patient could be excluded by the circumstances of her accident. Without

the accident it is not likely, given her psychology and social conditions,

that she would have ever taken narcotics on any other than a medical basis

and her general psychology and family history suggest that she would not

have become a drug abuser. Her injuries were chronic and necessitated

frequent narcotic administration. Her description of her gradual awareness

that there could be pleasure from these drugs without reference to pain

relief, and the fact that they could also have stress relieving effects, led

her, after a period of years, to begin a pattern of addictive behaviors

involving opioids in response to expectable but still severe life stress. Her

account was consistent with all the data we have and defines the best case

scenario for case reports.

237
The useless, sometimes misleading. end of the spectrum of clinical

reporting: Daily clinical experience supported by the studies described

above did not prepare me for the results of another study we carried out

when addicts in my clinic were reporting high rates of use of diazepam

both to enhance intoxication and for a variety of “therapeutic” purposes

(Senay et al. 1977). These reports occurred before benzodiazepines could

be tested for on a routine basis. I sought and obtained resources for

special testing for benzodiazepines which I carried out, in blind fashion,

on all urines for one month on all patients in my clinic. The results of the

blind testing revealed that the addicts were actually taking propoxyphene,

not diazepam. Griffiths carried out a study in which drug experienced

addicts reported that they preferred benzodiazepines over barbiturates on

the street, but under double blind conditions they consistently chose

barbiturates rather than benzodiazepines (Griffiths et al., 1980).

Studies like these combined with clinical experience with “look alikes”

in which drug users report drug effects of the drug they believe they are

using rather than the effects of the drug they are actually using lead me

to be quite cautious of reports of “street” preferences and actual use of

“adjunctive” drugs.

The confounding effects of multiple drug use: In the course of studying

the “T’s and Blues” epidemic we went out on the street and contacted

drug users not in treatment who alleged that they were using pentazocine.

We purchased the pills they identified as “T’s” from them and also paid

them to give us a urine. The pills we purchased were most frequently

indeed “T’s.” In many of these subjects we identified more than nine

common substances of abuse not counting nicotine. It was clear that they

were taking many drugs whose nature was unknown to them because the

drugs they told us they were using were fewer in number than the number

of drug classes we were detecting.

As our study of the “T’s and Blues” users on the street indicated, multiple

drug use has become the norm. Most admissions to drug treatment in

recent years are using substantial amounts of one or more primary

intoxicants and also are using substantial amounts of secondary drugs.

With high doses of intoxicants such as cocaine base and the newer potent

forms of marijuana it is probable that drug users, frequently, cannot

register how much and what they are using with any degree of accuracy.

Given the foregoing it is difficult to track the abuse liability of any single

drug, new or old, when there are possibilities of drug interactions and

severe cognitive and memory impairments.

238
The confounding effects of psychopathology: Another source of error

in case reports is the difficulty in separating psychopathology from drug

effects. Most intoxicants can produce symptoms and/or syndromes which

can mimic almost any kind of psychopathology. In a given case it may

be impossible to separate depression resulting from chronic drug use

from naturally occuring depression. A classic example is in case reports

of severe withdrawal in which a clinician biased against a given drug

class forgets that stress of any kind usually worsens psychopathology and

that withdrawal from any drug of dependence is a major stress. All the

resulting symptoms are then attributed to the drug without due

consideration of the pre-existing psychopathology and its possible

contribution to variance.

The lack of precise terms and the lack of substance abuse training in

medicine in general makes reporting problematic in manv instances: The

lack of a generally agreed on terminology also presents difficulties.

Diagnostic criteria for abuse and dependence change with each version

of DSM III and it is likely that we will see more changes when DSM IV

comes out in 1990. The clinician is then frequently without clear guidelines

when making diagnoses. Many of the terms we use in the field of substance

abuse are not defined. Intoxication, for example, has no scientific

definition. It would appear that the intoxication from cocaine is different

from intoxication from heroin which is different from intoxication from

alcohol but we have no language to be precise about the differences. It is

a lamentable fact but true that medical training is fifty years behind

developments in the field of substance abuse. This means that most

practitioners are untrained and inexperienced in the field. They are not

in position to observe or to report accurately as a result.

The variance in populations: Individuals value drug effects generally

with some consistency, but there is variation. Most users of pentazocine

and tripelennamine confined their doses to two to three times the ordinary

intoxicating dose because the margin between intoxicating doses and

convulsions with this combination is very narrow. Most users of the

combinations had experienced convulsions and wanted to avoid them

and so limited their doses, but I had a few patients in my clinic who valued

the convulsions and took doses they knew would induce them.

The responses of poly-drug abusers appear to be quite different from

those not given to frequent use of multiple intoxicants, as is illustrated by

the fact that normals prefer placebo to benzodiazepines but poly-drug

abusers find these drugs pleasurable (DeWit et al., 1984). These two

examples illustrate that there can be considerable variance attributable to

persons which appear to have little to do with pharmacology.

239
COMMENT

In this review of case reports in Phase 4 we have seen an underlying

spectrum of possibilities defined on one end by an accurate observer

reporting to an accurate recorder effects which are consonant with the

results of scientific study and which appear to have high reliability and

validity; the other end of the spectrum consists of reports which are not

consonant with science and appear to have no relation to pharmacology

and are either grossly misleading or are simply valueless. This review

also suggests that despite the many drawbacks of case reports in Phase 4

that they have functioned as the detection device for almost all abuse

liability problems. The application of the “human testing” technology

reviewed in this symposium promises to make less important the role of

case reports and, hopefully, to make them of purely historical interest in

the not too distant future.

REFERENCES

Beecher, H.K. Appraisal of drugs intended to alter subjective responses, symptoms.

J Amer Med Assoc, 158:399-401, 1955.

Covi, L.; Lipman, R.S.; Pattison, J.H.; Derogatis, L.; and Uhlenhuth, E.H. Length of

treatment with anxiolytic sedatives and response to their sudden withdrawal.

Acta Psychiat Scan 49:51-64, 1973.

deWit, H.; Johanson, C.E.; and Uhlenhuth, E.H. The dependence potential of

benzodiazepines. Curr Med Res Opin 8:48-59, 1984.

Griffiths, R.R; Bigelow. G.E.; Liebson, I.; and Kaliskak, J.E. Drug preference in

humans: Double-blind choice comparison of pentobarbital, diazepam and

placebo. J Pharmacol Exp Ther 215(3):649-661, 1980.

Kaul, B., and Davidow, B. Drug abuse patterns of patients on methadone treatment

in New York City. Am J Alc Abuse 8(1):17-25, 1981.

Marks, J. The Benzodiazepines, Lancaster, England: MTP Press Limited, 1985.

Pocock, S.J. Clinical Trials. New York: John Wiley and Sons, 1983.

Senay, EC. Clinical experience with T’s and B’s Drug Alc Dep 14:305, 1985.

Senay,E.C.; Harvey,W.H.; Oss, J.N.; Turk,R.F.; and Ginther, M.E. Adjunctive drug

use by methadone patients. Am J Drug Alc Abuse 4(4):533-541, 1977.

Senay, EC., and Shick, J.F.E. Pupillary response to methadone challenge: Aid to

diagnosis of opioid dependence. J Drug Alc Dep 3:133-138, 1978.

AUTHOR

Edward C. Senay, M.D.

Professor, Department of Psychiatry

The University of Chicago

Box 411

5841 South Maryland Avenue

Chicago, Illinois 60637

240
CHAPTER 12

United States Epidemiologic Data on Drug Use and

Abuse: How are They Relevant to Testing Abuse

Liability of Drugs?

James C. Anthony, Ph.D.

Alison M. Trinkoff, Sc.D.

INTRODUCTION

Jaffe and Jaffe (this volume) have proposed that laboratory research on

subjective drug effects has passed into adulthood after a tumultuous

adolescence. By contrast, epidemiologic work on comparative testing

for psychoactive drug self-administration and drug hazards is much less

advanced, if we rely on a similar scale of progress.

In this paper we outline some directions of epidemiologic work that grow

toward a capacity for comparative drug testing. However, major obstacles

remain, and three will be stressed. First, the abuse liability concept may

not serve well in the epidemiologic context where manifestations of drugtaking and drug hazards are heterogeneous, and where uncontrolled

determinants are multiple. Second, in studies of medicine hazards, we

often can rely on the hazardsoccuningatrandomwithrespecttoindications

for medicine use or other antecedent conditions. As we shall see, this

probably is not the case for many psychoactive medicines. In this context,

the indications for medicine use (e.g., depressed mood) often are associated

with occurrence of drug hazards (e.g., suicide by overdose). As a result,

it sometimes will be necessary to exchange the usual observational

strategies of epidemiology for random allocation designs in medical

practice settings, if we hope to get good answers to questions about

relative drug hazards.

A third major obstacle to progress concerns the nature and quality of the

surveillance data. The epidemiologic data now available for comparative

testing of controlled substances in the United States are gathered mainly

by routine surveillance systems not oriented specifically to this task. The

241
resulting surveillance data sometimes can be put to good use, as we shall

see, but not necessarily to good use in comparative drug testing.

UNPACKING ABUSE LIABILITY

Abuse liability and abuse potential are rich concepts densely packed with

meaning. These concepts remain difficult, even if abuse liability is divided

into liability for abuse and liability of abuse, an intuitively appealing

approach proposed for behavioral pharmacology (Griffiths et al., 1986;

Roache and Griffiths this volume).

As defined, the liability for abuse associated with a drug refers to drugtaking with a socially unacceptable purpose. Liability for abuse

encompasses initial self-administration of a drug outside the scope of

medical authority, or more than was prescribed; repeat self-administration;

a single episode of emptying the medicine cabinet and ingesting all of its

contents in order to commit suicide; and so on. To be sure, there may be

a single theme underlying all of these behaviors: one latent trait or class

may be the model that fits the data best. Nonetheless, until alternative

models are tested, it seems plausible that the drug-taking behaviors

encompassed by liability for abuse are quite heterogeneous, too

heterogeneous for the goal of comparative drug testing in an epidemiologic

context.

In contrast, a drug’s liability of abuse has been defined in relation to the

hazards of psychoactive drug use. The heterogeneity of drug hazards

may be self-evident, but it may be helpful to show a set of illustrations that

involve users of heroin, marijuana, and cocaine.

These illustrations are based on analyses of data from the National Institute

of Mental Health Epidemiologic Catchment Area (ECA) Program. The

ECA program was a five-site collaborative study in the United States,

involving probability samples of area residents age 18 years and older in

New Haven, Baltimore, St. Louis, Durham, and Los Angeles. In all,

20,862 subjects were interviewed for this study between 1980 and 1984,

representing about 75 percent of the sampled respondents.

In the general ECA survey design, the Diagnostic Interview Schedule

(DIS) was administered by trained lay interviewers at baseline and again

atfollowup approximately one year later. About 80 percent of the baseline

respondents participated at followup. Details of this study are published

elsewhere (Eaton and Kessler 1985; Regier et al., 1988; Eaton et al., in

press, a).

242
The DIS included a standardized battery of interview items to assess drug

use by self-report, as well as self-reported consequences of drug use.

Each of these interview items was written to correspond with a diagnostic

criterion for drug abuse-dependence syndromes defined in the Diagnostic

and Statistical Manual of Mental Disorders, third edition (DSM-III) (APA

1980; Anthony and Helzer, in press, a). Responses to these items and to

the items that concern other psychiatric syndromes and mental disorders

were analyzed by computer, which yielded computer-based diagnoses

(Robins et al., 1985).

In the ECA Program generally, no psychiatrists or clinical personnel

examined the subjects or the individual data gathered by the DIS

interviewers. However, the DIS was intended to make diagnoses

comparable to those produced by a psychiatrist. Initial results on this

count were promising, especially for DSM-III drug abuse-dependence

and alcohol abuse-dependence categories (Robins et al., 1981).

Community studies have been somewhat less promising (Anthony et al.,

1985; Helzer et al., 1985; Shrout et al., 1987).

Table 1 shows the pattern of consequences of drug use reported by ECA

respondents, in relation to level of drug involvement for a comparison of

marijuana, cocaine, and heroin users. The DIS distinguishes daily users

from those who used a drug on six or more occasions, but it does not yield

drug-specific data on lower levels of use. For this reason, in most ECA

publications and in this paper, a drug user generally is defined as one who

has used a drug on six or more occasions. This eliminates so-called

“purely experimental” users, with some unknown influence on

relationships to drug hazards.

Among the ECA participants, there were 297 who identified themselves

as having used heroin on a daily basis for 2 weeks or more, and there were

123 who reported heroin use on more than five occasions, but never daily

for 2 weeks or more. Many of the daily drug users in the ECA samples

were adult residents in correctional facilities and drug treatment programs,

selected for study by probability sampling, not by self-selection or

convenience sampling. Since the probability of selecting institutional

residents greatly exceeded the probability of selecting residents of

households, epidemiologic estimates for the total household and

institutional population depend upon sample weighting procedures and

adjustments for non-participation (Eaton and Kessler 1985; Regier et al.,

1988). The weighting procedures can be used to give site-specific estimates

as well as estimates based on pooled data. To aid the reader, we have not

presented site-specific estimates in this paper. The site-specific estimates

generally reflect the trends and tendencies shown in the pooled estimates

given in table 1.

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Table 1. Consequences of drug use reported by identified users of heroin,

cocaine, and marijuana.

Number of users. bv level:

—Sustained daily users

—Never daily users

Percent of users

Who felt dependent

—Sustained daily users1

—Never daily users

Who had withdrawal sickness

—Sustained daily users

—Never daily users

Who needed larger amounts

—Sustained daily users

—Never daily users

Who failed to reduce use

—Sustained daily users

—Never daily users

With social problems

attributed to drug use

—Sustained daily users

—Never daily users

With psychological problems

attributed to drug use

—Sustained daily users

—Never daily users

With other health problems

attributed to drug use

—Sustained daily users

—Never daily users

HEROIN COCAINE MARIJUANA

USERS USERS USERS

Note: Data from the NIMH Epidemiologic Catchment Area surveys in New

Haven, Baltimore, St. Louis, Durham, and Los Angeles, 1980-84.

1

 These are estimates produced by pooling and weighting the sample to

compensate for selection probabilities and non-response. Values for “never

daily” users are based on four sites; the New Haven survey identified daily users

only. Values in parentheses are standard error estimates (percent), * = <0.01.

244
As table 1 shows, after pooling the data from all five ECA sites and after

taking probability of subject selection into account, an estimated 71.2

percent of the daily heroin users reported having felt dependent on heroin.

By comparison, an estimated 8.9 percent of the never daily users reported

having had feelings of dependence on heroin. This difference in

percentages from about 9 to 71 percent is consistent with presumed toxicity

of nondaily heroin use versus daily heroin use.

Before proceeding, it is important to draw attention to the nature of the

statistical measure being reported here. This measure is an estimated

lifetime prevalence proportion based on ECA data. For example, 71

percent of daily heroin users reported having felt dependent on heroin.

This was derived by estimating the number of identified daily heroin

users who felt dependent, divided by the estimated total number of daily

heroin users at the time of the survey. Based on cross-sectional survey

data, the lifetime prevalence values represent crude approximations of

more standard and informative epidemiologic measures such as the

cumulative incidence and incidence density, defined elsewhere (e.g.,

Rothman 1986). Nevertheless, in the absence of prospective studies the

lifetime prevalence proportions given here are now the best available

estimates for cumulative incidence proportions.

Summarized below, there also were differences in percent reporting

consequences across two levels of heroin involvement uniformly held up

for cocaine use and marijuana use. Further, with one exception, subjects

reporting heroin use were more likely to report drug-related adversity

than the cocaine users. In general, subjects reporting cocaine use were

more likely to report adversities than marijuana users.

Among the 300 ECA subjects who identified themselves as having used

cocaine on a daily basis for 2 weeks or more, an estimated 23.6 percent

reported having felt dependent on cocaine; the corresponding estimate

for 749 “never daily” cocaine users was 2.2 percent. Among the 1394

ECA subjects who identified themselves as having used marijuana on a

daily basis for two weeks or more, an estimated 17.2 percent reported

having felt dependent on marijuana, while an estimated 1.3 percent of the

1863 “never daily” marijuana users reported having felt dependent.

The findings on withdrawal symptoms reported by heroin and cocaine

users were virtually identical to those for self-reported feelings of

dependence, but this was not the case for the marijuana users. Among the

daily marijuana users, only 2.9 percent reported having felt sick due to

245
stopping or cutting down on marijuana use. The corresponding estimate

for the “never daily” marijuana users was 0.2 percent.

The DIS assessed drug tolerance by means of the following interview

question, “Did you find that you needed larger amounts of these drugs to

get an effect—or that you could no longer get. high on the amount you

used to use?” An estimated two-thirds of the daily heroin users, 43

percent of the daily cocaine users, and 21 percent of the daily marijuana

users reported this experience. The never daily users were about onesixth as likely to describe themselves as having needed larger amounts.

Another DIS interview question on drug dependence sought reports about

failed attempts to stop or cut down on drug use. It is noteworthy that only

40 percent of the daily heroin users reported this experience with heroin,

as compared to 14.4 percent of the daily cocaine users and 8.4 percent of

the daily marijuana users. Failed attempts to cut back were reported by

3.4 percent of the never daily heroin users, 2.4 percent of the never daily

cocaine users, and 1.1 percent of the never daily marijuana users.

To address socially maladaptive behavior that might follow from drug

use, the DIS posed questions about drug-related problems with the police,

on the job, or involving family and friends. An estimated 58.4 percent of

daily heroin users reported these problems, as did one-half as many daily

cocaine users (27.6 percent), and roughly one-third as many daily

marijuana users (17 percent). Whereas three to four percent of the never

daily cocaine users and marijuana users reported social problems, an

estimated 13.8 percent of never daily heroin users reported social

difficulties related to heroin use.

In response to DIS questions on psychological or emotional troubles due

to drug use, daily heroin users and daily cocaine users were five times

more likely to report these problems as compared to corresponding never

daily users. The difference across levels of marijuana involvement was

not so steep: an estimated 20.6 percent of the daily marijuana users reported

psychological problems due to marijuana use as compared to an estimated

9.6 percent of the never daily marijuana users.

Other health problems due to drug use (e.g., a persistent cough, overdose,

convulsions) were reported by 24.2 percent of the daily heroin users and

14.5 percent of the never daily heroin users. These health problems were

reported by 10 percent of the daily cocaine users, but virtually none (0.8

percent) of the never daily users. Fewer than five percent of the daily

marijuana users and only 1.9 percent of the never daily marijuana users

reported other health problems due to marijuana use.

246
Table 2 extends the illustration of heterogeneity among drug hazards to

other classes of controlled substances and to other potential hazards and

consequences of drug use, including the proportion who had become

daily users and the proportion who had become cases of DIS/DSM-III

drug abuse-dependence syndromes. In studying this profile it may be

useful to take heroin as a reference for comparison. Unfortunately, the

DIS did not capture, in usable form, any distinctions between drug

compounds within the groups shown here. This is a general weakness in

current drug abuse interview survey methods, one that limits a capacity

for comparative drug testing.

Based on pooled and weighted estimates from the ECA household and

institutional samples, an estimated 40 percent of heroin users reported

having used heroin for 2 weeks or longer. By comparison, an estimated

14 percent of cocaine users and 33 percent of marijuana users identified

themselves as having a history of sustained daily use. Corresponding

estimates for other psychostimulants besides cocaine, for the anxiolytics

assigned to federal schedules, for other sedative-hypnotics, and for

hallucinogens were 25 percent, 18 percent, 18 percent, and 10 percent,

respectively, as shown in table 2. Thus, despite the presumed greater

mortality of heroin users, these data suggest that a larger proportion of

heroin users had become daily users as compared to users of the other

drugs. However, it is notable that the observed rank-ordering of heroin,

cocaine, and marijuana did not follow the ordering from laboratory studies

of drug self-administration described by others. This draws attention to

conditions such as relative availability of marijuana as compared to other

drugs, which clearly can affect repeated drug self- administration outside

the laboratory, perhaps more than any inherent reinforcing properties of

these drugs.

An estimated 44 percent of the identified heroin users qualified as current

or former cases of DIS/DSM-III opioid abuse and/or opioid dependence.

By comparison, about one-fifth of the identified marijuana users qualified

as current or former cases of DIS/DSM-III cannabis abuse and/or cannabis

dependence. Similar estimates were obtained for users of psychostimulants

besides cocaine, for scheduled anxiolytics, and for other sedative- hypnotic

drugs.

One item of note is the low value for the DIS diagnosis of cocaine abuse

(3 percent). This seems to be due in part to an idiosyncracy in the DSMIII and also in the DIS computer algorithm, subsequently revised in DSMIIIR but not yet implemented in the DIS. Another factor contributing to

the low values observed for both cocaine and the hallucinogens is that

DSM-III defined no dependence category for users of these drugs.

247
Table 2. Characteristics of identified drug users, by drug group.

Note: Data from NIMH Epidemiologic Catchment Area surveys in Baltimore., St. Louis, Durham, & Los Angeles, 1980-84

All estimates, except those in the last column, were produced by applying sample weighting procedures and by

compensating for survey non-response at the local level. Approximate standard errors ranged from one percent (marijuana

estimates) to five percent (heroin estimates), but typically were close to two percent. The number of drug users identified in

the four ECA samples is shown within parentheses associated with each drug group. The New Haven site is not represented

in this table, and the St. Louis site is not represented in the estimates concerning current and recent users -- the necessary

interview items were not included in the surveys there.
Up to this point, these ECA estimates have dealt with the lifetime history

of specific drug hazards, such as feeling dependent, having social problems,

becoming a daily user, or becoming a case of drug abuse or dependence.

Table 2 also shows estimates for the proportion of current drug users, who

were current users with current use defined as use within the one month

prior to the survey. These estimates indicate that current marijuana use

was characteristic of about one-half of those who identified themselves

as having used marijuana on more than five occasions. About one-third

of the identified cocaine users were current users. Estimated values for

the other drug groups ranged from 9 percent (hallucinogens) to 18 percent

(psychostimulants other than cocaine).

The last column of table 2 shows data from ECA followup interviews

conducted one year after the initial survey. The estimates are based on

the subjects who identified themselves as having used specific drugs

within one year of the initial survey, and who were interviewed atfollowup.

Each drug-specific estimate in the column is the unweighted proportion

of these subjects who reported they still were using at the time of followup.

According to the DIS, and subject to limitations of the followup method,

marijuana users identified in the initial interview were most likely to be

using one year later: 43 percent of them reported using marijuana within

two weeks prior to the followup interview. About one-half as many

cocaine users (23 percent) still were using cocaine one year after the

initial interview. The corresponding estimate for heroin users was 18

percent. Estimates for the other drug groups ranged from 5 percent

(hallucinogens) to 12 percent (sedative-hypnotics other than scheduled

anxiolytics).

The foregoing data serve to illustrate the heterogeneity of consequences

and hazards of drug use in the epidemiologic context, and by extension

the multiple determinants of these drug hazards, including conditions

such as drug availability. Nevertheless, there is something inherently

dissatisfying when analysis of drug consequences is limited to the domain

of drug-related behavior and to self-reported and self-attributed

consequences of drug use. One reason for dissatisfaction is uncertainty

about drug users’ capacity to know and to report the consequences of drug

use (Anthony and Petronis, in press, b, c). Another problem is that both

drug use and these drug consequences have been measured with selfreport interview techniques. To some extent, this similarity of methods

artificially elevates the degree of association between drug use and

suspected consequences.

For this reason, we have extended the range of consequences to specific

categories of psychiatric disorders, though there still is a problem of

249
shared methods co-variation. The psychiatric disorders were assessed by

the DIS, as was the syndrome of drug abuse-dependence. However,

neither the interviewers nor the respondents were aware that these

associations would be tested.

Because we sampled residents of prisons, mental hospitals, and alcohol

or drug treatment programs, we have developed separate estimates for the

various sample segments, including the household segment. This allows

us to depict a frequently neglected potential bias of clinical and convenience

samples of drug abusers. To control for age and sex as potential

confounding variables, this analysis has been restricted to males 18-44

years old.

Table 3 gives the number of 18-44 year old male participants sampled

from correctional facilities; from psychiatric, alcohol, and other drug

treatment facilities; and from households. Table 3 also shows that an

estimated 58 percent of the correctional inmates, 38 percent of the treatment

facility residents, and 12.3 percent of the household residents were current

or former cases of DIS/DSM-III abuse and/or dependence involving

controlled substances. (Alcohol abuse-dependence was not counted in

these estimates.)

The estimated lifetime prevalence of DIS/DSM-III antisocial personality

disorder (ASP) among correctional inmates with a history of drug abusedependence was 55 percent. Corresponding estimates for cases of drug

abuse-dependence found in treatment facilities and in the household

population were 58 percent and 37 percent. By comparison, the ASP

lifetime prevalence estimate was only 10 percent for household residents

not qualifying as current or former cases of DIS/DSM-III drug abusedependence. As indexed by the ratio of lifetime prevalence estimates for

persons with and without a history of drug abuse-dependence, there was

an association between drug abuse-dependence and ASP, consistent with

prior research on males summarized elsewhere (e.g.,Robins 1978; Kellam

et al., 1983; Anthony 1985; Robins and Przybeck 1985). These data on

ASP and drug abuse-dependence illustrate how studies of suspected causal

associations based solely on drug abuse-dependence cases located in

correctional facilities or in clinical samples might yield biased estimates,

as compared with those based on total population samples. The ASP

lifetime prevalence ratio of 0.38 to 0.10 based on the total sample was 3.8.

Corresponding ratios based on correctional inmates (0.55:0.10) and cases

in treatment (0.58:0.10) were larger, 5.5 and 5.8, respectively.

Whether these ratios of lifetime prevalence proportions accurately reflect

a causal association between ASP and drug abuse-dependence cannot be

250
Table 3. Estimated lifetime prevalence proportion for selected DIS/DSM-III mental

disorder categories among males 18-44 years of age, by place of residence,

and in relation to DIS/DSM-III abuse-dependence syndromes involving

controlled psychoactive drugs.

PLACE OF RESIDENCE:

Psychiatric,

drug, and

alcohol All

Correctional Treatment Sample

Facilities Facilities Households Segments

Number of subjects sampled: 550 131 3755 4436

Estimated lifetime prevalence of

pychoactive drug abuse-dependence 58% 38% 12.3% 12.5%

Estimated lifetime prevalence (%) of

Antisocial personality disorder

- Among cases of drug

abuse-dependence

- Among those with no

abuse-dependence

Estimated lifetime prevalence (%) of

Major depression

- Among cases of drug

abuse-dependence

- Among those with no

abuse-dependence

55

*

19

*

58

*

32

*

37 38

10 1 0

14 1 4

4 4

Estimated lifetime prevalence (%) of

Panic disorder

- Among cases of drug

abuse-dependence 4.3 7.4 3.1 3.2

- Among those with no

abuse-dependence * * 0.9 0.9

Note: Data from the NIMH Epidemiologic Catchment Area surveys in New

Haven, Baltimore, St. Louis, Durham, and Los Angeles, 1980-84.

All estimates weighted and adjusted for survey non-response at the local level.

* indicates “not estimated.”

METHODOLOGICCOMMENT: It is notable that the prevalence estimates based

on the household segment of the survey sample were not too distant from those based

on all sample segments (shown in the last column of the table). This is a reflection

of the relatively small proportion of younger adult males living in institutions and

group quarters, as compared to the much larger proportion living in households.

251
answered here. Analyses of lifetime prevalence data typically cannot

distinguish temporal antecedents from temporal successors. There is an

association here, with history of ASP being more common among drug

abuse-dependence cases, but the analysis cannot determine which disorder

came first. Moreover, the problem cannot be solved by asking for age of

onset of each disorder, unless the disorder has an abrupt onset (Robins

and Przybeck 1985; Anthony and Helzer, in press, a). For disorders such

as major depression, antisocial personality disorder, and drug abusedependence syndromes, the onset typically is insidious, not abrupt. Cases

may be able to specify events such as first drug-taking or first suicide

attempt, but these events do not necessarily signal onset of the disorder.

The other estimates shown in table 3 point toward possible associations

of drug abuse-dependence with major depression and panic disorder, for

example, as indexed by taking the ratio of lifetime prevalence values.

The comparison of ratios across sample segments, taking the household

estimate for persons without drug abuse-dependence as an expected value,

again shows how clinical samples might lead to upwardly biased estimates

of association between drug abuse-dependence and psychiatric conditions.

Epidemiologic evidence on possible associations of drug abusedependence syndromes with DIS/DSM-III major depression and panic

disorder complements and extends prior clinical case reports and studies

of clinical samples (Anthony and Petronis, in press, c). On one hand, in

considering the ECA data, there is some basis for concern because the

DIS diagnoses were not made by experienced clinicians. On the other

hand, use of the DIS method precluded any influence of diagnostic

suspicion bias, workup bias, or related biases that are difficult to control

when clinicians must assess psychiatric disorders among drug users (Senay,

this volume).

Table 4 provides an analysis of psychiatric disorder status in relation to

ordered levels of involvement with marijuana, heroin, and cocaine, based

on males and females 18-44 years old in the ECA sample. Users who

qualified for the DIS abuse-dependence diagnosis were considered to be

most involved. In reverse order of involvement, those with sustained

daily use but no diagnosis were next, followed by the other two groups

of users. The trends observed for both sexes were generally comparable

to those observed for males and females separately.

With all the strengths and limitations of these cross-sectional and lifetime

prevalence data, the results generally point toward predicted trends

252
Table 4. Suspected hazards of drug use among 18-44 year olds, by level of drug

involvement: DIS/DSM-III Major Depression, DIS/DSM-III Panic

Disorder, and use of emergency room services for problems with alcohol,

other drugs, or mental health (ADM).

A. Number of 18-44 year old subjects in each group1

Cocaine Mariiuana Heroin

Level of Drug Involvement

Used 0-5 times 8665 6483 9233

Used >5 times, never daily 713 1597 89

Used daily: two weeks or more 209 779 16

Qualified for DSM drug disorder 98 837 347

B. Percent found to be current or former Major Depression cases2

Cocaine Marijuana Heroin

Level of Drug Involvement

Used 0-5 times 7.6 (*) 6.7 (*) 7.8 (*)

Used >5 times, never daily 11.0 (2) 8.0 (*) 6.7 (4)

Used daily: two weeks or more 14.6 (4) 13.2 (2) 17.4 (16)

Qualified for drug diagnosis 25.8 (10) 15.3 (2) 23.0 (5)

C. Percent found to be current or former Panic Disorder cases2

Cocaine Marijuana Heroin

Level of Drug Involvement

Used 0-5 times 1.7 (*) 1.7 (*) 1.7 (*)

Used >5 times, never daily 2.4 (*) 1.7 (*) 3.9 (3)

Used daily: two weeks or more 2.3 (2) 1.8 (*) 16.9 (16)

Qualified for drug diagnosis 15.3 (8) 3.2 (*) 9.2 (4)

D. Percent reporting visit to emergency room for ADM problem2

Cocaine Marijuana Heroin

Level of Drug Involvement

Used 0-5 times 3.4 (*) 3.2 (*) 3.7 (*)

Used >5 times, never daily 5.5 (1) 2.7 (*) 13.1(6)

Used daily: two weeks or more 2.3 (5) 8.0 (2) 0.1 (2)

Qualified for drug diagnosis 25.2 (11) 9.1 (2) 12.9 (5)

Note: Data from NIMH Epidemiologic Catchment Area surveys in New

Haven, Baltimore, St. Louis, Durham, and Los Angeles, 1980-84.

1

 Some analyses based on slightly smaller numbers, due to missing values on

some variables.

2

 Approximate standard errors are (percent) within parentheses (*= <1.0)

253
involving cocaine and, to a somewhat lesser extent, marijuana and heroin

as well. For example, an estimated 7.6 percent of the 18-44 year olds with

fewer than six occasions of cocaine use qualified for the DIS/DSM-III

diagnosis of major depression. At the other extreme of involvement with

cocaine, 25.8 percent of the DIS/DSM-III cocaine abuse cases qualified

for the major depression diagnosis. Estimated lifetime prevalence values

for other levels of cocaine use were intermediate. Corresponding estimates

for levels of marijuana involvement were lower than those for cocaine,

but a roughly similar trendemerged. Arelatedtrend, with some irregularity,

also was present in estimates for levels of heroin involvement.

Table 4 shows a somewhat different pattern of association in relation to

DIS/DSM-III panic disorder. It was the DIS/DSM-III cocaine abuse

cases who were most likely to qualify for the panic disorder diagnosis

(15.3 percent), but the lifetime prevalence of panic disorder was under 3

percent for the other levels of cocaine involvement. Low panic disorder

prevalence values also were characteristic of the lower levels of marijuana

involvement, while 3.2 percent of the DIS/DSM-III cannabis abusedependence cases qualified for the panic disorder diagnosis. The panic

disorder prevalence values also tended to increase in relation to heroin

involvement. (The value for daily heroin users who did not qualify for

opioid abuse or dependence may be understood in relation to the small

number of daily users in this group; the standard error was large.)

Data presented in table 4 also describe an aspect of health services

utilization by level of involvement with marijuana, cocaine, and heroin.

As table 4 shows, some 12 to 25 percent of the cocaine and heroin abuse

or dependence cases had received emergency room care for alcohol,

drug, emotional, or mental problems, as compared to 9.1 percent of the

marijuana cases. For marijuana and cocaine, there was a trend for

increasing likelihood of having received such care with increasing level

of drug involvement. For heroin, this trend was not regular, due to a low

value for daily heroin users who did not qualify for the DIS/DSM-III

opioid abuse-dependence.

The purpose of this set of illustrations was to clarify the heterogeneity of

the hazards encompassed by liability of abuse in the context of

epidemiology. The illustrations also clarify how epidemiologic evidence

can become more important in comparative drug testing, provided the

epidemiologic strategies and methods are strengthened. For example, the

DIS assessment of drug use was limited. In future work, the assessment

of specific marketed drug products can be expanded to include use of

color pill charts pioneered by Balter and his colleagues in research on

254
psychotherapeutic medicines (Parry et al., 1971), possibly to include

testing of biological samples for corroboration of reported use. These

methods have been used in some drug abuse surveys, but with no attempt

to capture detailed information about specific drug compounds beyond

lifetime history of use or recent use.

Another important effort will be to clarify the temporal sequence between

drug use and occurrence of psychiatric disorders. This is an issue that is

left unresolved in analysis of lifetime data of the type gathered in the ECA

interviews.

To conclude this section of the paper, we reiterate our suggestion that

hazards of drug use, drug-seeking, and drug-taking likely are too

heterogeneous to be grouped under the proposed rubrics of liability for

abuse and liability of abuse. It may be possible to test the two-group

model empirically, using latent variable analyses of a type already used

to study psychiatric syndromes (Blazer et al., 1988; Eaton et al., in press,

b). In the interim, it may be most useful to unpack the abstract concepts

and discard the terminological baggage once they have been emptied of

meaning. The terms “liability” and “potential” conjure up an attribution

of influence to the drug, without balancing the relative influences of drug,

host, and environment. Even if the two-group model were to fit the data

as well or better than any other, this attribution problem provides a basis

for changing the terminology.

CONFOUNDING

In table 5, we introduce the problem of confounding with an example of

a within-drug comparison concerning the relative hazard associated with

three routes of administering cocaine. In data from the 1985 Drug Abuse

Warning Network (DAWN), about 13,500 drug episodes involving

cocaine were reported by emergency rooms in the network. Of these, 39

percent had a mention of cocaine taken by injection. The next highest

proportion corresponded to the inhalation route (U.S. 1986a).

The large value associated with injection was expected, based on a credible

and well-founded suspicion that cocaine use by injection is more hazardous

than other routes of administration. Exploring this hypothesis more

thoroughly required some information about the population of cocaine

users not admitted for emergency room care. There was no need for an

absolute number, but it was necessary to have some idea of the proportion

of users who inject on any given day. Preferably this estimate would

come from the cities where DAWN facilities are located.

255
Table 5. Is injecting cocaine associated with increased risk of

becoming an emergency casualty?

Drug Abuse2 National 3,4 National

Warning Household Survey of Drug

Network Drug Treatment

Emergency Survey Programs

Rooms. 1985 1985 1985.

Number and percent

distribution of cocaine

users by method of

cocaine administration:

Approximate no. of users: 13,501 1,000 13,000

Percent with:

Cocaine use by injection 39% 8% 20%

Cocaine use by inhalation* 35 95 52

Cocaine use by smoking 10 21 26

Unknown or other methods 16 12 0

Note: Data from the Drug Abuse Warning Network, the National Household

Survey on Drug Abuse, and a national survey of clients admitted to drug treatment

programs, United States, 1985.

1

 Inhalation by nose or mouth, except by smoking.

2

 The Drug Abuse Warning Network is an event-based reporting system. The

approximate number of users is based on the number of drug mentions.

3

The household survey allowed multiple responses to the interview question on

which routes of administration had been used. In contrast, the DAWN is concerned

with the method of administration proximal to admission to the emergency room, and

the survey of clients in drug treatment programs is concerned with methods of

administration at the time of admission to the program.

4

The method described by Finney (1980) was used to estimate the degree to

which cocaine injectors are at increased risk of becoming a DAWN emergency

room casualty. The text mentions risk ratio estimates derived by the following

calculations:

With expected value from survey of household residents:

(13501*0.39*0.92)/(13501*0.61*0.08) = 7.3.

With expected value from survey of clients in treatment:

(13501*0.39*0.80)/(13501*0.61*0.20) = 2.6.

256
The closest available estimate for cocaine users as a group was based on

aquestion in the 1985 national household drug survey which askedcocaine

users if they ever had injected cocaine. Eight percent of users said they

had (U.S. 1987a). This clearly is an underestimate relative to the actual

frequency of cocaine injection among persons using cocaine on any given

day, but it suggested a fairly strong degree of association between injecting

cocaine and being admitted to an emergency room. This can be appreciated

by thinking of the 8 percent value from the national household survey as

an expected value against which to compare the 39 percent value from

DAWN. Using Finney’s method (Finney 1980), the risk of becoming an

emergency room casualty among those who inject cocaine was an

estimated seven times greater than the risk among non-injecting users

(table 5).

There are several defects in this estimate. One defect that could be looked

into is the possibility that the 8 percent expected value was inaccurately

low. To check this possibility, we obtained data on 13,000 clients admitted

to drug abuse treatment facilities in 1985, who had cocaine as the primary

drug of abuse. In this group, 20 percent reported that they were cocaine

injectors at the time of admission (U.S. 1987a). Using this estimate for

the expected value and applying Finney’s method, we estimated that the

risk of becoming an emergency room casualty among cocaine users who

inject was 2.6 times greater than the corresponding risk among noninjecting cocaine users (table 5).

This result may mean that injecting cocaine accounts for the increased

risk. Nonetheless, despite plausibility of the inference, alternative

explanations are possible. The main obstacle to inference is absence of

control over confounding variables, such as concurrent heroin use. Heroin

users are more likely to inject cocaine, and in addition heroin use seems

to be associated with increased risk of being admitted to the emergency

room (table 4).

We also have noted that an increasing proportion of DAWN reports

mention cocaine smoking. This increase may be an indication that smoking

crack cocaine is an especially hazardous drug use pattern, or it may be that

the increase seen in DAWN data simply reflects the increased frequency

of crackcocaine use in the general population. This open question deserves

futher study.

Table 6 illustrates the confounding problem, using DAWN data on the

benzodiazepines, with an adjustment based on market share estimated for

each drug. Here, the number of DAWN emergency room reports

257
Table 6. Indices of the population’s experience with specific

benzodiazepine drugs in 1985.

RX1 No. of DAWN

Market Emergency No. of

Share Room (ER) ER:RX2 DAWN Death:RX3

(Millions) Episodes Ratio Deaths Ratio

Diazepam 23

Alprazolam 11

Lorazepam 10

Flurazepam 8

Triazolam 7

Chlorazepate 7

Chlordiazepoxide 6

Temazepam 5

Oxazepam 2

Prazepam 2

7653 333 317

3403 309 32

1450 145 <10

1517 190 40

1390 199 26

893 128 <10

1360 227 43

844 169 13

211 106 <10

274 137 <10

13.8

2.9

*

5.0

3.7

*

7.2

2.6

*

*

Note: Data from reports compiled for the Drug Abuse Warning Network,

United States, 1985.

1 The prescription market share (RX) refers to millions of prescriptions in a

period of time roughly corresponding to the 1985 period of DAWN reports.

2

The ER:RX Ratio is the number of DAWN emergency room episodes per

million prescriptions.

3

The Death:RX Ratio is the number of DAWN deaths reported by medical

examiners per million prescriptions. (* indicates that the ratio was not estimated

due to the small number of reported deaths.)

mentioning each of 10 benzodiazepines in 1985 and the corresponding

number of Medical Examiner events (deaths) were related to the number

of prescriptions for these drugs issued during a roughly comparable period

of time. Estimates for the number of prescriptions were based on market

research summarized in a government report on DAWN (U.S. 1988b).

In table 6, before and after the adjustment for market share, diazepam and

chlordiazepoxide were near the top of the distributions. Temazepam was

near the bottom. Triazolam was mid- range. However, drug comparisons

based on relative frequency of DAWN emergency room episodes were

258
different from those based on DAWN death data. Moreover, this analysis

also was subject to the problem of potential confounding or uneven

distribution of factors that influence probability of harm. For example,

users of diazepam may be more likely to be long- term users, as compared

to the other drugs shown. Further, there may be confounding in the

selection of patients for diazepam as compared to the other drugs. For

example, the diazepam users seen in DAWN facilities may more often be

methadone program clients or heavy drinkers of alcoholic beverages.

Finally, it also is worth noting that the number of prescriptions written

does not reflect the contribution of the street drug marketplace to casualties

involving these drugs. The number of illicitly supplied diazepam users

may be quite high, relative to the other drugs shown.

There is a tendency to interpret data of this type in hazard terms. For

example, one might read these data and conclude that taking diazepam

was most hazardous. Especially because of uncontrolled confounding,

this conclusion cannot be drawn on the basis of these data.

The issue of confounding in comparative drug testing may be understood

more clearly by thinking about which drugs are more hazardous to take

in relation to suicide. As shown in table 7, the 1986 DAWN report

indicated 152 suicide deaths involving amitriptyline, an antidepressant,

as compared to 97 for diazepam and 18 for alprazolam (U.S. 1987b). We

may wish to consider these raw values or to divide by the number of

prescriptions. Either way the ranking could lead to the conclusion that

diazepam causes more suicide than alprazolam and that amitriptyline

causes more suicide than diazepam. (Though we did not have an estimate

for amitriptyline’s market share, it certainly was lower than that of

diazepam. Hence, both the number of amitriptyline-related suicides and

the ratio of deaths to market share exceed corresponding values for

diazepam.)

On the basis of the available data, any conclusion that amitriptyline use

made a greater contribution to suicide deaths would be no more justified

than the conclusion that alprazolam actually has prevented more suicides

than either diazepam or amitriptyline. (This might be suspected because

the alprazolam values are lowest.) There is an unaddressable problem of

confounding by indication in these DAWN data. It is quite plausible that

diazepam and alprazolam are less likely to appear in relation to suicides

simply because amitriptyline users are more likely to have a major affective

disorder putting them at greater risk for suicide, The indications for

amitriptyline use, as compared to those for diazepam and alprazolam,

make it difficult to compare the hazards associated with each drug.

259
Table 7. Comparative analysis of suicide deaths and involvement of amitriptyline, diazepam, and alprazolam.

Amitriptyline Diazepam Alprazolam

Number of death reports

that mention the drug: 263 317 32

Percent of all such deaths

judged to be drug-induced: 81 79 88

Number of the reports on suicide

deaths that mention the drug: 152 97 18

Millions of prescriptions: <23 23 11

Number of suicide deaths per million RX: >4.2 4.2 1.6

Note: Data compiled for the Drug Abuse Warning Network based on reports from medical examiners offices, 1986.

Because the market share for amitriptyline is substantially smaller than the share for diazepam, we infer that the number of suicide

deaths per million prescriptions is larger for amitriptyline.
In conclusion, the only way to interpret data of this type meaningfully is

to make generally unrealistic assumptions that all confounding factors

are distributed evenly across drug groups. In some instances it is possible

to eliminate certain assumptions, for example, by using random allocation

designs in post-marketing research. Alternately, it sometimes is possible

to find special settings where some or all of the confounding factors have

demonstrably even distributions, or nearly so. This was what Bergman

and Griffiths were able to do in their work on relative abuse of diazepam

and oxazepam in Sweden (Bergman and Griffiths 1986). Unfortunately,

it often has been necessary to go outside the United States to find suitable

settings for comparisons of this type. Finally, when ancillary data can be

found for each important confounding variable, it sometimes is possible

to use statistical models that hold the confounding variables constant.

This is a strategy found to be generally useful in drug epidemiology that

we also have taken in our own work on suspected causal associations

between cocaine use and psychiatric disturbances, described elsewhere

(Anthony et al., 1989; Anthony and Petronis in press, c).

THE NATURE AND QUALITY OF DATA

In the United States, the epidemiologic data available for comparative

drug testing typically have been gathered for some other purpose. For

example, the Epidemiologic Catchment Area surveys were designed as

research on the occurrence of mental disorders in the population. There

was no explicitly stated, advance plan to use these data for comparative

drug testing. This accounts for some weaknesses of the ECA data when

we have applied them to problems related to comparative drug testing.

Similarly, the currently available data from drug abuse surveillance

systems like DAWN and the System to Retrieve Information from Drug

Evidence (STRIDE) are gathered primarily to describe current drug abuse

conditions and to monitor trends over time. By definition, these systems

were designed for surveillance, which in epidemiology means an ongoing review of a population’s experience in sickness and health, generally

with methods that are notable by their practicality, uniformity, and rapidity,

not necessarily distinguished by accuracy or completeness (Last 1983).

For this reason, it may be unreasonable to expect that these surveillance

systems can provide information of a nature and quality suitable for

comparative drug testing. As mentioned above and discussed in more

detail elsewhere (Ungerleider et al., 1980: Anthony and Trinkoff 1986),

there are important, unresolved questions about the capacity of surveillance

systems like DAWN to provide accurate information about specific drug

products. These questionsrelatenot only to the accuracy and completeness

261
of drug identification, but also to issues such as the responsivity of DAWN

to pending drug control decisions or to media coverage of the street drug

scene.

In thecontext of comparative drug testing through analysis of surveillance

data, one problem that deserves greater attention stems from amultiplicity

of possible comparisons. Due to a lack of broadly accepted guidelines or

principles, it is possible for an interested party to dredge through masses

of surveillance data, picking and choosing from among many possible

drug comparisons and from among many possible statistical indices for

comparison. When reading reports on the final comparisons, it is not

always clear that the investigator approached the analysis with specific

statistical indices or drug comparisons planned in advance. The element

of opportunism, which increases the likelihood of spurious findings, is

uncontrolled. Our discussion of table 6 illustrates this point.

CONCLUDING REMARKS

The subtitle for this paper asks, “How are epidemiologic data relevant to

testing abuse liability of drugs?” Others have said or implied that what

happens once a drug is released for use outside the laboratory should be

the gold standard against which all abuse liability predictors are tested.

As sketched out here, in principle, this is right, but it may be easier said

than done.

Due to the myriad features and determinants of psychoactive drug-taking

and drug hazards in the population, comparative testing of drugs for

abuse liability by epidemiologic methods calls for refining concepts like

liability for abuse and liability of abuse. These concepts now seem to

attribute too much influence to the drug itself, too little to environment

and host conditions under which suspected hazards are observed. In

addition, due to the likely presence of confounding by indications for use,

and possible confounding by other factors, it always will be difficult to

produce unequivocal drug comparisons using observational epidemiologic

strategies that do not contend with these possibilities for error in

comparative drug testing.

Considering the nature and quality of epidemiologic data now available,

we face a challenge if we are to use these data in comparative drug testing.

The challenge is to state the principles that must be followed and the

standards that must be met. At a minimum, it would seem that our

standards should require concurrent analyses involving a pre-specified

array of drug products and statistical measures of outcome. Tests of

262
assumptions about confounding by indication and other conditions related

to drug use should become standard practice, as should tests of assumptions

about quality of data being analyzed. Without these principles and

standards for use of epidemiologic data, the elements of opportunism and

selective attention are uncontrolled. Especially in exploration of

surveillance data, it is too easy to pick out the drugs, outcome measures,

and analytic techniques that serve one interest, one time. Without tests

or critical review of assumptions, the epidemiologic work is incomplete.

In view of difficulties with present epidemiologic data now available in

the United States, serious thought must be given to improving their quality.

If we are to use DAWN and other routine reporting systems for more than

surveillance, then some re-design will be needed to assure that these data

meet minimal standards for the additional tasks, such as comparative

drug testing. It is almost certain that the re-designing will require a major

investment of time and effort by experienced pharmacologists and

epidemiologists willing to be held accountable for the resulting products.

At present, no one is making this investment. Perhaps this is a task-area

that should be sponsored and given priority by the Committee on Problems

of Drug Dependence.

When marketed psychoactive drugs are of interest, the problems of

confounding by indication, and quality of data, may be best solved in the

United States by shifting to the arena of large-scale medical practices and

health plans. in some of these settings there is a capacity for careful

observational studies and a willingness to have patients assigned to

treatment conditions in order to account for indications and other

potentially confounding conditions. This approach is an especially

ambitious one that also requires a major investment by pharmacologists

and epidemiologists, not to mention practicing clinicians in charge of

patient care. Nevertheless, ambitious work of this type will be essential

if the drug epidemiologist’s contribution to comparative testing of

psychoactive drugs is to live up to the high standards now set in laboratory

research on this issue.

REFERENCES

American Psychiatric Association, Committee on Nomenclature and Statistics:

Diagnostic and Statistical Manual of Mental Disorders, Third Edition.

Washington, D.C., American Psychiatric Association, 1980.

Anthony, J.C. Young adult marijuana use in relation to antecedent misbehaviors.

In: Harris, L.S., ed. Problems of Drug Dependence 1984. National

Institute on Drug Abuse Research Monograph No. 55. DHHS Pub. No.

(ADM)85-1393. Washington, D.C.: Supt. of Docs., U.S. Govt. Print.

Off., 1985.

263
Anthony, J.C.; Folstein, M.; Romanoski, A.J.; VonKorff, M.R.; Nestadt, G.R.;

Chahal, R.; Merchant, A.; Brown, C.H.; Shapiro, S.; Kramer, M.; and

Gruenberg, E.M. Comparison of the lay Diagnostic Interview Schedule

and a standardized psychiatric diagnosis. Arch Gen Psychiatry 42:667-

675, 1985.

Anthony, J.C., and Helzer, J. Syndromes of drug abuse and dependence. In:

Robins, L.N., and Regier, D.A., eds. Psychiatric Disorders in America.

New York: The Free Press, in press, a.

Anthony, J.C., and Petronis, K.R. Cocaine and heroin dependence compared:

Re-consideration with evidence from an epidemiologic field survey, in

press, b.

Anthony, J.C., and Petronis, K.R. Epidemiologic evidence on suspected

associations between cocaine use and psychiatric disturbances. In:

Schade, C., and Schober, S., eds. The Epidemiology of Cocaine Use and

Abuse. National Institute on Drug Abuse Research Monograph.

Washington, D.C.: Supt. of Docs., U.S. Govt. Print. Off., in press, c.

Anthony, J.C.; Tien, A.Y.; and Petronis, K.R. Epidemiologic evidence on cocaine

use and panic attacks. Am J Epidemiol 129:543-549, 1989.

Anthony, J.C., and Trinkoff, A.M. Epidemiologic issues pertinent to international

regulation of 28 stimulant-hallucinogen drugs. Drug Alcohol Depend

17:193-211, 1986.

Bergman, U., and Griffiths, R.R. Relative abuse of diazepam and oxazepam:

Prescription forgeries and theft/loss reports in Sweden. Drug

Depend 16:293-301, 1986.

Blazer, D.; Swartz, M.; Woodbury, M.; Manton, K.G.; Hughes, D.; and George,

L.K. Depressive symptoms and depressive diagnoses in a community

population. Arch Gen Psychiatry 45(12):1078-1084, 1988.

Eaton, W.W., and Kessler, L.G., eds. Epidemiologic Field Methods in

Psychiatry. New York: Academic Press, 1985.

Eaton, W.W.; Kramer, M.; Anthony, J.; Dryman, A.; Shapiro, S.; and Locke, B.Z.

The incidence of specific DIS/DSM-III mental disorders: Data from the

NIMH Epidemiologic Catchment Area Program. Acta Psychiatr Scand, in

press, 1988a.

Eaton, W.W.; Dryman, A.; Sorenson, A.; and McCutcheon, A. DSM-III Major

depressive disorder in the community: A latent class analysis of data from

the NIMH Epidemiologic Catchment Area Program. Brit J Psychiatry, in

press, 1988b.

Finney, D.J. Statistical logic in the monitoring of reactions to therapeutic drugs.

In: Inman, W.H.W., ed. Monitoring for Drug Safety. Philadelphia: J.B.

Lippincott Company, 1980.

Griffiths, R.R. Progress Report from the Division of Behavioral Biology, The

Johns Hopkins University School of Medicine. In: Harris, L.S., ed.

Problems of Drug Dependence. 1985 National Institute on Drug Abuse

Research Monograph No. 67. DHHS Pub. No. (ADM) 86-1448.

Washington, D.C.: Supt. of Docs., U.S. Govt. Print. Off., 1986.

Helzer, J.E.; Robins, L.N.; McEvoy, L.T.; Spitznagel, E.L.; Stoltzman, R.K.;

Farmer, A.; and Brockington, I. A comparison of clinical and Diagnostic

Interview Schedule diagnoses: Physicians reexamination of layinterviewed cases in the general population. Arch Gen Psychiatry 42:

657-666, 1985.

264
Kellam, S.G.; Brown, C.H.; Rubin, B.R.; and Ensminger, M.E. Paths leading to

teenage psychiatric symptoms and substance use: Developmental

epidemiologic studies in Woodlawn. In: Guze; S.B., Earls, F.J.; and

Barrett, J.E., eds. Childhood Psychopathology and Development. New

York: Raven Press, 1983.

Last, J.M. A Dictionary of Epidemiology. New York: Oxford Press, 1983.

Parry, H.J.; Balter, M.B.; and Cisin, I.H. Primary levels of underreporting

psychotropic drug use. Public Opinion Quart 34:582-592, 1971.

Regier, D.A.; Boyd, J.H.; Burke, J.D.; Rae, D.S.; Myers, J.K.; Kramer, M.;

Robins, L.N.; George, L.K.; Kamo, M.; and Locke, B.Z. One-month

prevalence of mental disorders in the United States: Based on five

epidemiologic catchment area sites. Arch Gen Psychiatry 45:977-986,

1988.

Robins, L.N. Sturdy childhood predictors of adult antisocial behavior:

Replications from longitudinal studies. Psychol Med 8:611-622, 1978.

Robins, L.N.; Helzer, J.E.; Croughan, J.; and Ratcliff, K. National Institute of

Mental Health Diagnostic Interview Schedule. Arch Gen Psychiatry

38:381-389, 1981.

Robins, L.N.; Orvaschel, H.; Anthony, J.C.; Blazer, D.G.; Burnam, M.A.; and

Burke, J. The Diagnostic Interview Schedule. In: Eaton, W.W., and

Kessler, L.G., eds. Epidemiologic Field Methods in Psychiatry: The

NIMH Epidemiologic Catchment Area Program. New York: Academic

Press, Inc., 1985.

Robins, L.N., and Przybeck, T.R. Age of onset of drug use as a factor in drug and

other disorders. In: Jones, C.L., and Battjes, R.J. eds. Etiology of Drug

Abuse. National Institute on Drug Abuse Research Monograph No. 56.

DHHS Pub. No. (ADM) 85-1335. Washington, D.C.: Supt. of Docs.,

U.S. Govt. Print. Off., 1985.

Rothman, K.J. Modern Epidemiology. Boston: Little, Brown, and Company,

1986.

Shrout, P.; Spitzer, R.L.; and Fleiss, J.L. Quantification of agreement in

psychiatric diagnosis revisited. Arch Gen Psychiatry 44: 172-177, 1987.

Ungerleider, J.T.; Lundberg, G.D.; Sunshine, I.; and Walberg, C.B. The Drug

Abuse Waming Network (DAWN) Program: Toxicologic verification of

1,008 emergency room ‘mentions’. Arch Gen Psychiatry 37:106-109,

1980.

United States. National Institute on Drug Abuse. Division of Epidemiology and

Statistical Analysis. Annual Data 1985: Data from the Drug Abuse

Warning Network DAWN). Series I, No. 5. National Institute on Drug

Abuse. DHHS Pub. No. (ADM) 86-1469. Washington, D.C.: Supt. of

Docs., U.S. Govt. Print. Off., 1986.

United States. National Institute on Drug Abuse. Demographic Characteristics

and Patterns of Drug Use of Clients Admitted to Drug Abuse Treatment

Programs in Selected States: Annual Data 1985. National Institute on

Drug Abuse. Washington, D.C.: Supt. of Docs., U.S. Govt. Print. Off.,

1987a.

United States. National Institute on Drug Abuse. Annual Data 1986: Data from

the Drug Abuse Warning Network. Series I, Number 6. National Institute

on Drug Abuse. DHHS Pub. No. (ADM) 87-1530. Washington, D.C.:

Supt. of Docs., U.S. Govt. Print. Off., 1987b.

265
United States. National Institute on Drug Abuse. National Household Survey on

Drug Abuse: Main Findings 1985. National Institute on Drug Abuse,

DHHS Pub. No. (ADM) 88-1586. Washington, D.C.: Supt. of Docs.,

U.S. Govt. Print. Off, 1988a.

United States. National Institute on Drug Abuse. Division of Epidemiology and

Statistical Analysis. A Decade of Dawn: Benzodiazepine-Related Cases.

1976-1985. Series H, No. 4. National Institute on Drug Abuse, DHHS

Pub. No. (ADM) 88-1575. Washington, D.C.: Supt. of Docs., U.S. Govt.

Print. Off., 1988b.

ACKNOWLEDGMENTS

Supported by research grants from the National Institute on Drug Abuse

(DA 03992, DA 04392) and the Academic Data Processing Center of the

Johns Hopkins University School of Hygiene and Public Health. In

addition, the ECA Program was supported by grants from NIMH

(MH 34224, MH 33870, MH 33883, MH 35386, MH 35865). During the

period of data gathering, the principal investigators for these awards were

J.K. Myers (New Haven), M. Kramer (Baltimore), L. Robins (St. Louis),

D. Blazer (Durham), R. Hough and M. Karno (Los Angeles), D.A. Regier

and B.Z. Locke (NIMH).

AUTHORS

James C. Anthony, Ph.D.

Associate Professor

Department of Mental Hygiene

School of Hygiene

and Public Health

The Johns Hopkins University

615 North Wolfe Street

Baltimore, Maryland 21205

Alison M. Trinkoff, Sc.D.

Assistant Professor

Center for Nursing

and Health Services Research

School of Nursing

University of Maryland

655 West Lombard Street

Baltimore, Maryland 21201

266
CHAPTER 13

Current Approaches to Measurement of Drug Use and

Abuse in Sweden

Ulf Bergman, M.D.

David Lee, M.D.

INTRODUCTION

The use and abuse of barbiturates, organic bromides and amphetamines

was described in Sweden in the 1930s. The development of the abuse in

Sweden leading to the current restrictions in the prescribing of narcotic

drugs introduced in 1962 has previously been reviewed (Goldberg 1968a;

1968b). These regulatory measures drastically reduced the number of

prescriptions for narcotics, and several of these drugs, such as amphetamines, opiates and barbiturates, have been withdrawn from the market.

Table 1 lists currently available drugs legally classified as narcotics (which

includes some psychotropic drugs) in Sweden. The nine drugs on Schedule II and III are available in 13 trade names, all for parenteral use and

four’ also available in oral dosage forms. The 19 drugs on Schedules IV

and V are available in 30 trade names, in oral dosage forms, and two2 only

for parenteral use. There has been a considerable reduction in the number

of drugs and trade names since the late 1960s.

In agreement with the reported situation in the United States, the exaggerated fear of morphine abuse has also prevented cancer patients from

receiving adequate pain treatment in Sweden (Marks and Sachar 1973;

Agenäs et al., 1982). However, since the 1970s pharmacokinetic research

has led to an increasing use of high-dose oral morphine and methadone

in cancer patients (Säwe 1986). Keeping in mind the previous abuse

experience with these drugs, current prescribing is guided by strict regulations for narcotics.

1

 Injectables that are also available for oral use.

2

 Only available for parenteral use.

267
Table 1. Narcotic and psychotropic drugs under regulatory control in Sweden.

Schedules II and III Schedules IV and V

Fentanyl

Hydromorphone

Ketobemidone’

Methadone1

Morphine1

Pentazocine1

Pethidine

Phenoperidine

Piritramide

Alprazolam

Chloral hydrate

Chlordiazepoxide

Clomethiazole

Clonazepam

Clorazepate

Diazepam

Flunitrazepam

Hexapropymate

Lorazepam

1

 Injectables that are also available for oral use.

2

 Only available for parenteral use.

Meprobamate

Methohexital2

Methyprylon

Midazolam2

Nitrazepam

Oxazepam

Phenobarbital

Pyrithyldione

Triazolam

Drug abuse and dependence have lately attracted much attention and are

of major concern to health authorities as well as practitioners. With this

has come an awareness of the need for auditing mechanisms and/or control

measures at different levels of the health care system in order to promote

rational prescribing of drugs with an inherent abuse liability.

This paper will discuss the current epidemiological approaches to these

problems in Sweden. Although the term “medication” has been rightly

advocated to distinguish drugs used in a medical context fromillicit drugs

(Wright 1987), for the sake of consistency with current pharmaco-epidemiological terminology we will continue to use the term “drug” for

medically useful substances with abuse liability, even if they might be

subject to illegal use.

THE CLINICAL/PUBLIC HEALTH PROBLEM

Prior to marketing, the assessment of abuse liability of drugs, as for any

other measure of efficacy (and safety), is conducted under experimental

conditions and with populations which do not necessarily reflect the

reality of routine medical practice, such as the use of subjects who have

had little or no exposure to psychotropic drugs, nor medical conditions

requiring use of these drugs. In some cases, experimental assessment has

been performed in individuals with previous history of drug abuse.

However, drugs may have different effects on different subject populations. For example, it remains to be established that sedative drugs, and

268
benzodiazepines in particular, have significant reinforcing effects or induce

preference in subjects who do not have histories of sedative abuse (Woods

et al., 1987). Much information is still lacking on the determinants of the

use and misuse of drugs with central nervous system actions and their

consequences. Therefore, epidemiological data is needed to place into

perspective limited premarketing experimental data.

From the perspective of ensuring the most optimal (safest and most effective) use of drugs, an ongoing auditing process is required (Crooks

1984), particularly for those drugs with abuse liability. Descriptive drug

utilization studies are essential as a “signalling” mechanism to draw

attention to problems which arise with the drugs with abuse liability, to

assess the appropriateness and to quantify the extent of use and misuse.

The descriptive approach to the study of drug utilization at all levels of

the health and drug chain may be quantitative or qualitative. For example,

quantitative studies may describe time course profiles of psychotropic

drug usage at different levels of the health care system (national, regional,

local, institutional). On the other hand, qualitative studies address the

appropriateness of drug use by evaluating it relative to the medical context

(indication/condition) and the patient characteristics.

Data derived from such studies, whether quantitative or qualitative, may

form the basis for discussions, be it at the national or the local level, the

results of which, if appropriately translated into practice, reduce the risk

and increase the effectiveness of drug therapy.

THE METHODOLOGICAL PROBLEM

Considerable amount of psychotropic drug use data is currently available. Routine statistics on consumption of drugs have traditionally been

compiled either for administrative or marketing purposes. The sales data

have been usually expressed in terms of cost or volume units. Although

total costs or unit costs (cost per package, tablet, dose, treatment course)

may be useful for measuring and comparing the economic impact of drug

use, these units do not provide information on the amount of drug exposure in the population. Moreover, cost data are influenced by a number

of factors such as price fluctuations over time, distribution channels,

inflation, price control measures, etc. (WHO/EURO 1970).

Volume data is also available (overall weight or unit volumes) such as

number of packages, tablets, prescriptions, doses, treatments, etc. Drug

package sizes may differ in the number of tablets contained from time to

time or country to country. Dosage forms may be available in various

strengths.

269
The number of prescriptions is one of the most frequently used units of

volume. However, distinction must be made between first prescriptions

and refill prescriptions, as they affect the estimate of the number of persons

treated or exposed to the drug. Additional problems may be posed by

differences in the number of prescription items in each prescription. It

should be noted that all these units represent approximate estimates of

true consumption, which ultimately is determined by the patient’s actual

drug intake (degree of compliance).

Aggregate drug utilization data may provide crude estimates of the extent

of drug use, but, by themselves do not indicate the quality or appropriateness of use. The appropriateness of drug utilization must be assessed

relative to the reasons or medical indications for, or consequences of,

drug use (the clinical context). Data on morbidity and mortality may be

searched for in national registries (general or specialized, such as toxicology centers, adversedrugreactionsreportingcenters, etc.), national sample

surveys; ad hoc surveys and special studies; hospital records; physician

records; and patient/household surveys. Some of the morbidity and

mortality data may be available, but perhaps not relevant for clinical

purposes.

In addition to the reasons for drug use, and particularly in the assessment

of drug abuse liability, data is needed on individual patterns of use, such

as the frequency of intake (on a daily, weekly, monthly basis), the duration of use, and whether it is on a regular or an intermittent basis.

CURRENTLY AVAILABLE DRUG UTILIZATION DATA

BASES

Over the past 20 years, data on drug utilization has been systematically

compiled through the use of drug sales statistics, prescription surveys,

and continuous recording of prescriptions in two defined geographic

areas. Two of the currently available drug databases are linked to morbidity (diagnosis/indication) data. All are potentially useful, despite some

limitations, for the study of drug use and misuse.

Total sales of drugs to pharmacies and hospitals have been recorded by

Läkemedelsstatistik AB (Swedish Pharmaceutical Data, Ltd. LSAB) since

1965. These sales statistics are published quarterly in the Swedish Drug

Market (SDM) and are distributed to subscribers in the pharmaceutical

industry, the National Board of Health and Welfare (Department of Drugs),

and the National Corporationof Pharmacies (Apoteksbolaget). The sales

statistics are also made available by the Department of Drugs of the

National Board of Health and Welfare through the online Swedish Drug

Information System (SWEDIS). The National Corporation of Pharma270
cies (Apoteksbolaget) publishes annual drug sales statistics for the country as a whole and for each county since 1976. As of this year (1988)

national drug sales statistics are provided under the Anatomic-Therapeutic-Chemical (ATC) drug classification recommended by the Nordic

Council on Medicines and the World Health Organization (WHO) Drug

Utilization Research Group to facilitate comparability in cross-national

studies. Comparative drug utilization data for the Nordic countries

(Denmark, Finland, Iceland, Norway, and Sweden) have also been routinely available since 1979 (Nordic Council on Medicines 1979; 1982;

1986; 1988).

A continuous nationwide prescription survey has been conducted since

1974. For each prescription in a sample of 1 in 288 prescriptions filled the

following data are recorded: age and sex of the patient, the name and

amount of drug prescribed, daily dose, patient fee and total cost (Wessling

1987). Data obtained from this survey have been used to validate the sales

data and to provide age and sex profiles, etc., (figure 1).

The Swedish Diagnosis and Therapy Survey is a collaborative project run

by the Swedish Pharmaceutical Data Ltd (LSAB), the National Corporation of Pharmacies (Apoteksbolaget), the Swedish Medical Association,

and the National Board of Health and Welfare. A random sample of 1 out

of 8 physicians (2200 per year) are asked to participate. During a study

week all prescriptions are recorded on self copying forms with additional

information on the indication or diagnosis for each drug, patient characteristics (age and sex), type of consultation, etc. The diagnoses or symptoms are coded according to the International Classification of Diseases.

This survey is similar to IMS America’s National Drug and Therapeutic

Index (Bergman and Dahlström 1988). The data are analyzed according

to IMS routines and provided to subscribers twice a year. Drug utilization

data from this ongoing survey are also included in the annual drug statistics published by the National Corporation of Pharmacies (Apoteksbolaget 1988).

In the County of Jämtland Project all drug prescriptions dispensed to 14

percent of the Jämtland population (approximately 17,000) have been

continuously monitored since 1970 (Bergström and Westerholm 1973).

The recorded information includes the patient unique identity number;

name, dosage, quantity, and price of the drug; date of dispensing; dispensing pharmacy; and prescribing physician. This pioneer database has

been useful in studying individuals’ purchases of psychotropic medication over time. In a six-year longitudinal study of 2566 individuals who

purchased hypnotics, sedatives and minor tranquilizers, signs of overuse

or abuse were observed in only four patients (0.2 percent) (Boethius and

271
Westerholm 1977). A number of important issues concerning drug prescribing in primary care have also been studied, such as doses and dosage

intervals, prescribing in pregnancy, etc. (Boethius and Sjöqvist 1978;

Boethius 1977).

The Community of Tierp Project is run by the Centre for Primary Care

Research, University of Uppsala, Sweden. Since 1972 prescription and

morbidity data are routinely collected from all pharmacies and the health

center within the community for all residents (21,000). The data base has

been used to study patterns of psychotropic drug utilization in patients

considered as “heavy users” of prescription drugs in general (Isacson and

Smedby 1988). However, aggregate drug data are stored on a pharmacologic or therapeutic class basis and, with the exception of the benzodiazepines, it is not possible to study individual drugs.

Figure 1: Hypnotics, sedatives and minor tranquilizers. Age and sex distribution of

prescription items per 1000 men (upper) and 1000 women (1ower) per year in 1976.

and 1986 (Permission to reprint from Bergman et al., 1988:4. granted by B-E Wiholm,

Dept. of Drugs, National Board of Health)

272
Interestingly, in these two independent databases a marked decrease in

the prescribing of hypnotic-sedatives and minor tranquilizers has been

observed since the early 1970s. The decrease was most prominent in the

proportion of the population with infrequent prescription of these drugs,

whereas the proportion with regular use appeared to be stable (Boethius

and Westerholm 1979; Isacson and Smedby 1988).

The small size of both of the above databases are important limitations

for hypothesis testing studies, as evidenced by recent unsuccessful efforts to confirm or refute the signal generated by Laegreid et al. (1987)

concerning the teratogenicity of benzodiazepines (Bergman et al., 1989).

Units of Measurement

Two standard units have been developed in the Nordic countries to measure

and compare drug utilization and have been widely used in the past 15

years. Although the number of prescriptions is also widely used, the

following discussion will be limited to the Defined Daily Dose (DDD)

and the Prescribed Daily Dose (PDD).

The Defined Daily Dose methodology was developed in the 1970s to

standardize and exploit readily available volume data from sales statistics

or pharmacy inventory data (quantity of packages, tablets or other dosage

forms). Drug sales data was converted into medically meaningful units,

to make crude estimates of the number of persons exposed to a particular

drug or class of drugs (Baksaas-Aasen et al., 1975; Bergman et al., 1979).

The defined daily dose (DDD) is the assumed average maintenance dose

for the main indication of a particular drug. Expressed as DDDs/1000

inhabitants/day it can be interpreted as the proportion of the population

that may receive treatment with a particular drug (Baksaas-Aasen et al.,

1975; Nordic Council on Medicines 1986). Figure 2 illustrates the trends

in sales of hypnotics, sedatives, and minor tranquilizers, expressed in

DDDs.

For use in hospital settings, it may be expressed as DDDs/100 bed-days

(adjusted for occupancy rate) (Bergman et al., 1980). The method has

been useful in describing and comparing national and international patterns of psychotropic drug utilization (Grimsson et al., 1979; King and

Griffiths 1984), providing denominator data for the estimation of rates of

reported adverse drug reactions (Bergman et al., 1978), epidemiologic

screening for problems in drug utilization (Westerholm 1986), and to

monitor the effects of informational and regulatory activities (Sjöqvist

1975; Lunde et al., 1987). The advantages of this methodology include:

its usefulness for working with readily available gross drug statistics at

273
Figure 2: Sales of hypnotics, sedatives and minor tranquilizers in Sweden, 1976 July

1987, expressed in DDDs/1000 inhabitants/day (Permission to reprint from Bergman

et al., 1988:4, granted by B-E Wiholm, Dept. of Drugs, National Board of Health).

various levels of the drug and health chain; as a standardized unit of

measurement, it allows comparisons between drugs in the same therapeutic class, between different health care settings or geographic areas,

and comparisons over time; and is relatively inexpensive. The DDD

methodology has, however, some important limitations. The DDD is not

a recommended dose, but rather a technical unit of comparison. Since

DDDs are based on usage in the Nordic countries, some DDDs may be

high or low relative to other countries. Many drugs that are not marketed

in the Nordic countries have not been assigned DDDs (but guidelines

have been published for defining DDDs under these circumstances)

(Nordic Council on Medicines 1982, 1986). Additional problems arise

when dosages vary according to its indication as in the case of the neuroleptics, or when drugs are used in combination with other drugs for the

same disease. Although in Sweden, the use of psychotropic drugs in

analgesic and other combination products (“hidden psychotropics”) is

not a problem, this may be of importance in countries with elevated

utilization of combination drugs (Laporte et al., 1981). Moreover, the

DDD does not take into account pediatric uses. Since children’s doses are

substantially lower than the established DDDs, this situation will lead to

an underestimation of population exposures which may be significant in

countries with a large pediatric population.

274
The prescribed daily dose (PDD) is another unit, developed as a means

to validate the DDDs. The PDD is the average daily dose prescribed, as

obtained from a representative sample of prescriptions (Bergman and

Sjöqvist 1984). This unit provides a closer estimate of drug exposure.

Close agreement between the DDD and the PDD has been demonstrated

for drugs such as diazepam, nitrazepam, and clorazepate, whereas major

discrepancies were observed with other benzodiazepines and the neuroleptics (Bergman and Sjöqvist 1984). Higher PDDs have been observed in the U.S. relative to Sweden for commonly prescribed drugs,

such as diazepam and oxazepam (Bergman and Dahlström 1986). The

comparison indicated that even though population exposure is higher in

Sweden than in the U.S., Americans are prescribed higher daily doses of

benzodiazepines (Bergman et al., 1986). Although the DDD and the PDD

may be used to estimate population drug exposure, the methodology is

not useful to quantify or identify patients who receive doses lower or

higher than those considered effective and safe or sequential changes in

dosage.

CLINICAL AND ADMINISTRATIVE SOURCES OF

INFORMATION

A variety of different sources of information are available to provide a

clinical context to drug utilization data. Most hospitals in Sweden have

a computerized register of discharge diagnoses which allows a retrieval

of medical records according to specific diseases. Autopsy records and

analyses from the toxicology laboratories and the national toxicology

information center have been used in studies of psychotropic drug use

and abuse (Allgulander et al., 1984; Melander et al., 1984).

The Swedish Spontaneous Adverse Drug Reaction Reporting System

was established in 1965 at the Department of Drugs of the National Board

of Health and Welfare. Since 1975 it has been compulsory to report

suspected reactions that are fatal or otherwise serious, as well as new and

unexpected reactions. The annual rate of reporting has gradually increased

over the years (Strandberg and Wiholm 1986). Abuse and dependence,

however, are rarely reported as side-effects of drugs (0.5 percent). Based

on the WHO Collaborating Centre for International Drug Monitoring,

even on a global basis drug abuse/dependence account for only 0.6 percent of all reports up to 1986 (Bergman 1986).

The National Board of Health and Welfare has periodically conducted

one day prevalence studies on inpatient psychiatric diagnoses. The latest

survey in 1985 revealed that drug abuse was diagnosed in 5 per 1000

275
hospitalized patients. Hypnotics and sedatives were associated with 91

percent of these hospitalizations, barbiturates (in the process of being

withdrawn from the market) 3 percent, and analgesics 6 percent (Bergman

1986).

The Stockholm County Council, covering 1.5 million inhabitants, has

conducted a continuous register of hospital discharge diagnoses since the

late 1960s. Surveys covering the 1970s and 1980s indicate that one per

1000 residents have been hospitalized with the diagnosis of drug abuse

(Bergman 1983; Bergman et al., 1988). In the survey covering 1969-

1982, one-third of the patients (n=729) had no such history of alcohol or

illicit drug abuse. Two-thirds of these patients were women. In 24 percent

of the cases barbiturates were involved, in 67 percent other hypnoticsedatives, and analgesics in the remaining 9 percent. The results of longitudinal analyses indicate a high degree of morbidity (hospitalizations

for somatic and/or psychiatric problems) and mortality, consistent with

findings from another detailed follow-up study in the same catchment

area (Allgulander et al., 1984).

Prescription forgeries and theft/loss reports may be a useful indirect (proxy)

measure of misuse and abuse. All outpatient pharmacies (800) are

administratively organized in six pharmacy regions within the National

Corporation of Pharmacies (Apoteksbolaget AB). Prescription forgeries

uncovered at the outpatient pharmacies within each region are periodically reported (twice a year) to the Department of Drugs, National Board

of Health and Welfare. Data in the reports include the name of the drug(s)

in the prescription, the date and dispensing pharmacy. Similarly, theft and

loss reports from drug distribution channels (pharmacies, general/family

practices, clinics, hospitals, etc.) are reported to the Department of Drugs

through the regional pharmacy centers. The results of a study comparing

the rates of reported prescription forgeries and theft/loss reports for

diazepam and oxazepam were consistent with experimental data in humans

(Griffiths et al., 1984) that suggest a higher abuse liability for diazepam

relative to oxazepam (figure 3). The difference in rate of reports was still

significant when the most widely known brand of diazepam (Valium)

was excluded from the calculations (Bergman and Griffiths 1986). This

approach may be useful in a drug abuse surveillance network. When

prescription forgeries and theft/loss reports are related to actual drug

utilization, the changes in prevalence and patterns of abuse may suggest

problems that merit indepth investigation (Bergman and Dahl-Puustinen

1988). An important issue to be considered in the interpretation of the

data generated is the rate of detection and reporting of prescription forgery. At present, accurate data on rates of detection and reporting of

276
prescription forgeries is not available. The extent of use of prescription

forgeries and theft to obtain drugs, relative to consulting physicians for

a prescription, must also be taken into consideration in the analysis of

these data.

Figure 3: Relative prescription forgeries per 100,000 prescription items for the four

major benzodiazepines in Sweden, 1982-1986. (Bergman and Dahl-Puustinen 1988)

INTERVENTION STRATEGIES BASED ON DRUG

UTILIZATION DATA

Current activities to promote the rational use of drugs with abuse potential in Sweden fall under a more comprehensive approach to rational drug

utilization, emphasizing information and education, self-auditing, and,

on occasion, regulation.

Drug utilization data are important elements in the expert discussions and

formulation of consensus statements which have been conducted as a

workshop series by the National Board of Health and Welfare since 1982,

and have recently included discussions on the pharmacological management of alcohol abstinence, anxiety, and sleep disorders (Drug Information Committee 1985:2; 1988:1,4).

277
Drug utilization data, in the form of trends in overall sales statistics and

prescribing patterns, are routinely published (Svensk Läkemedelsstatistik 1987) and made widely available to stimulate and facilitate discussions at all levels of the health care system, particularly in local or regional therapeutics committees.

Two examples may serve to illustrate the Swedish approach regarding

drugs with abuse potential and the role of drug utilization data in drawing

attention to potential or actual problems of misuse or abuse.

In 1983, dextromethorphan was changed from prescription to over-thecounter (OTC) status. Concurrent with an increase in sales, several local

outbreaks of dextromethorphan abuse in young people were reported

over a 2 year period (Swedish Adverse Drug Reactions Advisory Committee 1985). In 9 of 30 surveyed areas belonging to a nationwide drug

abuse surveillance network, it was established that most of the outbreaks

were self-limiting and of short duration. However, although overall

dextromethorphan sales had decreased considerably, in two areas the

abuse level increased and extended to the adult population, as determined

from reports by the network and various other sources (police, schools)

and queries received by the national poison information center. The use

of much higher doses of dextromethorphan which were associated with

abuse may explain why results on liability testing were negative in humans

using low doses as opposed to positive results in animal studies (Griffiths

and Balster 1979). This risk was judged to be unacceptable for an OTC

drug and dextromethorphan was placed, once again, on prescription status

in April 1986 (Socialstyrelsens läkemedelsavdelning 1986).

In 1978, local review of the routinely published sales statistics for hypnotic, sedatives and minor tranquilizers revealed that sales in Malmöhus

county were well above the national mean. The follow up investigation

indicated that most of the prescribing was limited to the city of Malmö

and the very high prescribing rate to a small number of physicians (Kaij

et al., 1983). The appropriate indications for these drugs were reviewed

in a scientific meeting held in Malmö in 1979 and an information letter

by the local medical association was sent to all physicians discussing the

precautions to be taken in the prescribing of these drugs. The sales of

these drugs decreased following these information activities. Parallel

decreases in the number of hospitalizations due to abuse of these drugs

and the number of lethal barbiturate intoxications were observed (Melander

et al., 1984). The effect on the drug sales and number of hospitalizations,

however, was short-lived as shown by subsequent rises (Melander and

Stenberg 1986). Figure 4 illustrates the decrease and subsequent rise in

278
sales of these drugs in the larger area of Malmöhus county. The unfavorable risk/benefit of the barbiturates derived from these and other observations in the Stockholm area resulted in the withdrawal of the oral forms

of barbiturates (with the exception of phenobarbital for epilepsy) from

the Swedish market (Socialstyrelsens läkemedelsavdelning 1984).

Figure 4: Sales of hypnotics, sedatives and minor tranquilizers in selected counties

of Sweden, 1975-1985, expressed in DDDs/1000 inhabitants/day. M = Malmöhus

county; O = Gothenburg and Bohus; AB = Stockholm; Z= Jämtland; V = Västmanland;

BD = Norrbotten (Permission to reprint from Bergman and Dahlström 1988:1)

granted by B-E Wiholm, Dept. of Drugs, National Board of Health).

THE FUTURE

Opportunities

The descriptive epidemiological study of the use of drugs with abuse liability has primarily focused on the quantification of the extent of use in

the context of a more comprehensive signalling system that covers all

marketed drugs. Any “signalling” or “hypothesis generating system”

may also require some form of “hypothesis testing system” to be able to

provide meaningful conclusions. With regard to abuse liability testing,

this is probably best done in human experimental studies. It has been

suggested that the abuse potential of new drugs relative to well known

drugs on the market ought to be part of the registration dossier for relevant

psychotropic and analgesic drugs (Bergman et al., 1988:4).

Some initial work has been done regarding individuals’ use of psychotropic

drugs over time with the availability of patient specific drug databases.

Further studies investigating the determinants, patterns, risks and conse279
quences of the long-term use of drugs with abuse liability, alone and in

combination with other drugs, are warranted. Research is also sorely

needed on the absolute and relative efficacy of the various interventions

that have been proposed to reduce the risk of dependence development

(Woods et al., 1987). This may be facilitated with the development of

larger databases (greater population coverage) and linkage to morbidity

and mortality data or primary physician records.

The further development of patient specific databases may facilitate not

only descriptive, analytical, and experimental epidemiological studies,

but also to incorporate the studies in the context of timely identification

of individuals at risk of developing drug dependence and preventing or

treating those who actually do (“drug shoppers”). The use of patient

specific drug histories linked to morbidity information to signal potential

drug therapy related problems is an essential element in novel intervention programs (therapeutically oriented drug utilization review) already

established in some parts of the United States (Groves 1985; Strom amd

Morse 1988).

Problems

Historically, the large medical and pharmaceutical computer databases

have been established primarily for purposes other than scientific study.

All relevant information may not be available from the various databases

and access to primary records will necessarily be required for valid

epidemiological studies. These limitations have to be taken into account

in the design of proper epidemiological studies.

Although the technical aspects of ensuring the confidentiality of patients’

medical and pharmaceutical records in computer databases have been

successfully handled in other settings, the ongoing debate over the confidentiality issue in Sweden has impeded the capture of patient specific

drug data or its current use in health services research.

The development of a specific signalling system for drugs with abuse

liability has also been affected by legal and confidentiality issues. Local

units participating in a “drug abuse surveillance network” advocated by

the Swedish National Board of Health and Welfare in 1981, have been

implemented at a number of places in Sweden. This was found to be a

valuable way of integrating issues concerning drug abuse into the local

health care organization (Bergman et al., 1988b). These members, representing the in- and outpatient services as well as the local pharmacy,

integrated local prescribing data with data on abuse obtained from sources

such as the emergency room, the intensive care unit (Gustafsson et al.,

280
1988), laboratory analyses, as well as questions posed to the drug information center, to provide the best available health care for the individual

patient with potential drug dependence problems in the catchment area.

However, legal requirements and interpretations of informed consent

have limited the functioning of this network.

The increasing interest in cost-containment and cost-effectiveness issues, which are also present in Sweden, may become an influential factor

in future approaches to the study of drug use and misuse.

CONCLUSION

The epidemiological study of use and misuse of drugs with abuse liability

in Sweden has been developing within the wider context of drug utilization in general. A number of methods and standardized units of measurement are currently employed, which are based on relatively inexpensive

and readily available sources of drug statistics. Computer databases which

facilitate longitudinal studies, albeit limited in size and data elements,

have also contributed to the study of drug use and misuse. Drug utilization data are essential elements of ongoing therapeutic audits performed

at various levels of the health care system. The experience so far has been

quite limited, particularly with regard to drugs with abuse liability. Much

more research is needed on the development of abuse, the determinants,

patterns, risks, and consequences of the long-term use and misuse of

these drugs. Various approaches to reducing the risks and consequences

of misuse and abuse of drugs may be relevant and should be rigorously

assessed. At present, the political issue regarding confidentiality of medical

records and prescriptions seems to be the most important determinant of

the future epidemiological study and development of methods to measure, and strategies to reduce, the risks of drug use, misuse, and abuse.

281
REFERENCES

Agenäs, I.; Gustafsson , L.L.; Rane, A.; and Säwe, J. Analgetikatcrapi för cancerpatienter. Läkartidningen 79:287-289, 1982

Allgulander C; Borg S; and Vikander B. A 4-6-year follow-up of 50 patients with

primary dependence on sedative and hypnotic drugs. Am J Psychiatry

141:1580-1582, 1984.

Apoteksbolaget. Svensk läkemedelsstastik 1987. Stockholm: Apoteksbolaget,

1988, 278 pp.

Baksaas-Aasen, I.; Lunde, P.K.M.; Halse, M.; Halvorsen, I.K.; Skobba,T.J.; and

Stromnes, B. Drug Dose Statistics. List of Defined Daily Doses for Drugs

Registered in Norway. Oslo: Norsk Medisinaldepot, 1975.66 pp.

Bergman, U. Epidemiologisk uppfoljning av läkemedelsmissbruk. Sv

. . . . Läkaresällsk Handl, Hygeia 95:192, 1986.

Bergman, U. Bruk och missbruk av psykofarmaka. In: CAN, ed. Rapport 87;

Alkoholoch narkotika-utvecklingen i Sverige. Stockholm: Centralförbundet för alkohol- och narkotikaupplysning (CAN), 1987, pp. 167-177.

Bergman, U.; Agenäs, I.; and Dahlström, M. Utilization of psychotropic drugs in

Sweden and the other Nordic countries. In: Gram, L.F.; Usdin, E.; Dahl,

S.G.; Kragh-Sorensen, P.; Sjöqvist, F.; and Morselli, P.L., eds. Clinical

Pharmacology in Psychiatry, Bridging the Experimental-Therapeutic Gap.

London and Basingstoke: Macmillan Press Ltd., 1983, pp. 3-17.

Bergman, U.; Baum, C.; Dahlström, M.; Juergens, J.P.; and Kennedy, D.L. “Use

of benzodiazepines in the USA and Sweden.” Paper presented at the Drug

Information Association Annual Meeting, Washington, D.C., June 4,

1986.

Bergman, U.; Boethius, G.; Swarthng, P.G.; Isacson, D.; and Smedby, B. “Benzodiazepines and teratogenicity.” Information fran Socialstyrelsens

. . läkemedelsavdelning Argang 14:16-17, 1989.

Bergman, U.; Boman, G.; and Wiholm, B-E. Epidemiology of adverse drug

reactions to phenformin and metformin. Br Med J 2:464-466, 1978.

Bergman, U.; Christenson, I.; Jansson, B.; and Wiholm, B-E. Auditing of hospital

drug utilization by means of defined daily doses per bed-day. Eur J Clin

Pharmacol 17:183-187, 1980.

Bergman, U., and Dahl-Puustinen, M-L. “Use of prescription forgeries in a drug

abuse surveillance network.” Eur J Clin Pharmacol, in press, 1988.

Bergman, U., and Dahlström, M. Benzodiazepine utilization in Sweden and other

Nordic countries. In: Lader, M.H., and Davies, H.C., eds. Drug Treatment

of Neurotic Disorders: Focus on Alprazolam. Edinburgh: Churchill Livingstone, 1986, pp. 43-52.

Bergman, U., and Dahlström, M. Anxiety and antianxiety drug use in Sweden. In:

Drug Information Committee. Pharmacological Treatment of Anxiety.

Sweden: National Board of Health and Welfare, 1988: 1, pp. 63-74.

Bergman, U.; Dahlström, M.; and Nordenstam, I. Insomnia and pills in Sweden.

In: Drug Information Committee. Treatment of Sleep Disorders. Sweden:

National Board of Health and Welfare, 1988:4, pp. 1-16.

Bergman U., and Griffiths, R.R. Relative abuse of diazepam and oxazepam:

Prescription forgeries and theft/loss reports in Sweden. Drug Alcohol Depend 16:293-301, 1986.

282
Bergman, U.; Grimsson, A.; Wahba, A.H.W.; Westerholm, B.; eds. Studies in

Drug Utilization. Methods and Applications. Copenhagen: WHO Regional

Office for Europe, 1979, 185 pp.

Bergman, U., and Sjöqvist, F. Measurement of drug utilization in Sweden: Methodological and clinical implications. Acta Med Scand (Suppl. 683):15-22,

1984.

Bergman, U.; von Euler, C.; Frank, G.; Gertz, I.; and Rydberg, U. Arbete mot

lãkemedelsmissbruk i storstasregion-JO-beslut försvårar patientimiktade

åtgärder. Läkartidningen 85:1175-1178, 1988b.

Bergstrom, K., and Westerholm. B. Consumption of sedatives, hypnotics and

minor tranquillizers in a Swedish town. In: de la Fuente, R., and Weisman,

M.N., eds. Psychiatry, Proceedings of the V World Congress of

Psychiatry, Mexico, 1971. Amsterdam: Excerpta Medica, 1973, pp. 94-102.

Boethius, G. Recording of drug prescriptions in the Jämtland, Sweden. II. Drug

exposure of pregnant women in relation to course and outcome of

pregnancy. Eur J Clin Pharmacol 12:37-43, 1977.

Boethius, G., and Westerholm, B. Purchases of hypnotics, sedatives and minor

tranquillizers among 2.566 individuals in the county of Jämtland, Sweden

-a 6 years’ follow-up. Acta Psychiatrica Scand 56:147-59, 1977.

Boethius, G., and Westerholm, B. Hur mycket kan vi få veta om psykofarmakaförbrukningen? Läkartidningen 76:4101-4102, 1979.

Crooks, J. The concept of medical auditing. Acta Med Scand (Suppl 683):47-52,

1984.

Drug Information Committee. Pharmacological Treatment of Acoholism; Withdrawal and Aversion Therapy. Proceedings from a Workshop and

Opinions and Recommendations from the Group. Sweden: National Board

of Health and Welfare, 1985:2.

Drug Information Committee. Pharmacological Treatment of Anxiety. Proceedings from a Workshop and Opinions and Recommendations from the

Group. Sweden:National Board of Health and Welfare, 1988:1.

Drug Information Committee. Treatment of Sleep Disorders. Proceedings from a

Workshop and Opinions and Recommendations from the Group. Sweden:

National Board of Health and Welfare, 1988:4.

Goldberg, L. Drug abuse in Sweden. Bull Narc XX(1):1-31, 1968a.

Goldberg, L. Drug abuse in Sweden.(II). Bull Narc XX(2):9-36, 1968b.

Griffiths, R.R., and Balster, R.L. Opioids: Similarity between evaluations of

subjective effects and animal self-administration results. Clin Pharmacol

Ther 25:611-617, 1979.

Griffiths, R.R.; McLeod, D.R.; Bigelow, G.E.; Liebson I.A.; and Roache, J.D.

Relative abuse liability of diazepam and oxazepam: Behavioral and subjective dose effects. Psychopharmacology 84:147-154, 1984.

Grimsson, A.; Idänpään-Heikkilä, J.; Lunde, P.K.M.; Olafsson, O.; and Westerholm, B. The utilization of psychotropic drugs in Finland, Iceland, Norway, and Sweden. In: Bergman, U.; Grimsson, A.; Wahba, A.H.W.; and

Westerholm, B. Studies in Drug Utilization. Methods and Applications.

Copenhagen: World Health Organization Regional Office for Europe,

1979, pp. 163-173.

Groves, R. Therapeutic drug-use review for the Florida Medicaid program. Am J

Hosp Pharm 42:316-319, 1985.

283
Gustafsson, L. L.; Berg, A.; Magnusson, A.; Malmlund, H-O.; Sandell, B-M.; and

Stig, R. “Hexapropymate self-poisoning causes severe and long-lasting

clinical symptoms.” Unpublished manuscript, 1988.

Isacson, D., and Smedby, B. Patterns of psychotropic drug use in a Swedish

Community. Scand J Prim Health Care 6:51-58, 1988.

Kaij, L.; Melander, A.; Stenberg, P.; Widell, E. Bruk och missbruk av lugnande

medel - information påverkar förskrivningen. Läkartidningen 80:1062-63,

1983.

King, D.J., and Griffiths, K. Patterns in drug utilization-National and international

aspects: Psychoactive drugs 1966-80. Acta Med Scand (Suppl 683):71-

77, 1984.

Laegreid, L.; Olegård, R.; Wahlström, J.; and Conradi, N. Abnormalities in

children exposed to benzodiazepines in utero. Lancet i:108-109, 1987.

Laporte, J.R.; Capella, D.; Gisbert, R.; Porta, M.; Frati, M.E.; Garcia Santasmeses, M.P.; and Garcia Inesta, A. The utilization of sedative-hypnotic

drugs in Spain. In: Tognoni, G.; Bellantuono, C.; and Lader, M.; eds. Epidemiological Impact of Psychotropic Drugs. Amsterdam: Elsevier/North -

Holland, 1981, pp. 137-149.

Lunde, P.K.M.; Andrew, M.; and Baksaas, I. Drug utilization-an instrument in

drug research. In: Kewitz, H.; Roots, I.; and Voight, K., eds.

Epidemiological Concepts in Clinical Pharmacology. Berlin: SpringerVerlag, 1987, pp. 57-72.

Marks, R.M., and Sachar, E.J. Undertreatment of medical inpatients with narcotic

analgesics. Ann Intern Med 78:173-181, 1973.

Melander, A.; Bergdahl, U.; Hansson, H-B.; Kaij, L.; and Olovsson, L. Anxiolytika-hypnotika i öppen vård-omfattningen av bruk och missbruk.

Läkartidningen 81:3690-3693, 1984.

Melander, A., and Stenberg, P. Anxiolytic-hypnotic drugs in out-patient care:

Pronounced reduction of use, misuse and suicide following prescription

surveillance and information. Acta Pharmacol Toxicol 59 (Suppl

V):abstract 1252, 1986.

Nordic Council on Medicines. Nordic Statistics on Medicines 1975-1977. Part I.

NLN Publication No. 2. Helsinki: Nordic Council on Medicines, 1979.

Nordic Council on Medicines. Nordic Statistics on Medicines 1975-1977 . Part

II. Nordic Drug Index with Classification and Defined Daily Doses.

Publication No. 3. Oslo: Nordic Council on Medicines. 1979.

NLN

Nordic Council on Medicines. Nordic Statistics on Medicines 1978-1980 . Parts I,

II, III. NLN Publications No. 8, 9, 10. Uppsala: Nordic Council on Medicines, 1982.

Nordic Council on Medicines. Nordic Statistics on Medicines 1981-1983. Parts I,

II, III. NLN Publications No. 14, 15, 16. Uppsala: Nordic Council on

Medicines, 1986.

Nordic Council on Medicines. Nordic Statistics on Medicines 1984-1986. NLN

Publication No. 21. Uppsala: Nordic Council on Medicines, 1988:

Säwe, J. High-dose morphine and methadone in cancer patients. Clinical pharmacokinetic considerations of oral treatment. Clin Pharmacokinet 11:87-106,

1986.

Sjöqvist, F. Drug utilization. In: Tuomisto, J., and Paasonen, M.K.; eds. Clinical

Pharmacology. Vol. 5. Helsinki: Finnish Pharmacological Society, 1975,

pp. 39-50.

284
Socialstyrelsens läkemedelsavdelning. Barbiturathaltiga läkemedels medicinska

andamalsenlighet omvarderad. Information från Socialstyrelsens

läkemedelsavdelning (1):3, 1984.

Socialstyrelsens läkemedelsavdelning. Dextrometorfan receptbeläggs ånyo.

Information från Socialstyrelsens läkemedelsavdelning. (3):1-3, 1986.

Strandberg, K., and Wiholm, B-E. Regulatory decisions: Emphasis on safety

issues. Med Toxicol (Suppl 1):137- 149, 1986.

Strom, B.L., and Morse, M.L. Use of computerized databases to survey drug

utilization in relation to diagnoses. Acta Med Scand (Suppl 721):13-20,

1988.

Swedish Adverse Drug Reactions Advisory Committee (SADRAC). Overdosage

of dextromethorphan. Bulletin from SADRAC (Uppsala, Sweden) (46):3-

5, 1985.

Vikander, B.; Lindroth, A.; Tönne, U; and Borg, S. Avgiftning av bensodiazepinberoende patienter. Läkartidningen 84:3276-78, 1987.

Wessling, A. Continuous recording of drug prescribing in Sweden 1974-1983.

Methods and examples of utilization of data. Eur J Clin Pharmacol 33:7-

13, 1987.

Westerholm, B. Therapeutic audit at the national and international level. Br J Clin

Pharmac 22:55S-59S, 1986.

WHO/EURO. Consumption of Drugs, Report on a Symposium, Oslo 1969.

Document Euro 3102. Copenhagen: WHO Regional Office for Europe, 1970

Woods, J.H.; Katz, J.L.; and Winger, G. Abuse liability of benzodiazepines.

Pharmacol Rev 39:251-419, 1987.

Wright, I.S. Drug or medication. Clin Pharmacol Ther 42:245, 1987.

285
AUTHORS

Ulf Bergman, M.D., Ph.D.’

Associate Professor of Clinical Pharmacology

David Lee, M.D.1,2

Visiting Scientist

1Department of Clinical Pharmacology

Karolinska Institutet

Huddinge University Hospital

141 86 Huddinge

Sweden.

2Associate Clinical Professor

Department of Pharmacology

University of Panama

Faculty of Medicine

and

Physician-in-Chief

Pharmacotherapeutic Information Program

Medicines Commission

Social Security Institute

Apartado 1393

Panama 1

Republic of Panama.

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CHAPTER 14

Pharmacokinetic and Pharmacodynamic Drug

Interactions: Implications for Abuse Liability Testing

Edward M. Sellers, M.D., Ph.D.

Usanda Busto, Pharm.D.

Howard L. Kaplan, Ph.D.

INTRODUCTION

Every time two or more psychotropic drugs are ingested concurrently,

they will interact in some biochemical, physiological or pharmacological

fashion. Fortunately, most such interactions are unimportant events. The

important consequences of psychotropic drug interactions include the

following: an unexpected or unpredictable degree of impairment in

performing daily tasks associated with a serious potential for injury (e.g.,

driving a car, operating machinery); accidental death from overdose; the

augmentation of behavioural toxicity above that for the drugs alone (e.g.,

cognitive functions; violent behaviour, impaired formation of intent or

recognition of the consequence of one’s action, impaired memory

acquisition, retention or recall); and altered abuse liability.

The literature relating to psychotropic drug interactions is vast; however,

much of it is of limited value because it focuses on the hazards of acute

toxicity of such interaction and the relevance to abuse liability is only by

inference. Many reviews of such drug interactions exist (Grahame-Smith

1977; Haratzi and Davis 1978; Sellers et al., 1983). The interaction of

alcohol with other psychoactive drugs has been extensively studied and

reviewed (Linnoila et al., 1979; Mattila 1979; Sellers 1979, 1984; Sellers

et al., 1980a; Sellers and Busto 1982).

The complexity of abuse liability testing for single abusable drugs is

further compounded when more than one drug is present. Drug doses.

duration of use and order of administration increase the experimental

possibilities markedly. For example, at least three general combinations

of drug administration are relevant: 1) acute ingestion of single doses of

the two drugs; 2) chronic use of each drug plus a single dose of the other

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drug; and 3) chronic use of each drug together. For each of these

combinations, the at-risk populations need to be specified, e.g., drug

abusers, therapeutic users, general population. Finally, qualitative and

quantitative changes in drug effect (pharmacodynamics) can be further

confounded because drugs can alter each other’s disposition

(pharmacokinetics) (figure 1) (Ross and Gilman 1985).

In order to fully characterize a drug interaction “surface,” multiple doses

(ideally plasma free drug or biophase concentrations of the drug),

sequences, routes of administration and durations of administration or

therapy with each drug alone and together are necessary (Loewe 1953).

Theoretically, such interaction surfaces can be discontinuous; however,

this theoretical prediction has not yet been borne out in practice (Carpenter

1975). The increasing specificity and selectivity of drugs, however,

increases the likelihood such phenomena will be found.

Figure 1: Mechanisms of pharmacokinetic interaction and relationship of drug dose

and effect.

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POTENTIAL FOR DRUG INTERACTIONS IN ABUSING

POPULATIONS

The assessment of abuse liability requires identification of the at-risk

population. Theoretically, the risk of abuse is assumed to increase as one

progresses from the general population, to therapeutic users, protracted

therapeutic users, abusers of a single drug within the pharmacologic

class, to multi-drug abusers. The assessment of abuse liability of new

drugs requires conducting studies on representative samples of the at-risk

individuals. Most studies do not provide systematic validated concurrent

and past-drug use/abuse history about their subjects, hence the

appropriateness of the sample and its generalizability to the at risk abuse

population is uncertain. For practical reasons, abuse liability testing is

typically conducted in small numbers of compliant volunteers.

Table 1 summarizes the pattern of current substance abuse diagnosis in

discharged patients identified on the basis of the index diagnosis of

benzodiazepine abuse Diagnostic and Statistical Manual (DSM-III). The

patterns of tobacco and caffeine use or abuse are not known in these

individuals. Eighty-six percent (271/314) of such discharged patients

abused at least one other drug hence patients discharged with a diagnosis

of benzodiazepine abuse frequently have other concurrent abuse disorders.

Table 1. Most common other drugs of abuse in 314 consecutively

admitted benzodiazepine abusers (1978-1984)

Drug Mentions (N) Admissions (%)

1. Ethanol 142 45

2. Cannabis 82 26

3. Codeine 81 26

4. Oxycodone 64 20

5. Secobarbital 43 14

6. Amphetamine 39 12

7. Heroin 35 11

8. Butalbital 30 10

9. LSD 25 8

10. Cocaine 23 7

Total Mentions = 922

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Within the benzodiazepine abuse population the age and sex distributions

of pure (i.e., only benzodiazepine), primary (i.e., most responsible drug)

and non-primary (i.e., secondary importance) benzodiazepine abuse

populations differ (figures 2 and 3).

These data indicate that at a descriptive level drug abuse patterns are

complex and that interactions are common. Table 2 presents the pattern

of benzodiazepine use in chronic alcoholics (Busto et al., 1983).

Benzodiazepine use is common among in-patient and out-patient alcohol,

methadone, cocaine and amphetamine users (Woody et al., 1975; Stitzer

et al., 1981). With respect to assessment of abuse liability for drugs, the

labelling of such individuals as cross-dependent is not helpful since it

begs the question of prior use and exact order of use as a risk factor.

Careful studies of interactions would yield useful information with respect

to prevention, treatment and relapse prevention and would yield a better

understanding of the degree of interface between pharmacologic events

and drug-taking behaviour.

Table 2. Benzodiazepine Use in Alcoholics

TOTAL USING BENZODIAZEPINES

N N (%)1

Male 200 58 (29)

Female 61 29 (47)

Note: Objective confirmation of benzodiazepine use by urine screen

1

p<0.0005 for differences in proportion between the two sexes

PHARMACODYNAMIC INTERACTIONS

Alterations in the perceived pharmacologic effects (figure 4, upper row)

or their behavioural consequences (figure 4, lower row) are the

pharmacodynamic interactions important for abuse liability testing. Abuse

liability prediction usually focuses on directly measurable pharmacologic

features of the drug (figure 4, upper row). The consequent behaviours are

postulated to be the interactive consequence of drug effects and antecedent

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Figure 2: Age distribution of pure, primary and non-primary benzodiazepine abusers.

Figure 3: Drug dose distribution as diazepam equivalents of pure, primary and nonprimary benzodiazepine abusers.

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behaviours (Schuster et al, 1981). Some are clinically observable, e.g.

dose escalation (left column), others are more experimental in nature

(right column). Discriminative stimulus studies are the basis for inferring

the generalizability of the effect of pharmacologic cues on behaviours

(Schuster et al., 198 1). Studies in laboratory animals indicate that acute

and chronic prior administration of drugs within a class causes crosstolerance on a variety of motor, autonomic, cognitive and other drug

effects (Kalant et al., 1971). Some such changes involve metabolic

tolerance (Kalant et al., 1976; Khanna et al., 1976), but most appear to be

primarily the result of changes in CNS sensitivity. Hence kinetics, drug

effects and behaviours are modified by drug interactions.

In humans, systematic studies of the effects of graded doses of one drug

on the measured drug effects and behaviours of interest in abuse liability

testing have rarely been done. Mechanistically, such studies are important

if we want to know if prior use of a drug increases or decreases the

likelihood that a new substance will be abused (i.e., behavioural

consequence). From a drug interaction perspective the behavioural,

pharmacologic and pharmacokinetic interactions among drugs and their

importance to initiation or maintenance of drug abuse or its successful

treatment are largely unknown.

Figure 4: Drug effects and consequent behaviors affected by drug interactions.

292
PHARMACOKINETIC INTERACTIONS

Pharmacokinetic properties of a drug may contribute to abuse liability,

drug preference and persistent drug use (figure 1). These kinetic features

can be divided into those that relate primarily to acute drug effects (e.g.,

dysphoria, euphoria, liking, choice, etc.) (Griffiths and Balster 1979;

Griffiths et al., 1980; Busto and Sellers 1986) and to the development of

physical dependence and post-drug discontinuation symptoms cf.

“withdrawal” (Lukas and Griffiths 1982; Busto and Sellers 1986). Each

of these can be affected by concurrent administration of other drugs

(Sellers and Busto 1982; Busto and Sellers 1986).

Absorption and Distribution

Rapid delivery of a drug to the brain will provide optimal conditions for

reinforcement and drug readministration (Arendt et al., 1983; Greenblatt

et al., 1983; Bustoand Sellers 1986; Ator and Griffiths 1987). Drugs with

highest abuse potential typically have rapid access of an active form of

the drug to their site of action in the brain. Pro-drugs such as halazepam,

prazepam or flurazepam are slowly converted to active drug and this is

thought to account, in part, for their lesser abuse (Jaffe et al., 1983;

Griffiths et al., 1984). Therefore, route and rate of absorption tend to

shape patterns of drug abuse. In the case of oral administration, concurrent

drugs that increase dissolution rate, accelerate stomachemptying, increase

systemic bioavailability, or decrease intravascular metabolism (e.g.,

acetylation, esterases), decrease binding to serum proteins or increase

rate of brain entry will all favour increased subjective liking (or aversive

experience). Conversely, drugs that decrease gastric acidity, delay gastric

emptying (e.g., opiates) or increase protein binding would be expected to

decrease drug effects.

The study of early absorption and distribution interactions may require

very frequent blood sampling and the ability to measure drug effects

rapidly (Sellers and Busto 1982). Drugs administered intravenously or

via the lungs require especially frequent sampling to capture the

intravascular mixing phase of the interaction (Sellers and Koch-Weser

1969; Koch-Weser and Sellers 1971).

Pre-Systemic Hepatic First-Pass Drug Interaction

Theoretically, drugs with low bioavailability and high hepatic clearance

may be expected to be susceptible to the pre-systemic effects of prior

administered drugs (e.g., ethanol) (Wilkinson and Shand 1975; Sellers

and Busto 1982). The hypothesis that high extraction drugs are particularly

293
susceptible to ethanol effects has been tested with a number of drugs

(Sellers et al., 1980b, 1985; Dorian et al., 1983; 1985). For example,

studies in the isolated perfused rat liver indicate that ethanol affects the

initial rapid uptake phase into the liver and inhibits subsequent

biotransformation of propranolol, a high extraction drug, to its metabolites

(Dorian et al., 1984). Such studies suggest that the timing of the

presentation of ethanol could be important to the type and extent of

pharmacokinetic interaction. The unique positioning of the liver between

gut and systemic circulation means that drugs passing through the liver

primed by ethanol will be affected by inhibition of oxidative drug

metabolism, inhibition of uptake and binding within the liver, changes in

liver blood flow or a combination of these factors (Sellers et al., 1980b).

Cimetidine, which also inhibits P450-mediated drug biotransformation

and decreases liver blood flow, causes an increase in the plasma

concentrations of lidocaine and diazepam during the distribution or

absorption phase.

However, even “low extraction” drugs can demonstrate that they are

susceptible to a pre-systemic absorptive phase interaction with ethanol.

Ethanol, for example, causes a 96 percent relative increase in diazepam

concentration at 18 minutes after intravenous administration and a 100

percent increase 15 minutes after oral diazepam administrationcompared

with a diazepam-alone condition (MacLeod et al., 1977; Sellers et al.,

1980a; Sellers 1984). The intravenous data are particularly interesting

since they reflect the impact of altered hepatic clearance on a drug during

its plasma and tissue distribution phase. After intravenous administration

of drug, altered hepatic clearance of drug can be important during the

distribution phase because of the high relative blood flow to liver (i.e.,

approximately 25 to 30 percent of cardiac output) (Sellers et al., 1980b).

Therefore, the influence of ethanol and other inhibitors of drug metabolism

or hepatic uptake on pharmacokinetics of drugs can be best understood

by considering three overlapping phases: systemic absorption, distribution

and elimination.

Physical Dependence and Discontinuation Symptoms

The rate of appearance and severity of withdrawal symptoms depends

upon the balance of those factors which determine the degree of physical

dependence and apparent rate of drug removal from its site of action. The

removal of drug can be due to metabolism. excretion or displacement by

an antagonist. The longer a drug’s half-life (i.e., high volume of distribution

and low total body clearance), the greater the likelihood of the development

of physical dependence. The shorter the half-life, the earlier and more

294
severe will be the withdrawal (Busto and Sellers 1986; Busto et al., 1986;

Cappell et al., 1987).

Antagonists are the most dramatic way of shortening a drug’s half-life in

the biophase. As a result they have an important diagnostic role in

establishing the presence of physical dependence in laboratory animals

and humans (Lukas and Griffiths 1982). For example, Ro15-1788

precipitates withdrawal from benzodiazepines in baboons and humans.

Similarly, naloxone and other opiate antagonists and partial agonists do

the same for opiates. Such interactions dramatically unmask the underlying

adaptive changes,

Increasing Half-Life, Decreasing Clearance

A number of drugs consistently decrease drug biotransformation by hepatic

cytochrome enzymes and prolong half-life, e.g., disulfiram, cimetidine,

acute ethanol, chloramphenicol, oral contraceptives (Sellers 1984; Murad

and Gilman 1985). For example, caffeine half-life is 10.4 hours in women

on oral contraceptives compared to 4 hours in female controls. The

clinical importance for caffeine abuse and liability testing is uncertain.

A decrease in total clearance will be associated with a proportionate

increase in average steady state free drug concentration if dose is kept

constant (Benet and Sheiner 1985). However, if dose has been “titrated”

by the subject to a preferred plasma drug concentration it is conceivable

that the ingested drug dose may be decreased by a decrease in drug

clearance. Such an interaction then could become part of a treatment

approach (Bendayan et al., 1988). For high first-pass drugs, inhibitors

can also be expected to increase systemic bioavailability after oral

administration. Greater effects from single doses can be expected. With

respect to the longer half-life (assuming the volume of distribution is

constant), the inter-dose area under the curve (AUC) is increased by

decreased clearance and fewer inter-dose withdrawal symptoms should

occur. Upon discontinuation a more delayed, and less severe set of

symptoms should occur. To the extent such symptoms are a cue or trigger

for persistent drug use, drug use should decrease (Busto and Sellers 1986).

Decreasing Half-Life, Increasing Clearance

Phenobarbital, chronic ethanol, tobacco smoking, rifampin or

carbamazepine can double or triple total clearance of some abused drugs

(Murad and Gilman 1985). The consequent shortening in half-life and

decrease in average steady state drug concentration should be associated

with some or all of the following: a decrease in drug effect (unless the

295
metabolites are more active or toxic than the parent compound), a decrease

in total and free drug concentration; a compensatory increase in drug dose

self-administered; shortening of the dose interval; an increase in number

and severity of withdrawal symptoms and greater difficulty in

discontinuing drug. Once again, the clinical importance of such

phenomena is unknown. Of these, heavy smoking deserves particular

attention (Sellers et al., 1983). The biotransformation of caffeine, nicotine

and other xanthines may be affected by smoking and enzyme induction.

The extent of interindividual variation in caffeine “tolerance” and

discontinuation symptoms may in part be explained by confounding codrug use, e.g., ethanol, smoking, barbiturates, etc.

EXPERIMENTAL EXAMPLES

The interactions of ethanol with several drugs will be used to illustrate the

specific principles reviewed above.

Acute Ethanol Ingestion and Single Doses of a Benzodiazepine

Diazepam absorption may be delayed slightly if alcohol is given 30 minutes

before the dose of diazepam. The apparently slight differences in order

and timing of drug and ethanol administration may explain other

discrepancies among reported studies of the ethanol-diazepaminteractions

(Sellers and Busto 1982; Sellers 1984).

MacLeod and associates showed that 0.5 g/kg of ethanol in a 20 percent

v/v oral solution resulted in diazepam levels about 30 percent higher after

ethanol than with diazepam alone, although the increases were not as

great when the alcohol and diazepam were co-administered (MacLeod et

al., 1977). No significant changes in diazepam absorption rate or plasma

elimination rate were found up to 8 hours post-drug. Since the

bioavailability of diazepam is normally high, the observed increase in

peak diazepam could arise from an ethanol-mediated decrease in initial

diazepam distribution volume. This possibility is attractive because

ethanol is metabolized relatively quickly compared with diazepam; hence,

any acute ethanol-mediated effects are transient and occur during a phase

of diazepam disposition characterized and predominated by absorption

and tissue distribution.

A balanced cross-over study confirmed that ethanol increases

concentrations of intravenously administered diazepam by inhibiting the

hepatic intrinsic clearance of free diazepam and altering diazepam and

desmethyldiazepam free fraction (Sellers et al., 1980a). These observations

296
clarify the pharmacokinetic mechanism of ethanol-diazepam interaction

and suggest that a similar mechanism accounts for changes in disposition

with other benzodiazepines.

Chronic Ethanol Ingestion and Benzodiazepines

Considerable basic pharmacological research suggests that acute ethanol

exposure inhibits microsomal mixed function oxidase activity (see

preceding section) and chronic administration stimulates drug metabolism

(Sellers et al., 1983).

In recently abstinent chronic alcoholics, the peak and AUC for diazepam

are lower after oral diazepam than in control subjects (Sellman et al.,

1975a). Whether these results are due to a decrease in serum albumin

with an increase in the volume of diazepam distribution, decreases in

bioavailability or increased biotransformation is not known because halflife could not be accurately estimated with the limited number and brief

period of diazepam blood level measurements. A comparable study in

chronic alcoholics given intravenous diazepam also showed decreased

peak diazepam and AUC up to 12 hours post-dose and lower

desmethyldiazepam levels, suggesting an increased initial volume of

distribution (Sellman\] et al., 1975b).

Sellers and colleagues (1978) reported the pharmacokinetics of

chlordiazepoxide during alcohol withdrawal in six male chronic alcoholics

(defined as individuals who ingested more than 80 g of ethanol per day

for at least 10 years). These subjects received 25 mg of chlordiazepoxide

every 6 hours for 6 days. Steady state plasma levels of chlordiazepoxide

were decreased on day 6 compared to levels on day 2 of withdrawal,

suggesting increased chlordiazepoxide clearance. This is consistent with

a return to normal enzymatic activity after the inductionof mixed function

oxidase enzymes.

Interpretation of these studies is difficult because of concurrent changes

in drug free fraction (Greenblatt et al., 1982; Sandor et al., 1983). Increased

free fractions caused by fatty acids or competing drugs will decrease the

average stated state drug concentration in plasma. The net free drug

concentration may be unchanged (Greenblatt et al., 1982). However,

important enhancement of effect based on high free concentration can

occur during the acute distribution and inter-dose distribution phase

(Sellers 1986).

The clinical consequence of an increased drug clearance is that patients

will have a lower average steady state drug level and a lesser therapeutic

297
or toxic effect. The clinical implication of increased benzodiazepine

clearance is further confused because there is cross-tolerance between

ethanol and benzodiazepines, suggesting that chronic ethanol ingestion

might not only decrease blood levels but also decrease central nervous

system sensitivity to the benzodiazepines. Of course, the typical pattern

of ethanol ingestion is alternatively intoxication and abstinence so that a

fluctuating mixture of kinetic and dynamic effects can be predicted in the

usual field setting.

Acute Amitriptyline-Ethanol

Amitriptyline has clinically important interactions with ethanol (Dorian

et al., 1983). Five healthy volunteers received 25 mg of amitriptyline

orally, preceded by 1 hour and followed for 8 hours by oral ethanol (or

juice), doses adjusted to achieve and maintain blood ethanol concentrations

of 800 mg/l. In the presence of ethanol, amitriptyline free plasma

concentrations were increased by a logarithmic mean of 205 percent, 186

percent and 127 percent at 1.5, 2 and 2.5 hours, respectively, and

amitriptyline free AUC0-8h was increased by 48 percent ± 13 percent

(mean ± SEM) (t = 5.21, p < 0.01). Nortriptyline total AUC0-8h was

increased by 26.6 percent ± 12 percent (mean ± SEM) (t = 2.2 1, p < 0.09).

At the time of peak amitriptyline plasma concentrations, mean postural

sway was increased over baseline by 92 percent with, and 2 percent

without ethanol; likewise, mean short term memory (word recall) was

decreased over baseline by 71 percent with, and 37 percent without,

ethanol. Ethanol increases free amitriptyline plasma concentrations most

dramatically during the period of drug absorption; this is due to a decrease

in amitriptyline hepatic clearance, resulting in decreased first-pass

extraction. Together with the pharmacodynamic interaction, the kinetic

changes provide a rationale for the greater than expected toxicity of this

combination and its deleterious effects on psychomotor skills.

Acute Ethanol-Zimelidine

Ethanol decreases the rate of biotransformation of zimelidine to

norzimelidine by 46 percent, but the areas under the curve (AUCs) of

zimelidine, norzimelidine, and their total concentration over 8 hours are

not altered by ethanol (Naranjo et al., 1984a; Sellers and Naranjo 1988).

Ethanol induced impairments in memory, body sway and a manual tracking

task were further enhanced by zimelidine as was the ethanol induced

decrease in friendliness. These potentiation effects include decreases in

postural stability on one foot, recall memory, and “friendliness,” but

analysis of individual subjects shows that the effect of zimelidine with

ethanol was often inconsistent in direction among subjects. By this

298
analysis, significant zimelidine-ethanol effects in a consistent direction

include manual tracking and the “friendliness” rating. There were also

inconsistent, but individually significant, results for the “sedation” rating

scale. In this experiment, friendliness decreased further when zimelidine

was combined with ethanol, indicating that zimelidinemodifies the effect

of ethanol on mood and, therefore, that the drugs interact centrally. Since

ethanol has positive and aversive effects, it is possible that zimelidine acts

by modifying the balance of such effects, either by making the subjects

perceive ethanol as less reinforcing, more aversive, or both, which might

lead to decreased ethanol intake. However, we must be cautious in

interpreting such mood effects since effects of ethanol on mood not only

depend on dose but also on the psychophysiologic state of the subject and

the context in which drinking occurs.

Chronic Fluoxetine, Amitriptyline and Ethanol

Several serotonin uptake inhibitors decrease alcohol consumption but

not smoking and also decrease weight (Naranjo and Sellers 1988). Such

effects may be mediated through effects on desire to drink and initiation

of drinking (Naranjo and Sellers 1988; Sellers and Naranjo 1988). A

study of chronic amitriptyline and fluoxetine and their interaction with

ethanol has been conducted (Hamilton et al., 1987; Sellers and Naranjo

1988). Ethanol has no apparent effect on the pharmacokinetics of

chronically administered fluoxetine or amitriptyline (Hamilton et al.,

1987; Sellers and Naranjo 1988). The deleterious effects of ethanol on

memory, manual tracking, body sway, intoxication and sedation were not

modified by either fluoxetine or amitriptyline. Interestingly, chronic

fluoxetine may have had some subtle effects on mood as reflected in the

POMS (decreased friendliness) (Hamilton et al., 1987). Possibly such

mood effects may be the reflectors of drug effects that correspond to the

“urge to drink,” “craving” or sense of “self-worth” or “need” for chemical

reinforcement. Much further work is needed. If the initial observations

are supported and extended they could serve as a basis for looking for

generalization of drug abuse liability across patient populations.

NEW TREATMENT APPROACHES AND DRUG

INTERACTIONS

Pharmacotherapy that could prevent or decrease the risk of drug abuse or

could decrease non-therapeutic drug use would likely be widely accepted.

Substitution therapy with nicotine-containing resin (Nicorette®) or with

methadone for heroin abusers is well accepted despite evidence that the

effects of drug alone are limited in size. Several additional therapeutic

299
approaches utilizing drug interactions deserve consideration, to decrease

the probability of drug-taking behaviour or to decrease desire to use drug.

Such approaches are properly considered drug interactions because prior

drug abuse with its physiologic/neurochemical and behavioural

consequences is required for the putative effect to occur.

Several possible interaction mechanisms need consideration:

1. Substitute a safer or kinetically more suitable drug or dose delivery

form (e.g., nicotine patch, methadone maintenance).

2. Block the reinforcing effects of drug (e.g., naloxone, naltrexone).

3. Decrease the perceived effects of drug that reinforce behaviour.

4. Induce aversive reaction upon drug use (e.g., disulfiram).

5. Suppress target symptoms (e.g., anxiety, depression) which may

prompt or sustain drug use.

6. Decrease the desire to initiate or continue drug use.

7. Cause non-specific side effects, e.g., nausea, which decrease the

interest in consummatory behaviours.

8. Modify the kinetics of an abusable drug (e.g., slow absorption).

Formalization of the factors that motivate drug use appear in several

theories (i.e., withdrawal model; compensatory model; opponent-process

model). These have been recently reviewed and re-examined (Baker et

al., 1988). The conclusions of this review are pertinenttoconceptualizing

potential therapeutic strategies for use of drugs. Notwithstanding detailed

differences in the major theories of why drugs are repeatedly or persistently

used, all share in common (supported by much experimental, laboratory

and clinical data) the idea that the desire to use drugs “reflects the presence

of a drug-acquisitive motivational state.” All three theories also involve

the idea that desire for drugs is produced by drug-free related processes

(cf., conditioned or physical withdrawal). Baker argues that urges may

be elicited associatively (cf., directly) and non-associatively (cf., indirectly)

by pharmacologic and non-pharmacologic cues that have motivational

effects similar to unconditioned and conditioned agonist effects of drug.

Baker further proposes that “urges” can be best viewed as affects (moods)

with a wide qualitative and quantitative range. Fluctuations within the

range can also occur. Such a view reconciles a large body of empirical

clinical data and at least offers a framework for expecting identical

behaviours (e.g., alcohol or drug consumption) triggered by positive and

negative affects.

The searchforeffective drug treatments of alcoholism and alcohol-related

problems centres on the potential value of serotonergic (5-HT) drugs.

Recent reports of four clinical trials indicate that serotonin uptake inhibitors

300
(zimelidine, citalopram, viqualine, fluoxetine) decrease average alcohol

consumption in humans by 10 to 20 percent (Naranjo et al., 1984b, 1987;

Naranjo and Sellers 1988; Sellers and Naranjo 1988). These studies,

conceptualized on the basis of the neurochemical modulation of

consummatory behaviours, renew the hope that drugs may play an

important role in substantial treatment progress in this field. Recent

observations that 5-HT3 antagonists can normalize drug withdrawal

anxiety-like behaviour (Brittain et al., 1987; Costall et al., 1987, 1988;

Kilpatrick et al., 1987; Jones et al., 1988) and decrease ethanol preference

(Sellers et al., 1988) are important. In terms of the serotonin uptake

inhibitors and 5-HT3 antagonists, the incorporation of a careful

consideration of the urges-affect-mood complex motivating drinking in

drug abusers seems useful.

CONCLUSIONS

Since drug abuse has behavioural antecedents and consequences and

rarely involves a single drug, a conceptualization incorporating drug

interactions and multi-drug use is needed. Since abuse of a single drug

is rare, drug interactions reflect the complex reality of drug use behaviour.

The kinetic and dynamic aspects of drug interactions in abuse liability

testing have been largely ignored. When more than one psychoactive

drug is used, kinetic and dynamic interactions are inevitable. Apart from

acute toxicity, the implications for behaviours such as risk to take drug

and to stop using are rarely known. There is a reasonable probability that

abuse liability can be decreased by other drugs and more effective

discontinuation strategies developed.

1. The pharmacokinetic determinants of the abuse liability by individuals

need much more study. The development of pharmacokineticpharmacodynamic models to better understand drug effects of abuse

drugs should have high priority. Highly abused drugs (e.g., cocaine)

are particularly useful but difficult to study model compounds. Such

studies will require unique multi-disciplinary study teams.

2. The effects of prior and co-administration on abuse liability within a

class of drugs and in some cases across classes are appropriate.

3. Detailed validated prior and current drug use including alcohol, caffeine

and tobacco should be included in abuse liability studies. Agreement

of a standard within the field could help.

301
4. More consideration should be given to how drug interactions could be

used to therapeutic advantage:

a) to decrease abuse liability and/or decrease the risk of toxicity; and

b) to directly modify the desire to use a drug.

5. It is probable that interactions which decrease rate of drug absorption

will lessen the probability a drug will be abused.

REFERENCES

Arendt, R.M.; Greenblatt, D.J.; de Jong, R.H.; Bonin, J.D.; Abemethy, D.R.;

Ehrenberg. B.L.; Giles, G.; Sellers, E.M.; and Shader, R.I. In vitro

correlates of benzodiazepine cerebrospinal fluid uptake,

pharmacodynamic action and peripheral distribution. J Pharmacol Exp

Ther 227:98-100, 1983.

Ator, N.A., and Griffiths, R.R. Self-administration of barbiturates and

benzodiazepines: A review. Pharmacol Biochem Behav 27:391-398,

1987.

Baker, T.B.; Morse, E.; and Sherman, J.E. The motivation to use drugs: A

psychobiological analysis of urges. In: Rivers, C., ed. The Nebraska

Symposium on Motivation: Alcohol Use and Abuse. Lincoln: University

of Nebraska Press, 1988, in press.

Bendayan, R., Sullivan, J., Shaw, C., Frecker, R.C. and Sellers, E.M. Effect of

H2-receptor antagonists on nicotine disposition. Clin Pharmacol Ther

43(2):124, 1988.

Benet, L.Z., and Sheiner, R.B. Pharmacokinetics: The dynamics of drug

absorption, distribution and elimination. The Pharmacological Basis of

Therapeutics. Seventh Ed. New York: MacMillan Publishing Company,

1985, pp. 3-34.

Brittain, R.T.; Butler, A.; Coates, I.H.; Fortune, D.H.; Hagan, R.; Hill, J.M.;

Humber, D.C.; Humphrey, P.P.A.; Ireland, S.J.; Jack, D.J.; Jadan, C.C.;

Oxford, A.; Straughan, D.W.; and Tyers, M.B. GR38032F, a novel

selective 5-HT3 receptor antagonist. Br J Pharmacol 90:87P, 1987.

Busto, U., and Sellers, E.M. Pharmacokinetic determinants of drug abuse and

dependence: A conceptual perspective. Clin Pharamcokin 11:144-153,

1986.

Busto, U.; Sellers, E.M.; Naranjo, C.A.; Cappell, H.; Sanchez-Craig, M.; and

Sykora, K. Withdrawal reaction after long-term therapeutic use of

benzodiazepines. N Engl J Med 315(14):854-859, 1986.

Busto, U.; Simpkins, J.; Sellers, E.M.; Sisson. B.; and Segal. R. Objective

determination of benzodiazepine use and abuse in alcoholics. Br J Addict

78:429-435, 1983.

Cappell, H.; Busto, U.; Kay, G.; Naranjo. C.A.. Sellers. E.M.. and Sanchez-Craig,

M. Drug deprivation and reinforcement by diazepam in a dependent

population. Psychopharmacology 91: 154-160, 1987.

302
Carpenter, J.A. Some methodological considerations in research on joint action.

In: Sellers, E.M., ed. Clinical Pharmacology of Psychoactive Drugs.

Toronto: Addiction Research Foundation, 1975, pp. 147-164.

Costall, B.; Domeney, A.M.; Naylor, R.J.; and Tyers, M.B. Effects of the 5-HT3

receptor antagonist, GR38032F, on raised dopaminergic activity in the

mesolimbic system of the rat and marmoset brain. Br J Pharmacol 92:881,

1987.

Costall, B.; Naylor, R.J.; and Tyers, M.B. Recent advances in the

neuropharmacology of 5-HT3 agonists and antagonists. Rev Neurosci

2(1):41-66, 1988.

Dorian, P.; Sellers, E.M.; Kaplan, H.L; Carruthers, G.; Hamilton, C.; and Khouw,

V. Ethanol-induced inhibition of hepatic uptake of propranolol in

perfused rat liver and in man. Eur J Clin Pharmacol 27:209-215, 1984.

Dorian, P.; Sellers, E.M.; Kaplan, H.L.; Hamilton, C.; Greenblatt, D.J.; and

Abemethy, D. Triazolam and ethanol interaction: Kinetic and dynamic

consequences. Clin Pharmacol Ther 37(5):558-562, 1985.

Dorian, P.; Sellers, E.M.; Reed, K.L.; Warsh, J.J.; Hamilton, C.; Kaplan, H.L.;

and Fan, T. Amitriptyline and ethanol: Pharmacokinetic and

pharmacodynamic interaction. Eur J Clin Pharmacol 25:325-331, 1983.

Grahame-Smith, D.G. General aspects of drug interactions in

psychopharmacology. In: Grabame-Smith, D.G., ed. Drug Interactions.

Baltimore: University Park Press, 1977, pp. 147-157.

Greenblatt, D.J.; Arendt, R.M.; Abemethy, H.G.; Sellers, E.M.; and Shader, R.I.

In vitro quantitation of benzodiazepine lipophilicity: Relation to in vivo

distribution. Br J Anaesth 55:985, 1983.

Greenblatt, D.J.; Sellers, E.M.; and Koch-Weser, J. Importance of protein

binding for the interpretation of serum or plasma drug concentrations. J

Clin Pharmacol 22:259-263, 1982.

Griffiths, R.R., and Balster, R.L. Opioids: Similarity between evaluation of

subjective effects and animal self-administration results. Clin Pharmacol

Ther 25:611-617, 1979.

Griffiths, R.R.; Bigelow, G.E.; Liebson, I.; and Kalissak, J.E. Drug preference in

humans: Double-blind choice comparison of pentobarbital, diazepam and

placebo. J Pharmacol Exp Ther 215:649-661, 1980.

Griffiths, R.R.; MacLeod, D.R.; Bigelow, G.E.; Liebson, L.A.; Roache, D.L.; and

Chung, S. Comparison of diazepam and oxazepam. Preference, liking

and extent of abuse. J Pharmacol Exp Ther 229:501-508, 1984.

Hamilton, C.A.; Sellers, E.M.; Sullivan, J.T.; Kadlec, K.; Kaplan, H.L.; and

Naranjo, C.A. Interactions of fluoxetine and amitriptyline with ethanol.

Clin Pharmacol Ther 41:231, 1987.

Haratzi, J.S., and Davis, J.M. Psychotropic drug interactions. In: Clark, W.G.,

and del Giudice J., eds. Principles of Pharmacology. 2nd ed. New York:

Academic Press, 1978, pp. 495-510.

Jaffe, J.H.; Ciraulo, D.A.; Nies, A.; Dixon, R.B.; and Monroe, L.L. Abuse

potential of halazepam and diazepam in patients recently treated for acute

alcohol withdrawal. Clin Pharmacol Ther 34:623-630, 1983.

Jones, B.J.; Costall, B.; Domeney, A.M.; Kelly. M.E.; Naylor. R.J.; Oakley, N.R.;

and Tyers, M. The potential anxiolytic activity of GR38032F, a 5-HT3

receptor antagonist. Br J Pharmacol 93:985-993, 1988.

303
Kalant, H.; Khanna, J.M.; Lin, G.Y.; and Chung, S. Ethanol—a direct inducer of

drug metabolism. Biochem Pharmacol 25:337-442, 1976.

Kalant, H.; Le Blanc, A.E.; and Gibbins, R.J. Tolerance to, and dependence on,

some non-opiate psychotropic drugs. Pharmacol Rev 23:135-191, 1971.

Khanna, J.M.; Kalant, H.; Yee, Y.; Chung, S.; and Siemens, A.J. Effect of

chronic ethanol treatment on metabolism of drugs in vitro and in vivo.

Biochem Pharmacol 25:329-335, 1976.

Kilpatrick, G.J.; Jones, B.J.; and Tyers, M.B. Identification and distribution of 5-

HT3 receptors in rat brain using radioligand binding. Nature 330:746-748,

1987.

Koch-Weser, J., and Sellers, E.M. Medical progress. Drug interactions with

coumarin anticoagulants. N Eng J Med 285:487-498 (Part 1); 547-558

(Part 2), 1971.

Linnoila, M.; Mattila, M.J.; and Kitchell, B.S. Drug interactions with alcohol.

Drugs 18:299-311, 1979.

Loewe, S. The problem of synergism and antagonism of combined drugs.

Arzneim Forsch 3:285-290, 1953.

Lukas. S.E., and Griffiths, R.R. Precipitated withdrawal by a benzodiazepine

receptor antagonist (Ro15-1788) after 7 days of diazepam. Science

217:1161-1163, 1982.

MacLeod, S.M.; Giles. H.G.; Patzalek, G.; Thiessen, J.; and Sellers, E.M.

Diazepam actions and plasma concentrations following ethanol ingestion.

Eur J Clin Pharmacol 11:345-349, 1977.

Mattila, M.J. Pharmacokinetic aspects of drug-alcohol interaction. In: Olive, G.,

ed. Advances in Pharmacology and Therapeutics. Vol. 8. Oxford:

Pergamon Press, 1979, pp. 223-233.

Murad, F., and Gilman, A.G. Drug Interactions. In: Gilman, A.G.; Goodman,

L.S.; Rall, T.W.; and Murad, F., eds. The Pharmacological Basis of

Therapeutics. Seventh Ed. New York: MacMillan Publishing Company,

1985, pp. 1734-1750.

Naranjo, C.A., and Sellers, E.M. Serotonin uptake inhibitors attenuate ethanol

intake in humans. Australian Drug Alcohol Rev 7(1):109-112, 1988.

Naranjo, C.A.; Sellers, E.M.; and Lawrin, M.O. Modulation of ethanol intake by

serotonin uptake inhibitors. J Clin Psychiatry 47 (4, Suppl.):16-22, 1986.

Naranjo, C.A.; Sellers, E.M.; Kaplan, H.L.; Hamilton, C.; and Khouw, V. Acute

kinetic and dynamic interactions of zimelidine with ethanol. Clin

Pharmacol Ther 36:654-660, 1984a.

Naranjo, C.A.; Sellers, E.M.; Roach, C.A.; Woodley, D.V.; Sanchez-Craig, M.;

and Sykora, K. Zimelidine-induced variations in alcohol intake by

nondepressed heavy drinkers. Clin Pharmacol Ther 35:373-381, 1984b.

Naranjo, C.A.; Sellers, E.M.; Sullivan, J.T.; Woodley, D.V.; Kadlec, K.; and

Sykora, K. The serotonin uptake inhibitor citalopram attenuates ethanol

intake in humans. Clin Pharmacol Ther 41:266-274. 1987.

Ross, E.M., and Gilman, A.G. Pharmacodynamics: Mechanism of drug action

and the relationship between drug concentration and effect The

Pharmacological Basis of Therapeutics. Seventh Ed New York:

MacMillan Publishing Company. 1985. pp. 35-48.

304
Sandor, P.; Naranjo, C.A.; Khouw, V.; and Sellers, E.M. Variations in drug free

fraction during alcohol withdrawal. Br J Clin Pharmacol 15:481-486,

1983.

Schuster, C.R.; Fischman, M.W.; and Johanson, C.E. Internal stimulus control

and subjective effects of drugs. In: Thomson, T., and Johanson, C.E., eds.

Behavioral Pharmacology of Human Drug Dependence. National Institute

on Drug Abuse Monograph No. 37, DHHS Pub. No. (ADM) 81-1137,

Washington, D.C.: US. Govt. Print. Off., 1981, pp. 116-129.

Sellers, E.M. Mechanism of alcohol interactions with drugs. In: Avogaro, P.;

Sirtori, C.R.; and Tremoli, E., eds. Metabolic Effects of Alcohol.

Amsterdam: Elsevier-North Holland Medical Press, 1979, pp. 113-117.

Sellers, E.M. Ethanol-psychotropic drug interactions: Pharmacokinetics.

Psychopharmacol Bull 20(3):497-499, 1984.

Sellers, E.M. Drug displacement interactions: A case study of the

phenylbutazone-warfarin interaction. In: Reidenberg, M.M., and Erill, S.,

eds. Drug-Protein Binding. New York: Praeger Scientific, 1986, pp.

257-273.

Sellers, E.M., and Busto, U. Benzodiazepines and ethanol: Assessment of the

effects and consequences of psychotropic drug interactions. J Clin

Psychopharmacol 2(4):249-262, 1982.

Sellers, E.M., and Koch-Weser, J. Protein binding and vascular activity of

diazoxide. N Engl J Med 281:1141-1145, 1969.

Sellers, E.M., and Naranjo, C.A. Interaction of serotonin uptake inhibitors with

ethanol. Australian Drug Alcohol Rev 7(1):113-116, 1988.

Sellers, E.M.; Frecker, R.C.; and Romach, M.K. Drug metabolism in the elderly:

Confounding of age, smoking, and ethanol effects. Drug Metab Rev

14(2):225-250, 1983.

Sellers, E.M.; Giles, H.G.; Greenblatt, D.J.; and Naranjo, C.A. Differential

effects on henzodiazepine disposition by disulfiram and ethanol. Arzneim

Forsch 30(1):882-886, 1980b.

Sellers, E.M.; Greenblatt, D.J.; Zilm, D.H.; and Degani, N. Decline in

chlordiazepoxide plasma levels during fixed-dose therapy of alcohol

withdrawal. Br J Clin Pharmacol 6:370-372, 1978.

Sellers, E.M.; Hamilton, C.A.; Kaplan, H.L.; Degani, N.C.; and Foltz, R.L.

Pharmacokinetic interaction of propoxyphene with ethanol. Br J Clin

Pharmacol 19:398-401, 1985.

Sellers, E.M.; Kaplan, H.L.; Lawrin, M.O.; Somer, G.; Naranjo, C.A.; and

Frecker, R.C. The 5-HT3

 antagonist GR38032F decreases alcohol

consumption in rats. Abstracts of 18th Annual Meeting of the Society for

Neuroscience 14 (Part 1):41, 1988.

Sellers, E.M.; Naranjo, C.A.; Giles, H.G.; Frecker, R.C.; and Beeching, M.

Intravenous diazepam and oral ethanol interaction. Clin Pharmacol Ther

28(5):638-645, 1980a.

Sellman, R.; Kanto, J.; Raijola, E.; and Pekkarinen, A. Human and animal study

on elimination from plasma and metabolism of diazepam after chronic

alcohol intake. Acta Pharmacol Toxicol 36:33-38, 1975a.

Sellman, R.; Pekkarinen, A.; Kangas, L.; and Raijera, E. Reduced concentrations

of plasma diazepam in chronic alcoholic patients following an oral

administration of diazepam. Acta Pharmacol Toxicol 36:25-32, 1975b.

305
Stitzer. M.L.; Griffiths, R.R.; McLellan, A.T.; Grabowski. J.; and Hawthorne,

J.W. Diazepam use among methadone maintenance patients: Patterns and

dosage. Drug Alcohol Depend 8:189-199, 1981.

Wilkinson, G.R., and Shand, D.G. A physiological approach to hepatic drug

clearance. Clin Pharmacol Ther 18:377-390, 1975.

Woody, G.E.; Mintz, J.; Otlare, K.; O’Brien, C.P.; Greenstein, R.A.; and

Margrove, E. Diazepam use by patients in a methadone program. How

serious a problem? J Psychedelic Drugs 7:373-370. 1975.

AUTHORS

Edward M. Sellers, M.D., Ph.D.1,2

Professor of Pharmacy and Medicine

Usanda Busto, Pharm. D.1.

2

Assistant Professor

Howard L. Kaplan, Ph.D.1

Senior Systems Analyst

1

Psychopharmacology Program

Clinical Institute

Addiction Research Foundation

2Departments of Pharmacology and Medicine and

Faculty of Pharmacy

University of Toronto

33 Russell Street

Toronto, Ontario M5S2S1.

Address correspondence to: Dr. E.M. Sellers

33 Russell Street

Toronto, Ontario M5S 2S1

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CHAPTER 15

Promising New Biological and Behavioral Correlates

of the Reinforcing Properties of Drugs

Jack H. Mendelson, M.D.

Nancy K. Mello, Ph.D.

Scott E. Lukas, Ph.D.

Bryan T. Woods, M.D.

Siew K. Teoh, M.D.

INTRODUCTION

The pioneering studies of human drug abuse liability (Himmelsbach

1937a, b; Martin and Fraser 1961) involved volunteer participation by

drug dependent men who were incarcerated in a federal penal institution.

These volunteers also served as subjects in studies of biological and

behavioral effects of abused substances for development of instruments

such as the Addiction Research Center Inventory (ARCI)(Hill et al.,

1963). The subjects who participated in this research were appropriately

defined as “high risk” persons as a consequence of their drug abuse

related problems prior to their incarceration. The logic of evaluating drug

abuse liability for new compounds with such high risk persons is

compelling, but it is unlikely that similar studies will be carried out in the

future because of social, political and ethical concerns.

Subjects who participated in the original drug abuse related assessments

carried out at the Addiction Research Center more often reported

preference for a single drug than a history of polydrug abuse. In contrast

polydrug abuse is highly prevalent among contemporary substance

abusers and predictions about risk for polydrug abuse may not be

generalized from studies of individuals who exhibit a single or a unique

drug use preference. Moreover, we cannot assume that absence of a past

history of substance abuse of any individual indicates lack of vulnerability

for substance abuse problems for that individual in the future. There is

now compelling evidence that a number of factors may predict occurrence

of substance abuse problems long before the individual begins to use his

or her substance of abuse. There is also increasing evidence that there

may be a number of biologic markers which may be employed for

307
prediction of risk of substance abuse by individuals who have not, as yet,

experienced any substance abuse problems. Although the discovery of

biologic and behavioral factors which predict risk for substance abuse are

probabilistic in nature and can rarely be used to identify a specific

individual at risk, consideration of these factors may be important for the

recruitment and selection of subjects who volunteer to participate in

human drug testing paradigms.

SOCIAL AND BEHAVIORAL FACTORS WHICH MAY COVARY WITH RISK FOR SUBSTANCE ABUSE

Psychosocial and behavioral factors which may contribute to risk for

substance abuse have been discussed by Nurco and by Kellam et al. in the

1981 Proceedings of Problems of Drug Dependence (Nurco 1982;

Kellam et al., 1982). There is reasonably good evidence that antisocial

and aggressive behavior are important predictors of substance abuse

especially among males (Kellam et al., 1982). The relationship between

shyness, aggressiveness, learning problems and substance use has been

carefully delineated in longitudinal studies carried out by Kellam and his

associates who found that:

as early as first grade there are clearly identifiable antecedents

leading to specific outcomes at least as far as 10 years in the

future. Briefly, the findings are:

1. First-grade learning problems are the strongest predictor

of teenage psychiatric symptoms for males. This effect is

less clear for females. Learning problems do not predict

substance use.

2. Among both females and males, higher scores on firstgrade readiness and IQ tests in general lead to fewer

psychiatric symptoms but more substance use 10 years

later. However, the relationship of some symptoms to

early cognitive performance appears to be more complex,

showing a curvilinear relationship, with the level of

teenage symptoms decreasing as one moves from the

lowest to the average first-grade scores, but increasing

with the highest scores.

3. Shyness among first-grade males (but not females) clearly

inhibits substance use at age 16 or 17. For both males and

308
females, however, early shyness seems to predict higher

levels of at least some teenage symptoms.

4. First-grade aggressiveness without shyness is a strong

predictor of increased teenage substance use by males

(not by females), but it is now associated with later

psychopathology.

5. The combination of shyness and aggressiveness in firstgrade males is associated with even more frequent use of

substances (especially of cigarettes) than aggressiveness

alone.

6. First-grade psychiatric symptoms as measured by both

mothers’ reports and clinicians’ observations predict

later symptoms for females but not for males.

7. With one seemingly minor exception, the SAS and PWB

predictors do not interact in their effects on later substance

use and pyschiatric symptoms.

8. The two outcome areas of psychiatric symptoms and

substance use are empirically as well as conceptually

distinct. They are barely correlated among male and

female adolescents, and the developmental paths leading

to them are very different.

9. There are strong differences between males and females

in the developmental paths leading to adolescent outcomes.

Early SAS has stronger predictive power for both later

SAS and PWB among males (points 1,3,4 and 5), whereas

early PWB shows continuity with later PWB only for

females (point 6). The measures of cognitive achievement

have similar effects for both sexes {point 2).

(Kellam et al., 1983, pp. 17-51)

Data obtained by Kellam and his associates suggest that substance abuse

problems may have their genesis, in part, as a consequence of very early

life stress and environmental factors. Assessment of these factors in a

more systematic manner may provide a more rational basis for selection

of subjects who participate in abuse liability assessments.

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GENETIC FACTORS WHICH ENHANCE VULNERABILITY

FOR ALCOHOL AND DRUG ABUSE

First-degree relatives of alcoholics are at greater risk for developing

alcoholism than persons with negative family histories of alcoholism

(Goodwin et al., 1973, 1974: Schuckit et al., 1972; Schuckit 1986; Cotton

1979; Bohman et al, 1981, for reviews see Cloninger et al., 1986; Russell

et al., 1985). Although risk for alcohol and drug abuse involves an

interaction of biologic, psychologic and sociocultural processes (for

reviews see Mello 1980, 1983; Cloninger et al., 1986; Lex 1985), genetic

predisposition is also probably a major risk factor for alcoholism .

Although it is clear that genetic predisposition cannot wholly explain risk

for alcoholism (indeed genetic models can explain only a portion of the

variance associated with the causation of most diseases) a number of

biologic factors have been identified as putative genetic markers for

enhanced risk for alcoholism. Among the most robust findings in this

area are differences in subjective reports in levels of alcoholism-induced

intoxication for persons with family histories of alcoholism in contrast to

those who have no family history of alcoholism (Schuckit, 1984). There

are also reports of differences in endocrine and neuroendocrine responses

following alcohol consumption in family history negative and positive

individuals, differences in derangements of psychomotor function induced

by alcohol in family history negative and positive persons and differences

in brain electrical activity during both basal conditions and in evoked

response studies following alcohol intake by persons with negative and

positive family histories of alcoholism (for review, see Schuckit, 1986).

Taken together, data derived from biologic, psychologic and sociocultural

studies suggest that, at least for alcohol abuse, individuals may possess

differential vulnerabilities for development of alcohol abuse and

dependence. Thus we may infer that a variety of biologic, behavioral and

sociocultural factors may mitigate for or against many substance abuse

problems. If this hypothesis is correct, it would appear reasonable to

employ subject selection criteria for abuse liability studies which take

into consideration relative risk as defined by biologic, psychologic and

sociocultural predictors for substance abuse potential.

An excellent exposition of procedures available for testing drugs for

physical dependence potential and abuse liability was published in a

NIDA Research Monograph during 1984 (Brady and Lukas 1984).

However, this report did not contain any recommendations for volunteer

subject selection based upon biologic, behavioral or sociocultural

antecedents as predictors of risk for abuse liability. The aim of this report

is to discuss several promising new areas which may be of value in the

conduct of abuse liability testing in the future. These studies involve

310
neuroendocrine, neurophysiologic and behavioral correlates of alcoholand drug- induced intoxication, procedures for determining alcohol and

drug effects on brain electrical activity with computer-based imaging

studies and new technologies for assessing alcohol and drug concentrations

in regional portions of the brain with Magnetic Resonance Spectroscopy.

NEUROENDOCRINE, NEUROPHYSIOLOGIC AND

BEHAVIORAL CORRELATES OF ALCOHOL AND DRUG

REINFORCEMENT

Covariance of neurophysiologic, neuroendocrine and behavioral events

has been determined in human subjects during the first two hours after

ingesting alcohol or alcohol placebo, administered under controlled

double-blind conditions (Lukas and Mendelson 1988). Analysis of

plasma adrenocorticotropic hormone (ACTH) and cortisol levels at 5 min

intervals and EEG power spectral analysis in multiple 2-min epochs

permitted examination of the biobehavioral correlates of intoxication.

Data obtained establish that alcohol induces rapid changes in brain

electrical activity and ACTH secretion from the pituitary that are correlated

with subjective perceptions of positive changes in mood.

Methods

Twelve adult male volunteers ages 21 to 35 (57-98 kg) provided informed

consent for participation in this study. Subjects were recruited via

newspaper advertisements and were given a complete medical evaluation

including an electrocardiogram, blood chemistry studies and urinalysis.

Subjects with alcohol or drug abuse-related problems were not permitted

to participate in the study. All subjects described themselves as social

drinkers who, on the average, consumed alcohol one to three times/week.

Electrophysiological Recording and Blood Withdrawal

Procedures

Subjects were studied while they were seated in a recliner chair, in a

sound- and light-attenuated, electrically-shielded chamber, with their

eyes closed (figure 1). Scalp electroencephalogram (EEG) electrodes

were applied using the International 10-20 System (Jasper 1958) over sites

C3, C4, P3, and P4. Electrodes were referenced to linked earlobes. A

Kowarski-Cormed butterfly needle/catheter was inserted into an

antecubital vein of the right arm and threaded through the chamber wall.

311
The end was attached to a syringe, mounted on a syringe pump and

adjusted to continuously exfuse blood at a rate of 1.0 ml/min. Blood

samples were collected at 5-min intervals to obtain integrative plasma

levels of ACTH. cortisol and alcohol

Figure 1: Artist’s rendering of a subject in the experimental chamber, demonstrating

the multiple components of the study. Movement of the instrumental joystick device

is recorded on the polvgraph, along with electroencephalographic activity.

(Permission to reprint from Lukas and Mendelson 1988 from Biological Psychiatry.)

Subjective Reports of Intoxication

Because verbal or written reports of perceived mood state changes may

compromise the accuracy of EEG measures (Otto 1967; Matousek and

Petersen 1983), a custom-made instrumental joystick device was used to

obtain mood status reports. Movement of the handle or depression of the

button resulted in a deflection of an event pen located on the polygraph.

Thus, behavioral responses were monitored continuously with EEG

activity. Details of the device are presented in Lukas et al. (1986a.b).

These behavioral measures of mood status do not confound recording of

electroencephalographic activity influence pituitary excretion of ACTH.

Subjects were instructed to use their left hand to move the instrumental

joystick device as follows: forward-when they detected an alcohol

effect; left-when the effects became intense; backward-when the effects

312
disappeared. In addition, they were instructed to press a small button

located on the top of the joystick during periods when they perceived

feelings of intense pleasure, or euphoria.

Endocrine Assays

Consecutive 5-min integrated blood samples were subsequently analyzed

for plasma ACTH, cortisol and alcohol levels. ACTH and cortisol were

analyzed via radioimmunoassay procedures obtained from Nichols

Institute Diagnostics, San Juan Capistrano, CA and Travenol Laboratories,

Cambridge, MA, respectively. The ACTH assay is a double antibody

procedure whereas the cortisol assay utilizes a single antibody procedure.

Intra- and interassay coefficients of variance (CV) were 9.04 percent and

15.1 percent, respectively. for ACTH and 4.4 percent and 13.1 percent,

respectively, for cortisol. Plasma alcohol levels were determined

spectrophotometrically using the method of Leric et al. (1970). Intra- and

interassay CVs were 3.0 percent and 7.4 percent, respectively.

Experimental Procedure

After 30 min of baseline recordings, subjects drank either a placebo or

alcohol (0.695 g/kg) solution at a constant rate over a 15-min interval. A

total of 350 ml was delivered via a drinking tube/peristaltic motor device

which permitted the subjects to drink without opening their eyes or

moving their hands. The placebo solution contained only grapefruit

juice, whereas the alcohol solution was made with 40 percent beverage

alcohol (vodka). For both doses a 10 ml reservoir located between the

pump and the mouthpiece was filled with 3 ml of vodka to provide a

strong initial taste to mask the two treatments. This practice is an

effective placebo that does not produce measurable plasma alcohol levels

(Mendelson et al., 1984). Electroencephalographic activity and behavioral

responses were monitored continuously for the next 2 hours. Multiple 2-

min epochs of EEG activity were subjected to power spectral analysis.

Twelve-sev epochs were digitized at a rate of 256/set, followed by a Fast

Fourier Transformation using a Pathfinder 11 signal processor (Nicolet

Biomedical, Madison, WI). EEG power in the 0.25-4, 4-8. 8-13. and 13-

30 Hz bands was determined and block averaged over 2-min intervals.

Consecutive 5-min integrated plasma samples were removed without

disturbing the subject for the duration of the study.

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Results

After placebo administration, subjects did not report episodes of euphoria

and there were no significant changes in plasma ACTH or cortisol levels

or EEG alpha power. In contrast, after alcohol administration, subjects

reported several paroxysmal episodes of euphoria which began within 10

min after drinking and continued for an additional 40 min. Plasma

ethanol levels were 32.85 ± 5.35 mg/dl within 10 min after drinking began

and peaked at 81.79 ± 5.35 mg/dl at 115 min after drinking. Plasma ACTH

levels increased an average 20 pg/ml within 10-20 min after drinking

began and subsequently declined. Plasma cortisol levels gradually

increased and peaked at 30 min when blood alcohol levels averaged 44.98

± 6.14 mg/dl.

Figure 2 shows regression lines for the linear portion of the time-effect

curves for plasma ACTH, cortisol and alcohol levels, EEG alpha power,

and the incidence of reported euphoria after placebo (top) and alcohol

(bottom) administration.

Figure 2: Regression analysis of changes in plasma ACTH, cortisol. and ethanol

levels, EEG alpha power, and incidence of reported euphoria after placebo (top) and

ethanol (bottom) administration. Data are derived from six subjects per group.

(Permission to reprint from Lukasand Mendelson 1988 from Biological Psychiatry.)

314
Tests for parallelism (Tallarida and Murray 1981) revealed that EEG alpha

power, subjective reports of euphoria, plasma ACTH levels, and plasma

alcohol levels were parallel and all increased linearly during the first 30

min after alcohol consumption (p < 0.05). Increases in plasma cortisol

were not statistically significant. All physiologic and behavioral measures

decreased linearly within 35-60 min after drinking, even though plasma

alcohol levels continued to increase.

Discussion

In the present study, subjective reports of self-perceived euphoriaoccurred

between 10-15 min after drinking alcohol and were accompanied by a

significant increase in EEG alpha power and increased plasma levels of

ACTH. These data indicate that major physiologic and behavioral

concomitants of alcohol intoxication occur at relatively low-blood alcohol

levels (approx. 32 mg/dl) during the ascending phase of the blood alcohol

curve. Previous studies have noted that alcohol intake is associated with

activation of the hypothalamic-pituitary-adrenal axis (Mendelson and

Stein 1966; Noth and Walter 1984), but we have been unable to locate any

report that describes the initiation of such activation after such a shorttime course and low blood alcohol levels following ethanol intake.

Enhanced secretion of ACTH at low-blood alcohol levels could be the

result of alcohol-induced stimulation of corticotropin releasing factor

(CRF). Although subsequent activation of the adrenal cortex following

alcohol-related ACTH release could mediate changes in central nervous

system function and behavior, ACTH and probably CRF itself may also

directly effect neuronal function in regional portions of the central

nervous system (Ehlers 1986). It is also possible that low doses of alcohol

may directly stimulate release of ACTH from pituitary corticotrophs

(Redei et al., 1986).

The acute effects of alcohol on human EEG activity consist of increased

voltage and decreased alpha frequency (Engel and Rosenbaum 1945;

Holmberg and Martens 1955; Varga and Nagy 1960; Docter et al., 1966).

However, most of these studies have examined EEG effects that appear

during the “peak” behavioral responses, which typically occur 30-75 min

after drinking. Data obtained in this study and our previous study (Lukas

et al., 1986c) focused on very early components of the alcohol response

and found that neurophysiologic and neuroendocrine measures covaried

with alcohol -induced intoxication in normal persons. Abrupt increases

in EEG alpha power have been associated with specific subjective mood

states generally reported as pleasurable, floating and extremely relaxed

(Brown 1970; Lindsley 1952; Matejcek 1982; Wallace 1970). These data

315
suggest that the reinforcing properties of alcohol intoxication reflect

these rapid changes in EEG activity and ACTH secretion. A previous

study reported that acute oral administration of 40 mg of ACTH 4-9

analogue to human subjects reduced alpha activity (Bonn et al., 1984,

1985). However, this study was conducted to assess selective attention to

a dichotic listening task which may have induced an alpha suppressing

alerting response.

These positive early effects of alcohol are probably transient and dosedependent, as high alcohol doses and chronic alcohol abuse are followed

by increased anxiety, dysphoria and depression (Alterman et al., 1975;

McGuire et al., 1966; Mello 1972; Melloand Mendelson 1978; Mendelson

1964, 1970; Nathan et al., 1970). Yet it is tempting to speculate that the

early positive effects of alcohol may be especially salient for alcohol

abusers. Alcohol abusers also have low amounts of spontaneous EEG

alpha activity (Davis et al, 1941; Little and McAvoy 1952) and many

abnormal endocrine and physiologic responses (e.g., impaired

adrenocortical responses, regulation of arterial blood pressure) that are

reversed or “normalized” after consumption of small amounts of alcohol

(Kissin et al., 1959, 1960).

The paroxysmal short epochs of euphoria associated with concomitant

neurophysiologic and neuroendocrine responses during the ascending

phase of the blood alcohol curve may serve as powerful reinforcers for

perpetuation of drinking. The rising phase of the blood alcohol curve

may produce effects that are comparable to the heroin “rush” and cocaine

“high” - intense sensations of intoxication that persist for seconds or

minutes and then rapidly disappear.

Recent studies have shown that adrenocortical steroids may enhance or

depress neuronal activity (Majewska et al., 1986) and that these changes

may covary with positive and negative fluctuations in mood (Gold et al.,

1986). Based on these observations, it has been postulated that

adrenocortical activation of short-term duration which induces an acute

glucocorticoid response may facilitate occurrence of positive mood

states, whereas long-term adrenocortical activation and associated high

levels of glucocorticoids may cause dysphoria (Barnes 1986). Data

obtained in the present study are consistent with the notion that alcoholinduced ACTH secretion during the ascending phase of the blood ethanol

curve covaries with subjective reports of euphoria and alterations of

electrical activity in the central nervous system. Although chronic

alcohol abuse, which isassociated with chronic adrenocortical activation,

may increase risk for dysphoria, acute low dose alcohol intake clearly,

induces euphoria. Thus the biphasic close-related effects of alcohol on

mood may be mediated, in part, by the effects of alcohol on the

hypothalamic-pituitary-adrenal axis.

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TOPOGRAPHIC MAPPING OF EEG ALPHA ACTIVITY

DURING ALCOHOL-INDUCED INTOXICATION

The same technologies employed in power spectral analysis, high-speed

digital computers, are used to digitize the analog EEG activity, transform

the data with a Fast Fourier Transformation (Walter 1963) and generate

a power spectrum containing numerical values for the amount of power

in specific frequency bands. Thus, quantification of brain electrical

activity using power spectral analysis provides concomitant measures of

power and frequency independent of sample length. Topographic

mapping of brain electrical activity extends this technology because raw

EEG recordings from 18 to 20 electrode sites contain more information

than can be assimilated readily by the human brain (Duffy et al., 1979,

1981). Topographic mapping procedures assemble information from

multiple EEG leads by simultaneously creating power spectral arrays

from all electrode sites. The values between electrode sites are computed

with a three- or four-point linear interpolation algorithm using the

activity from the nearest three or four electrodes. The data are then

combined into a composite color-coded (cf. Duffy et al., 1979, 1981) or

gray-level (Buchsbaum et al., 1982) map which provides an overall view

of brain electrical activity at the moment the map is generated. This

technique has been used recently in the differential diagnosis of brain

dysfunctions (John et al., 1988). Anextensivediscussionof the principles

and the clinical and research applications of topographic mapping of

brain electrical activity has been published recently (Duffy 1986).

Ethanol-induced changes in electroencephalographic (EEG) activity

obtained using visual inspection and spectral analysis procedures include

increased voltage and slowing of the predominant frequency (Davis et

al., 1941; Abramson 1945; Engel and Rosenbaum 1945; Ekman et al.,

1963, 1964; Docter et al., 1966; Begleiter and Platz 1972; Warren and

Raynes 1972; Myrsten et al., 1975; Lukas et al., 1986a,c,d). While the

results from these studies are fairly consistent, they were based on

recordings from only a few EEG electrode sites, usually located over the

occipital and parietal cortex. A re-examination of alcohol’s effects on

brain electrical activity has been prompted by recent technical advances

in quantitative analysis of the topographic distribution of EEG activity

using far more recording sites than previously employed.

Measures of brain electrical activity have been useful in characterizing

various naturally-occurring behavioral states such as sleep and

wakefulness, but EEG correlates of drug-induced euphoria, anxiety or

dysphoria have been difficult to obtain. One major problem associated

with determining the relationship between brain electrical activity and

drug-induced mood changes is the procedural difficulty associated with

317
accurately measuring changes in subjective mood states without

introducing EEG artifacts. The use of questionnaires and visual analog

scales alters levels of alertness which, in turn, affect the EEG (Otto 1967;

Matousek and Petersen 1983). Therefore, the use of a nonverbal

instrumental device for recording drug-induced changes in mood is

necessary to avoid disturbing the subject’s level of alertness and thus

altering EEG activity (cf. Lukas 1988; Lukas et al., 1986a,c).

Methods

Six healthy right-handed women (age 21-27 years, mean = 22.9; height

152-173 cm, mean=163.3; weight 54.3-79.1 kg, mean=64.7) volunteered

for this study. Subjects were recruited via newspaper advertisements and

were paid for their participation. After a full explanation of the nature of

the study, all subjects provided informed consent for participation. All

women received a complete physical examination including an

electrocardiogram, blood chemistry and urinalysis evaluations. Beta

subunit human chorionic gonadotropic hormone levels were measured l2 days before the study to ensure that no woman was pregnant. Subjects

with any neurological, psychiatric or alcohol- or drug abuse-related

problems were excluded. Selection criteria also included a lean body

mass of between 30 and 45 lbs/in to ensure minimal variability in ethanol

volume of distribution (Reed 1978). Subjects were not currently taking

any prescription medication, including oral contraceptives, and urine

screens for recreational drugs were conducted on each study day-all

results were negative. Analysis of the recruiting questionnaires revealed

that all subjects described themselves as social drinkers who consumed,

on average, the equivalent of 1-3 glasses of wine per week. All but one

subject reported a negative family history for alcohol abuse or dependence

based upon DSM-III criteria (APA 1980).

Experimental Design and Procedure

Each subject served as her own control and participated in the study on

two occasions, 1 to 4 days apart (one subject was run 6 days apart) with

the first study day occurring on the day after the last day of menses.

Women were told that they might receive either placebo or alcohol on

each study day. Each subject actually received alcohol on one day and

ethanol placebo on the other in a randomized counterbalanced design.

The alcohol drink contained 0.7 g/kg of beverage grade ethyl alcohol [86

proof vodka] mixed in chilled fresh orange juice. The placebo drink

contained only orange juice. The total volume of both drinks was 350 ml.

318
To help mask the drink’s content, a 10 ml reservoir within the straw was

filled with 3 ml of vodka and 7 ml of orange juice to provide a strong

initial alcohol taste before both placebo and active drinks were consumed

(Mendelson et al., 1984). Subjects were informed of this procedure in

order to discourage them from using taste as a discriminating cue. Both

beverages were administered via a peristaltic pump located outside the

experimental room (Lukas et al., 1986a,c,d) which delivered fluid at a

rate of 23 ml/min to a mouthpiece. The mouthpiece was supported by a

flexible metal arm to permit hands-free drinking and allow the subjects

to keep their eyes closed and one hand on the joystick device (see figure

1) during the drinking procedure. The pump was activated for 3 min

followed by a 1 min rest period. This procedure was repeated until the

drink was consumed (19 min). Additional details of this procedure have

been published recently (Lukas and Mendelson 1988).

Subjects arrived at the laboratory at 9:00 a.m. and reported that they had

refrained from eating or drinking (except water) since midnight the night

before. Fifteen to 20 min of baseline EEG activity were collected before

alcohol or placebo administration. Since the major aim of the experiment

was to study the early effects of alcohol , all measures were recorded for

only 80 min after the drink was consumed.

EEG Recording Procedure

Subjects were prepared with 25 scalp electrodes affixed with collodion

using the International 10-20 system (Jasper 1958). In addition, bilateral

neck electrodes were attached to record muscle activity and two electrodes

were placed above and below the left eye to monitor eye movements.

Subjects were seated in a dimly lit room and the recording polygraph was

located in an adjacent room. Unipolar activity from leads F3, F4, C3, C4,

P3, P4, O1, O2, FPl, FP2, F7, F8, T3, T4, T5, T6, Fz, Cz, Pz, Oz, linked

eyes, left zygomatic, right zygomatic, and linked bilateral electrodes

placed over the fifth cervical vertebrate were referenced to linked ear

lobes and collected during eyes closed conditions using amplifiers at a

bandpass of 1-300 Hz.

Topographic mapping of EEG activity was conducted using a Brain

Electrical Activity Mapping(BEAM) system. EEG activity was recorded

continuously during the study on a paper chart driver. Two to 3 min

epochs of EEG activity were recorded on the BEAM system every 10 min

forsubsequent power spectral analysis. Additional epochs were recorded

during joystick responding.

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Subjective State Assessments

Subjects reported changes in subjective mood states by moving the

instrumental joystickdevice to indicate initial detection, strong intoxication

and termination of alcohol effects (Lukas et al., 1986a,d). In addition,

subjects could push a button to indicate an intense feeling of pleasure

(euphoria); a second button was available to indicate an intense feeling

of displeasure (dysphoria). Joystick movements were monitored

continuously during the experiment and recorded directly on the paper

chart driver, below the EEG recordings.

Blood Sample Collections

A standard i.v. flexible catheter was inserted into an antecubital vein.

Patency was maintained by continuous saline drip which was connected

via a 3-way stopcock. Discrete 5 ml blood samples were withdrawn at

10 min intervals for subsequent determinations of plasma alcohol levels.

Blood samples were centrifuged immediately and the plasma samples

were then frozen and stored for subsequent batch analysis for alcohol

concentration. Parallel estimates of blood alcohol levels were obtained

from a few subjects via expired air using a portable Alto-Sensor III

device (Intoximeters, Inc., St. Louis, MO). Breath samples (obtained at

the end of a 15 sec forced expiration) were measured once every 30-40

min and were gathered as part of a validation study to compare with

measured plasma alcohol levels.

Data Analysis

Three 2-min topographic brain electrical activity maps were generated

during the control period and at 10 min intervals after drinking began.

EEG activity was not recorded during blood sampling or when subjects

provided a breath sample. Additional samples of EEG activity were

recorded when subjects pushed the button to report euphoria. Topographic

maps of brain electrical activity were generated as follows. Digitized

epochs of EEG activity were edited on a blind basis for eye and head

movement artifact (abrupt deflections of 50 mV). Since the buttons on

the joystick require only 1 Newton of force to operate, movement artifact

was minimal or nonexistent: when present, only a 1-2 sec epoch of EEG

activity required editing. Using the BEAM system software, Fast Fourier

Transformations were perfomed on the remaining EEG activity. Brain

electrical activity between electrode sites was calculated using a 3-point

interpolation algorithm, and the resultant power spectral arrays were

320
color-coded on the basis of power in each of the following bands: delta

(0.5-3.5 Hz), theta (4.0-7.5 Hz), slow alpha (7.5-9.5 Hz), fast alpha (9.5

12.5 Hz), beta1 (12.0-15.5 Hz), beta2 (16.0-19.5 Hz), and beta3 (20.0-23.5

Hz). To avoid false interpretations due to truncation, the range of

absolute values (μV) and corresponding color codes were used for data

analysis, but then were scaled identically across all time points and

subjects for graphic display.

Topographic maps were compared to a non-treated control database,

consisting of thirty 20-29 year old right-handed women using significant

probability mapping (SPM) techniques (Duffy et al., 1981). Significant

probability mapping is a procedure that constructs z-scores for the

voltage and frequency values at each data point. Brain electrical activity

in each region of a subject’s scalp is then displayed on a color scale that

is calibrated in the number of standard deviations the subject’s activity is

from a control group. Because of the controversy surrounding the

validity of techniques that employ multiple post hoc comparisons (Oken

and Chiappa 1986; Duffy et al., 1986; Kahn et al, 1988), an alternative

approach to quantifying the topographic maps was developed. This

procedure involved collecting and storing the color-coded BEA-generated

maps as gray scale images using a high-resolution digitizer/flat bed

optical scanner and a microcomputer. The digitized images were then

stored and loaded into a drafting program. The contours of individual

colors on each BEAM-generated map were traced manually using a

digitizing board and cross-hair puck, A yuantitative measure of the

distribution of alpha activity over the scalp was obtained by determining

the area (in mm2) of the various color-coded regions using the Show Area

command of the graphics program (MacDraft). The area of each color

was then multiplied by its corresponding voltage value provided by the

absolute scale supplied with each topographic map; values for each

voltage range were then added together to yield the total alpha energy of

each topographic map. Additional details of this procedure are available

from the authors.

Subjective report data were retrieved from the paper tracings as previously

described (Lukas et al, 1986a,b,c). Mean latency to detection, intense

intoxication and termination of alcohol effects as well as number and

duration of euphoric and dysphoric episodes were determined after

placebo and alcohol treatments.

Subjective Reactions to Alcohol and Placebo

All subjects discriminated correctly between alcohol and placebo; joystick

responses indicating alcohol detection and intoxication reactions occurred

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only after alcohol administration. Subjects detected alcohol effects (i.e.,

moved the joystick forward) within 15-25 min after drinking began.

Alcohol-induced intoxication became more intense and was accompanied

by multiple episodes of intense pleasure or euphoria (i.e., pushed button

on joystick). Alcohol effects lasted 55.75 ± 20.1 min (range 30 - 79 min)

in the five subjects without a family history of alcoholism. One subject

detected alcohol effects for only about 15 min and failed to report a

pleasurable response. Subsequent evaluation of this subject’s history

revealed that her father was diagnosed as alcohol dependent (DSM-III

criteria). The temporal distribution of alcohol-induced subjective effects

in subjects with a negative family history for alcoholism (FHN) and the

one subject with a positive family history for alcoholism (FHP) are

shown in table 1. While there was no difference in the latency to detection

of ethanol effects, the FHP subject’s response was markedly attenuated

in both degree and duration. This differential behavioral response is

depicted in figure 3.

Figure 3: Behavioral responses of a representative FHN woman and the on FHP

woman after consuming 0.7 g/kg ethanol. Responses were recorded using an

instrumental joystick device which was available continuously to the subjects

throughout the duration of the study. (Reprinted from Lukas et al. 1989, copyright

by Alcohol Research Documentation , Inc., Rutgers Center of Alcohol Studies, New

Brunswick, NJ 08903.)

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Table 1. Latency to and duration of ethanol-induced intoxication in women with a negative (FHN) and

positive (FHP) family history of alcoholisma

TREATMENT LATENCYb DURATIONb

GROUP Detect Intense Euphoria Detect Euphoria

FHN 19.60 ± 6.77 29.67 ±6.11 30.00 ± 6.08 55.75 ± 20.10 11.30 ± 17.30

(n=5)

FHP

(n=l)

15.00 ------- ------ 15.50 -----

a

 0.7 g/kg consumed over an 18 min interval.

b

 All values are in minutes (mean ± sem); latency data are from the onset of drinking.

(Reprinted from Lukas et al., 1989, copyright by Alcohol Research Documentation, Inc., Rutgers Center of Alcohol Studies,

New Brunswick, NJ 08903)
EEG Patterns After Ethanol and Placebo

Topographic maps of each frequency band (e.g.. delta, theta, alpha, beta)

obtained during the pre-drink control period exhibited distribution patterns

normally found during an eyes closed/quiet awake state (Gibbs and

Gibbs 1951; Niedermeyer 1987). This included a localization of alpha

activity over the occipital poles, midline theta and frontal delta. Ethanolinduced behavioral reports of intoxication were associated with alterations

in brain electrical activity in the subjects with a negative family history

for alcoholism. Figure 4 depicts this relationship for both a representative

FHN subject and the one FHP subject.

In the FHN subjects, topographic mapping of alpha activity after ethanol

revealed that the distribution of high-amplitude, slow- and fast-frequency

alpha activity (white and red areas in the 4 right panels of figure 4)

extended bilaterally to encompass parietal, temporal and frontal areas

rostral of the central sulcus (electrodes C3-Cz-C4). Both slow and fast

EEG alpha activity was reduced after ethanol in the FHP subject even

though her plasma ethanol level (62 mg/dl via expired air analysis) was

in the same range as the FHN subjects at the time these maps were

generated. The results of the area analysis of alpha activity are shown in

figure 5.

The overall ANOVA showed a significant effect of ethanol on EEG alpha

activity F (3.20) = 20.757, p < 0.001. Scheffe F-test followup tests

revealed significance (p < 0.05) after ethanol in both slow and fast alpha

activity of the FHN subjects during the first 15 min after the drink was

consumed while placebo did not significantly alter the topographic

distribution of EEG alpha activity. The association between subjective

reports of euphoria and increased alpha distribution was quite high

(r=0.61, p < 0.01 for slow alpha and r=0.74, p < 0.01 for fast alpha); no

subject reported euphoria at any time after receiving placebo. Slow alpha

activity continued to remain elevated while fast alpha activity returned to

control levels. The one FHP subject displayed a marginal decrease in

both slow and fast alpha activity (figure 5), and reported only mild

ethanol effects (see figure 3).

Significant probability mapping (SPM) techniques were applied to track

the changes in alpha activity during the course of reported feelings of

sobriety, intoxication and euphoria. Results from a representative FHN

subject are shown in figure 6.

The color scale in a these topographic maps represents the difference

between this subject and the subjects in the control database in units of

standard deviations. The increased EEG alpha activity in frontal areas is

evident by 30 min after ethanol at the time this subject reported an intense

324
pleasurable feeling. The last panel of this figure demonstrates that alpha

power over frontal cortex has increased by 4 standard deviations (white

area).

Figure 5: Quantitative area analysis of slow and fast EEG alpha activity at various

times before and after drinking ethanol (0.7 g/kg) or placebo in five FHN subjects and

the one {dotted lines) FHP subject. The number and distribution of subjective reports

of euphoria are plotted along the time axis for direct comparison. All five FHN

subjects reported euphoria while the FHP subject did not. EEG alpha energy was

quantified using a contour area analysis procedure. ‡ denotes significance atp <

0.05 level using ANOVA. Reprinted from Lukas et al. 1989, copyright by Alcohol

Research Documentation, Inc., Rutgers Center of Alcohol Studies, New Brunswick,

NJ 08903.)

Plasma Alcohol Levels

All plasma samples from this study were lost due to a freezer malfunction.

However, analysis of the occasional expired air samples revealed that

subjects achieved plasma alcohol levels in the 70-80 mg/dl range. This

was true for the one FHP subject as well. In another study from our

laboratory, female subjects that received the same close of alcohol under

the exact same conditions achieved similar plasma alcohol levels that

peaked 60 min after alcohol administration.

325
Figure 4: Topographic maps of slow (7.5-9.5 Hz) and fast (0.5-12.5 Hz) alpha activity of the same

two subjects depicted in figure 3. Maps were generated using a BEAM system during the control

period and 15 min after the completion of drinking ethanol (0.7g/kg). Maps are plotted using identical

scaling factors (0-50 uV) to aid in visual comparisons. Subjects’ eyes were closed during data

collection. (Reprinted from Lukas et al. 1989. copyright by Alcohol Research Documentation. Inc.,

Rutgers Center of Alcohol Studies. New Brunswick, NJ 08903.)

Figure 6: Significant probability maps of EEG alpha activity from one FHN subject during the

progression from a sober state to ethanol intoxication. Reference bars to the right of each map are

calibrated in units of standard deviations of the control sample population (20-29 year old righthanded women) in the BEAM system database. (Reprinted from Lukas et al. 1989. copyright by

Alcohol Research Documentation, Inc., Rutgers Center of Alcohol Studies, New Brunswick, NJ

08903.)

326
Discussion: Topographic Distribution of EEG Alpha Activity

After Alcohol

Alcohol-induced increases in alpha activity have been reported by a

number of laboratories using selected scalp electrodes (Davis et al., 1941;

Engel and Rosenbaum 1944; Newman 1959; Docter et al., 1966; Begleiter

and Platz 1972; Lukas et al., 1986c,d). High-amplitude alpha activity is

normally localized about the occipital area (e.g., electrode leads O1, O2,

P3, and P4) and is usually most prominent when the eyes are closed. In

the present study in which topographic mapping techniques were used to

analyze EEG activity after alcohol administration, a unique pattern of

increased alpha activity was found to encompass the entire scalp; this

pattern was not observed during non-intoxicated states. While no left

versus right hemispheric assymetries were observed, the recording

montage (i.e., referenced to linked ears) was not suitable for detecting

such differences. While low-amplitude, slow-frequency alpha activity

can be recorded over the entire scalp, it is noteworthy that highamplitude, fast frequency alpha activity is not normally recorded over the

frontal cortex; this is the first report documenting an alcohol-induced

alteration in the distribution of EEG alpha activity.

It is unlikely that the observed increases in EEG alpha activity are the

result of neurophysiologic processes associated with intentional or

voluntary movement (e.g., joystick responding). Control recordings

obtained before drinking during simulated joystick responding failed to

produce observable changes in EEG alpha activity. While voluntary

movements can activate cortical recordings, particularly over the

sensorimotor cortex, these effects are observed only when the movement

is repetitive in nature and is paced over a specific time interval (Harner

1986; Pfurtscheller 1986). Joystick responding in the present study was

limited to single movements of either the wrist or the index finger.

Furthermore, voluntary movements reduce central beta activity (Jasper

and Andrews 1938; Pfurtscheller 1981), and exogenous stimulation or

increased attentiveness to the environment actually attenuates or “blocks”

alpha activity (Morrell 1966).

Behavioral Correlates of Alcohol-Induced EEG Changes

All five women without a family history of alcoholism moved the

joystick device to indicate that they were intoxicated. In addition. as

observed in male subjects (Lukas et al,. 1986a,c), these women also

reported that they experienced brief periods of intense pleasure or

euphoria during alcohol intoxication. These subjective reports of alcohol

327
intoxication and euphoria were paralleled by abrupt increases in EEG

alpha activity. Previous data from our laboratory (Lukas et al., 1986b)

showed that reports of intense pleasure after marijuana smoking are also

associated with abrupt increases in EEG alpha activity. Increased EEG

alpha activity is normally associated with a pleasurable, free-floating and

extremely relaxed state (Lindsley 1952; Brown 1970; Wallace 1970;

Matejcek 1982) similar to that induced during transcendental meditation

(Wallace 1970). The covariance between increased EEG alpha activity

over the entire scalp and subjective reports of euphoria after ethanol

suggests that this neurophysiologic response may be associated with

ethanol’s reinforcing properties. Hans Berger (1931) reported a similar

increase in alpha activity after cocaine administration. Herning et al.

(1985) replicated Dr. Berger’s findings (i.e., a tendency for increased

alpha) but noted that the lack of persistent alpha increases were due to the

fact that the subjects in their study were required to perform a sequential

subtraction task- thus, eliminating much baseline alpha activity.

Therefore, it is plausible that increased EEG alpha activity may be

associated with drug-induced reinforcement in general, and may not be

selective for a single drug class. This interpretation is consistent with the

notion that drug-seeking behavior is a form of stimulus self-administration

that produces a change (regardless of the direction) in subjective state

(Mello 1977, 1983).

EEG Indices of a Positive Family History of Alcoholism

The one woman who reported a positive family history of alcoholism

experienced an attenuated behavioral and electrophysiological response

to alcohol. Studies from other laboratories have demonstrated that

subjects with a positive family history of alcoholism have a differential

sensitivity to alcohol effects in comparison to subjects without this

history. The observed differences have reflected almost exclusively an

attenuated response in the FHP subjects as compared to FHN subjects.

These include measures of body sway (Hegedus et al., 1984; Schuckit

1985), subjective reports of intoxication (Schuckit 1984; Pollock et al.,

1986). motor control (O’Malley and Maisto 1985), spontaneous

electromyographic activity (Schuckit et al., 1981). and spontaneous EEG;

activity (Pollock et al,. 1983).

One laboratory that found a greater response in subjects with a family

history of alcoholism reported that men with an alcoholic father exhibited

alpha activity at a slower frequency than individuals without this history

(Pollock et al., 1983). The effects of alcohol on alpha freqency have

been shown to be dependent on the subject's baseline frequency (Engel

and Rosenbaum 1945; Varga and Nagy 1960), and Propping et al., (1980)

328
demonstrated that alcohol elicited a more pronounced alpha rhythm in

control subjects who have very little spontaneous EEG alpha activity.

While it is likely that these variables could interact with the observed

alcohol effect, the present results differ from those of Pollock et al. (1983)

in that these investigators found that FHP individuals exhibited a greater

increase in slow alpha energy and a greater decrease in fast alpha energy

than FHN subjects after alcohol administration. In contrast, data from the

present study indicate that a FHP subject exhibited less slow and fast

alpha activity after alcohol. However, this subject exhibited more slow

and fast alpha activity than the FHN subjects during control recordings

(compare the top left panel with the top right panel of figure 2), so the

direction and magnitude of the differences between FHP and FHN

subjects may be less important than the fact that they differ from one

another in their EEG responses to alcohol.

Additional evidence supporting a genetic component to alcohol’s

effects comes from studies in young boys who have a positive family

history of alcoholism. Both spontaneous EEG activity (Gabrielli et al.,

1982) and visual P300 evoked response potentials (Begleiter et al., 1984)

differentiated these boys from control subjects without a family history

of alcoholism. These data are particularly striking because these

electrophysiological alterations were observed in the absence of

alcohol administration. Similar data obtained in adults is not as conclusive

since visual (O’Connor et al., 1987) but not auditory (Polich and Bloom

1986, 1987) P300 evoked potential amplitudes were lower in adult male

subjects with a positive family history of alcoholism. Since spontaneous

EEG activity is genetically related (Vogel 1970; Vogel et al., 1979;

Propping et al., 1980), the data from the above and the present studies

provide additional evidence that genetic predispositions to ethanolrelated problems may be reflected in certain measures of brain electrical

activity that are associated with the visual system such as visual evoked

potentials and alpha activity.

Statistical Issues in the Analysis of Topographic Mapping Data

Abrupt increases in alpha activity were also observed using a statistical

tool-significant probability mapping (SPM). Current limitations of the

BEAM system prevent the creation of a separate database for the subjects

in the present study, or for comparing individual subjects against one

another, except by visual inspection. Thus, the SPM comparisons were

made against a database. resident in the BEAM operating system, of 30

adult, right-handed females between the ages of 20 and 29. Recently. the

validity of using significant probability mapping techniques as a diagnostic

tool to classify a patient as either normal or possessing a specific disease

329
has been challenged (Oken and Chiappa 1986). Further, because of the

complex nature of the data obtained, the collection process must be

conducted with much greater care to ensure that the results are interpreted

properly (Kahn et al., 1988). Duffy et al. (1986) defend SPM as

exploratory in nature and emphasize that it is designed to localize

regional differences in brain electrical activity, not for making diagnoses

(Duffy 1982; Duffy et al., 1984). Oken and Chiappa (1986) argue that the

use of “significant difference” tests for evaluating differences between

control groups and patients must be based on planned comparisons

between the control group and the patient. Since we were interested in

analyzing only the distribution of EEG alpha activity after alcohol, the

present study is not at variance with this notion.

One method of circutnventing this problem is to subject the topographic

data to analyses that are especially appropriate for such graphic-oriented

data--contour area analysis. The present study employed such a procedure

based on digitized image reproduction using a microcomputer-based

system. While it is clearly more desirable to use the actual data points

generated by the BEAM system, these data are not easily obtained using

the currently available software. Thus, area analysis of EEG topographic

maps represents a compromise between the highprecisionof the algorithms

in the BEAM program that generated the maps, and interpretable

differences in area that yielded clear distinctions between treated and

non-treated conditions as well as between FHP and FHN subjects.

Results from the present topographic EEG mapping study demonstrating

that alpha activity was increased over the entire scalp and that these

changes paralleled subjective reports of intoxication suggest that alcoholinduced increases in EEG alpha activity may correlate with its reinforcing

properties. Previous reports from this laboratory (Lukas et al., 1986c;

Lukas and Mendelson 1988) made a similar suggestion based on data

from only a limited number of electrode sites; topographic mapping

procedures used in the present study clearly provide a more detailed and

descriptive analysis of this phenomenon. Since the alcohol-induced

increases in EEG alpha activity were so widespread over the scalp, it is

possible that this neurophysiological alteration may be related to processes

which maintain continued alcohol-seeking behavior in spite of aversive

consequences associated with its chronic use (McGuire et al., 1966;

Alterman et al., 1975; Mello and Mendelson 1978: Mello 1983).

330
NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY IN

ALCOHOL AND DRUG ABUSE LIABILITY ASSESSMENT

During the past decade, major technologic advances have occurred in the

use of nuclear magnetic resonance (NMR) spectroscopy for the noninvasive study of brain function. These studies require the use of

specialized instrumentation which generates strong magnetic fields

(current clinical instruments generate 1.5 Tesla, approximately ten thousand

times stronger than the earth’s magnetic sphere). However, strong

magnetic fields, unlike ionizing radiation, do not produce any known

safety hazard for human or animal tissues and organs. In order to

determine the molecular structure of intrinsic oradministered compounds

in the brain, induction coils connected to radio frequency oscillators and

receivers are applied to regional portions of the head and neck. An NMR

spectrum is generated by altering the strength of the magnetic field or the

radio frequency; variation of the radio frequency signal permits

identificationof variations of NMR frequencies of brain tissue components.

Compounds which can be identified with NMR spectroscopy in the brain

include those which contain the following atoms: 1H 13C 19F, 23Na, 31P,

39K. The natural abundance of all of these atoms exceeds 90 percent with

the exception of 13C which occurs in nature in approximately one percent

of all carbon containing molecules.

Among the most important applications of NMR spectroscopy are in vivo

studies of cerebral metabolic processes. These studies were pioneered by

Ackerman and his associates (1980) and provided the basis for parametric

determination of levels of high energy phospholated compounds in the

brain by phosphorus NMR spectroscopy. Peres and his colleagues have

utilized this procedure for studying effects of histotoxic hypoxia on

intracellular brain pH and cerebral energy metabolism (Peres et al.,

1988). More recently deterium oxide (2 H2O) has been administered to

determine in vivo blood flow and tissue profusion. The application of

deterium oxide labeled compounds for studying drug distribution in

regional portions of the intact human brain provides an exciting new

opportunity for safe, non-invasive assessments of drug distribution and

action in the central nervous system.

A major breakthrough in NMR spectroscopy has been reported very

recently by Hanstock and his associates (1988). They have successfully

measured alcohol concentrations in the human brain by proton magnetic

resonance spectroscopy (Hanstock 1988). Following acquisition of a

control spectrum, a subject consumed 750 ml of a beverage containing

12.5 percent alcohol. A second spectrum waS obtained 50 minutes

following alcohol intake, when blood alcohol levels were approximately

331
100 mg/dl(22 mM). At these blood alcohol levels, the brain concentration

of ethanol methyl protons were approximately 60 mM. Dr. Hanstock and

his associates concluded that “detection of a large ethanol resonance

from the human brain is clearly practical. Since the ethanol protons are

an AX2 spin system, the ethanol signal can be separated from coresonant

signals by homonuclear editing if necessary. The way is open for

systematic study of ethanol neuropharmacology directly in the organ of

interest, with good time and anatomical resolution.”

Incorporation of nuclear magnetic resonance spectroscopy studies in

paradigms of human drug abuse liability testing will facilitate the

discovery of biologic mechanisms underlying drug reinforcement. When

such studies are complemented with improved psychologic and

sociocultural assessments which predict risk for drug abuse, an exciting

new area will have commenced for increasing our knowledge about

abuse liability.

REFERENCES

Abramson, H.A. The effect of alcohol on the personality inventory (Minnesota):

A preliminary report. Psychosom Med 7:184-185, 1945.

Ackerman, J.J.H.; Grova, T.H.; Wong, G.G.; Gadian, D.G.; and Radda, G.K.

Mapping of metabolites in whole animals by P-31 NMR using surface

coils. Nature 283: 167-170, 1980.

Alterman, A.I.; Gottheil, E.; and Crawford, D.H. Mood changes in an alcoholism

treatment program based on drinking decisions. Am J Psychiat 132:1032-

1037, 1975.

American Psychiatric Association Task Force on Nomenclature and Statistics:

Diagnostic and Statistical Manual of Psychiatric Disorders. (DSM-III).

Washington, D.C.: American Psychiatric Association, 1980, pp. 494.

Barnes, D.M. Steroids may influence changes in mood. Science 232:1344-1345,

1986.

Begleiter, H., and Platz, A. The effects of alcohol on the central nervous system

in humans. In: Kissin, B., and Begleiter, H. eds. The Biology of

Alcoholism. Vol. 2. New York: Plenum Press, 1972, pp. 293-343.

Begleiter, H.; Porjesz, B.; Bihari, B.; and Kissin, B. Event-related brain potentials

in boys at risk for alcoholism. Science 225: 1493-1496, 1984.

Berger, H. Uber das E.E.G. des menschen. [On the electroencephalogram of man:

Third report]. Arch Psychiat Nervenkr 94:16-30, 1931. Translated in:

Gloor, P., ed. Hans Beraer on the Electroencephalogram of Man.

Electroenceph. Clin. Neurophysiol. Suppl. 28. Amsterdam: Elsevier.

1969, pp. 95-132.

Bohman, M.; Sigvardsson, S.; and Cloninger. C.R. Maternal inheritance of

alcohol abuse: Cross-fostering analysis of adopted women. Arch Gen

Psychiat 38:965-969, 1981.

332
Bonn, J.; Fehm-Wolfsdorf, G.; Schiebe, M.; Birbaumer, N.; Fehm, H.L.; and

Voight, K.H. An ACTH 4-9 analog impairs selective attention in man.

Life Sci 36:2117-2125, 1985.

Bonn, J.; Fehm-Wolfsdorf, G.; Schiebe, M.; Rockstroh, B.; Fehm, H.L.; and

Voight, K.H. Dishabituating effects of an ACTH 4-9 analog in a vigilance

task. Pharmacol Biochem Behav 21:513-519, 1984.

Brady, J.V., and Lukas, S.E., eds. Testing Drugs for Physical Dependence

Potential and Abuse Liability. National Institute on Drug Abuse Research

Monograph No. 52. DHHS Publ. No. (ADM)84-1332. Washington, D.C.:

Supt. of Docs., U.S. Govt. Print. Off., 1984.

Brown, B.B. Recognition of aspects of consciousness through association with

EEG alpha activity represented by a light signal. Psychophysiology 6:442-

452, 1970.

Buchsbaum, M.S.; Rigal, F.; Coppola, R.; Cappelletti, J.; King, C.; and Johnson,

J. A new system for gray-level surface distribution maps of electrical

activity. Electroenceph Clin Neurophysiol 53:237-242, 1982.

Cloninger, C.R.; Sigvardsson, S.; Reich, T.; and Bohman, M. Inheritance of risk

to develop alcoholism. In: Braude, M.C., and Chao, H.M. eds. Genetic

and Biological Markers in Drug Abuse and Alcoholism. National Institute

on Drug Abuse Research Monograph No. 66. DHEW Pub. No.

(ADM)86-1444. Washington, D.C.: Supt. of Docs., U.S. Govt. Print.

Off., 1986., pp. 86-96.

Cotton, N.S. The familial incidence of alcoholism: A review. J Stud Alcohol

40:89-116, 1979.

Davis, P.A.; Gibbs, F.A.; Davis, H.; Jetter W.W.; and Trowbridge, L.S. The

effects of alcohol upon the electroencephalogram (brain waves). Quart J

Stud Alcohol 1:626-637, 1941.

Dotter, R.F.; Naitoh, P.; and Smith, J.C. Electroencephalographic changes and

vigilance behavior during experimentally induced intoxication with

alcoholic subjects. Psychosom Med 28:605-615, 1966.

Duffy, F.H. Topographic display of evoked potentials: Clinical applications of

brain electrical activity mapping (BEAM). In: Bodis-Wollner, I., ed.

Evoked Potentials, Ann. N.Y. Acad. Sci. 388:183-196, 1982.

Duffy, F.H., ed. Topographic Mapping of Brain Electrical Activity. Boston:

Butterworths, 1986, pp. 428.

Duffy, F.H.; Albert, M.S.; McAnulty, G.; and Garvey, A.J. Age-related

differences in brain electrical activity of healthy subjects. Ann Neurol

16:430-438, 1984.

Duffy, F.H.; Bartels, P.H.; and Burchfiel, J.L. Significance probability mapping:

An aid in the topographic analysis of brain electrical activity.

Electroenceph Clin Neurophysiol 51: 455-462, 1981.

Duffy, F.H.; Bartels, P.H.; and Neff, R. A response to Oken and Chiappa. Ann

Neurol 19:494-496, 1986.

Duffy, F.H.; Burchfiel, J.L.; and Lombroso, C.T. Brain electrical activity

mapping (BEAM): A method for extending the clinical utility of EEG and

evoked potential data. Ann Neurol: 309-321, 1979.

333
Ehlers, C.L. EEG stability following corticotropin releasing factor in rats.

Psychoneuroendocrinology 11:121-125, 1986.

Ekman, G.; Frankenhaeuser M.; Goldberg, L.; Bjherver, K.; Jarpe, G.; and

Myrsten A-L. Effects of alcohol intake on subjective and objective

variables over a five-hour period. Psychopharmacologia 4:28-38, 1963.

Ekman, G.; Frankenhaeuser M.; Goldberg, L.; Hagdahl, R.; and Myrsten, A.-L.

Subjective and objective effects of alcohol as functions of dosage and

time. Psychopharmacologia 6:399-409, 1964.

Engel, G.L., and Rosenbaum, M. Studies of the electroencephalogram in acute

alcoholic intoxication. Proc Cent Soc Clin Res 17:62-63, 1944.

Engel, G. L., and Rosenbaum, M. Delirium III. Electroencephalographic

changes associated with acute alcohol intoxication. Arch Neurol Psychiat

53:44-50, 1945.

Gabrielli, W.F.; Mednick, S.A.; Volavka, J.; Pollock, V.E.; Schulsinger, F.; and

Itil, T.M. Electroencephalograms in children of alcoholic fathers.

Psychophysiology 19:404-407, 1982.

Gibbs, F.A., and Gibbs, E.L. Atlas of Electroencephalography, Vol. 1,

Methodology and Controls. Reading, MA: Addison-Wesley, 1951.

Gold, P.W.; Loriaux, D.L.; Roy, A.; Kling, M.A.; Calabrese, J.R.; Kellner, C.H.;

Nieman, L.K.; Post, R.M.; Pickar, D.; Galucci, W.; Avgerinos, P.; Paul,

S.; Oldfield, E.H.; Cutler, G.B.; and Chrousos, G.P. Responses to

corticotropin-releasing hormone in the hypercortisolism of depression and

Cushing’s disease: Pathophysiologic and diagnostic implications. N Eng

J Med 314:1329-1335, 1986.

Goodwin, D.W.; Schulsinger, F.; Hermansen, L.; Guze, S.B.; and Winokur, G.

Alcohol problems in adoptees raised apart from alcoholic biological

parents. Arch Gen Psychiat 28:238-243, 1973.

Goodwin, D.W.; Schulsinger, F.; Moller, N.; Hermansen, L.; Winokur, G.; and

Guze, S.B. Drinking problems in adopted and nonadopted sons of

alcoholics. Arch Gen Psychiat 31:164-169, 1974.

Hanstock, C.; Rothman, D.; Shulman, R.; Novotny, E.; Petroff, O.; and Prichard,

J. Ethanol observed in human brain by proton magnetic resonance

spectroscopy. Seventh Annual Meeting, Society of Magnetic Resonance

in Medicine. San Francisco, CA, 1988.

Hamer, R.N. Clinical application of computed EEG topography. In: Duffy, F.

H., ed. Topographic Mapping of Brain Electrical Activity. Boston:

Butterworths, 1986, pp. 347-356.

Hegedus, A.M.; Tarter, R.E.; Hill, S.Y.; Jacob, T.; and Winsten, N.E. Static

ataxia: A possible marker for alcoholism. Alcoholism: Clin Exp Res

8:580-582, 1984.

Herning, R.I.; Jones, R.T.; Hooker, W.D.; Mendelson, J.; and Blackwell, L.

Cocaine increases EEG beta: A replication and extension of Hans

Berger’s historic experiments, Electroenceph Clin Neurophysiol 60:470-

477, 1985.

Hill, J.E.; Haertzen, C.A.; Wolbach, A.B.; and Miner. E.J. The Addiction

Research Center Inventory: Standardization of scales which evaluate

subjective effects of morphine, amphetamine.pentobarbital. alcohol, LSD25, pyrahexyl and chlorpromazine. Psychopharmacologia 4:167-183,

1963.

334
Himmelsbach, C.K. Clinical studies of drug addiction I. The absence of

addiction liability in “Perparin.” Publ Hlth Rep Suppl 122, 1937a.

Himmelsbach, C.K. Clinical studies in drug addiction II. “Rossium” treatment of

drug addiction. Publ Hlth Rep Suppl 125, 1937b.

Holmberg, G., and Martens, S. Electroencephalographic changes in man

correlated with blood alcohol concentration and some other conditions

following standardized ingestion of alcohol. Quart J Stud Alcohol 16:411-

424, 1955.

Jasper, H.H. The l0-20 electrode system of the International Federation.

Electroenceph Clin Neurophysiol 10:371-375, 1958.

Jasper, H.H., and Andrews, H.L. Electro-encephalography. III. Normal

differentiations of occipital and precentral regions in man. Arch Neurol

Psychiat 39:96-115, 1938.

John, E.R.; Prichep, L.S.; Fridman, J.; and Easton, P. Neurometrics: Computerassisted differential diagnosis of brain dysfunctions. Science 239: 162-

169, 1988.

Kahn, E.M.; Weiner, R.D.; Brenner, R.P.; and Coppola, R. Topographic maps of

brain electrical activity-Pitfalls and precautions. Biol Psychiat 23:628-

636, 1988.

Kellam, S.G.: Brown, C.H.; and Fleming, J. Developmental epidemiological

studies of substance use in Woodlawn: Implications for prevention

research strategy. In: Harris, L.S., ed. Problems of Drug Dependence

1981. National Institute on Drug Abuse. Research Monograph No. 41.

Washington, D.C.: Comm. on Problems of Drug Dependence, 1982, pp.

22-33.

Kellam, S.G.; Brown, C.H.; Rubin, B.R.; and Ensminger, M.E. Paths leading to

teenage psychiatric symptoms and substance use: Developmental

epidemiological studies in Woodlawn. In: Guze, S.B.; Earls, F.J.; and

Barrett, J.E. eds. Childhood Psychopathology and Development. New

York: Raven Press, 1983, pp. 17-51.

Kissin, B.; Schenker, V.; and Schenker, A. The acute effects of ethyl alcohol and

chlorpromazine on certain physiological functions in alcoholics. Quart J

Stud Alcohol 20:480-492, 1959.

Kissin, B.; Schenlcer, V.; and Schenker, A.C. The acute effect of ethanol

ingestion on plasma and urinary 17-hydroxycorticoids in alcoholic

subjects. Am J Med Sci 239:690-705, 1960.

Leric, H.; Kaplan, J.C.; and Broun, G. Dosage enzymatique de l’alcool sanguin

par micromethode colorimetrique. Clin Chim Acta 29:523-528, 1970.

Lex, B.W. Alcohol problems in special populations. In: Mendelson, J.H., and

Mello, N.K., eds. The Diaenosis and Treatment of Alcoholism, 2nd

Edition. New York: McGraw-Hill Book Co., 1985, pp. 89-187.

Lindsley, D.B. Psychological phenomena and the electroencephalogram.

Electroenceph Clin Neurophysiol 4:443-456, 1952.

Little, S.C., and McAvoy, M. Electroencephalographic studies in alcoholism.

Quart J Stud Alcohol 13:9-15, 1952.

Lukas, S.E. Brain electrical activity as a tool for studying drugs of abuse. In:

Mello, N.K. ed. Advances in Substance Abuse. Behavioral and Biological

Research, Vol. 4. Greenwich, CT: JAI Press, 1988, in press.

335
Lukas, S.E., and Mendelson, J.H. Electroencephalographic activity and plasma

ACTH during ethanol-induced euphoria. Biol Psychiat 23:141-148, 1988.

Lukas, S.E.; Mendelson, J.H.; and Benedikt, R.A. Instrumental analysis of

ethanol-induced intoxication in human males. Psychopharmacology

(Berlin) 89:8-13, 1986a.

Lukas, S.E.; Mendelson, J.H.; Amass, L.; and Smith, R. Plasma delta-9-

tetrahydrocannibinol (THC) levels during marihuana-induced EEG and

behavioral effects in human subjects. Pharmacologist 28:191, 1986b.

Lukas, S.E.; Mendelson, J.H.; Benedikt, R.A.; and Jones, B. EEG alpha activity

increases during transient episodes of ethanol-induced euphoria.

Pharmacol Biochem Behav 25:889-895, 1986c.

Lukas, S.E.; Mendelson, J.H.; Benedikt, R.A.; and Jones, B. EEG, physiologic

and behavioral effects of ethanol administration. In: Harris, L.S., ed.

Problems of Drug Dependence 1985. National Institute on Drug Abuse

Research Monograph No. 67. DHEW Pub. No. (ADM))86-1448.

Washington, D.C.: Supt. of Docs., U.S. Govt. Print. Off., 1986d, pp. 209-

214

Lukas, S.E.; Mendelson, J.H.; Woods, B.T.; Mello, N.K.; and Teoh, S.K.

Topographic mapping of EEG alpha activity during ethanol-induced

intoxication. J Stud Alcohol 50:176-185, 1989.

Majewska, M.D.; Harrison, N.L.; Schwartz, R.D.; Barker, J.L.; and Paul, S.M.

Steroid hormone metabolites are barbiturate-like modulators of the GABA

receptor. Science 232:1004-1007, 1986.

Martin, W.R., and Fraser, H.F. A comparative study of physiological and

subjective effects of heroin and morphine administered intravenously in

postaddicts. J Pharmacol Exp Ther 133:388-399, 1961.

Matejcek, M. Vigilance and the EEG: Psychological, physiological and

pharmacological aspects. In: Hermann, W.M., ed. EEG in Drug Research.

Stuttgart: Gustav Fischer, 1982, pp. 405-508.

Matousek, M., and Petersen, I. A method for assessing alertness fluctuations

from EEG spectra. Electroenceph Clin Neurophysiol 55:108-113, 1983.

McGuire, M.T.; Stein, S.; and Mendelson, J.H. Comparative psychosocial studies

of alcoholic and nonalcoholic subjects undergoing experimentally-induced

ethanol intoxication. Psvchosom Med 28:13-26, 1966.

Mello, N.K. Behavioral studies of alcoholism. In: Kissin, B., and Begleiter, H.,

eds. The Biology of Alcoholism. Vol. II: Physiology and Behavior. New

York: Plenum Press, 1972, pp. 219-291.

Mello, N.K. Stimulus self-administration: Some implications for the prediction

of drug abuse liability. In: Thompson, T., and Unna, K.R., eds. Predicting

Dependence Liability of Stimulant and Depressant Drugs. Baltimore:

University Park Press, 1977, pp. 243-260.

Mello, N.K. Some behavioral and biological aspects of alcohol problems in

women. In: Kalant, O.J., ed. Alcohol and Drug Problems in Women:

Research Advances in Alcohol and Drug Problems. Vol. 5. New York:

Plenum Press, 1980, pp. 263-298.

Mello, N.K. Etiological theories of alcoholism. In: Mello. N.K.. ed. Advances in

Substance Abuse: Behavioral and Biological Research. Vol. 3.

Greenwich, Conn.: JAI Press, 1983. pp. 271-312.

336
Pathogenesis of Alcoholism. Biological Factors.. Vol. 7. New York:

Mello, N.K. A behavioral analysis of the reinforcing properties of alcohol and

other drugs in man. In: Kissin, B., and Begleiter, H., eds. The

Plenum Press, 1983, pp. 133-198.

Mello, N.K., and Mendelson, J.H. Alcohol and human behavior. In: Iversen,

L.L.; Iversen, S.D.; and Snyder, S.H., eds. Handbook of

Psychopharmacology, Section III, Chemistry, Pharmacology, and Human

Use. New York: Plenum Press, 1978, pp. 235-317.

Mendelson, J.H. Experimentally induced chronic intoxication and withdrawal in

alcoholics. Quart J Stud Alcohol Suppl. 2, 1964.

Mendelson, J.H. Biological concomitants of alcoholism, Part I. N Engl J Med

283:24-32, 1970.

Mendelson, J.H.; McGuire, M.; and Mello, N.K. A new device for administering

placebo alcohol. Alcohol 1:417-419, 1984.

Mendelson, J.H., and Stein, S. Serum cortisol levels in alcoholic and nonalcoholic subjects during experimentally induced ethanol intoxication.

Psychosom Med 28:616-626, 1966.

Morrell, L.K. Some characteristics of stimulus-provoked alpha activity.

Electroenceph Clin Neurophysiol 21:552-561, 1966.

Myrsten, A-L.; Hollstedt, C.; and Holmberg, N. Alcohol-induced changes in

mood and activation in males and females. Scan J Psychol 16:303-310,

1975.

Nathan, P.E.; Titler, N.A.; Lowenstein, L.M.; Solomon, P.; and Rossi, A.M.

Behavioral analysis of chronic alcoholism. Interaction of alcohol and

human contact. Arch Gen Psychiat 22:419-430, 1970.

Newman, H.W. The effect of alcohol on the electroencephalogram. Stanford Med

Bull (South Stacks) 17:55-60, 1959.

Niedermeyer, E. Electroencephalography. 2nd Edition. New York: Urban and

Schwarzenberg, 1987, pp. 940.

Noth, R.H., and Walter, R.M., Jr. The effects of alcohol on the endocrine system.

Med Clin North Am 68:133-146, 1984.

Nurco, D.N. Precursors of addiction. In: Harris, L.S., ed. Problems of Drug

Dependence, 1981. National Institute on Drug Abuse Research

Monograph No. 41. Washington, D.C.: Comm. on Problems of Drug

Dependence, 1982, pp. 10-20,

O’Connor, S.; Hesselbrock, V.; Tasman, A.; and DePalma, N. P3 amplitudes in

two distinct tasks are decreased in young men with a history of paternal

alcoholism. Alcohol 4:323-330, 1987.

Oken, B.S., and Chiappa, K. H. Statistical issues concerning computerized

analysis of brainwave topography. Ann Neurol 19:493-494, 1986.

O’Malley, S.S., and Maisto, S.A. Effects of family drinking history and

expectancies on responses to alcohol in men. J Stud Alcohol 46:289-297,

1985.

Otto, E. The effect of instructions influencing the level of alertness on the EEG

activity. In: Nedecky, I., ed. Mechanisms of Orienting Reaction in Man.

Bratislave: Slovak Acad. Sci. Publ. House. 1967, pp. 351-365.

337
Peres. M.; Merit, P.; Barrere, B.; Pasquier, C.; Beranger, G.; Beloeil, J.C.;

Lallemand, J.Y.; and Seylaz, J. In vivo 31P Nuclear Magnetic Resonance

(NMR) study of cerebral metabolism during histotoxic hypoxia in mice.

Metabol Brain Dis 3:37-48, 1988.

Pfurtscheller, G. Central beta rhythm during sensorimotor activities in man.

Electroenceph Clin Neurophvsiol 51:253-264, 1981.

Pfurtscheller, G. Event-related desynchronization mapping. In: Duffy, F.H., ed.

Topographic Mapping of Brain Electrical Activity. Boston: Butterworths,

1986, pp. 99-111.

Polich, J., and Bloom, F.E. P300 and alcohol consumption in normals and

individuals at risk for alcoholism. Prog Neuro-Psychopharmacol Biol

Psychiat 10:201-210, 1986.

Polich, J., and Bloom, F.E. P300 from normals and adult children of alcoholics.

Alcohol 4:301-305, 1987.

Pollock, V.E.; Teasdale, T.W.; Gabrielli, W.F.; and Knop, J. Subjective and

objective measures of response to alcohol among young men at risk for

alcoholism. J Stud Alcohol 47:297-304, 1986.

Pollock, V.E.; Volavka, J.; Goodwin, D.W.; Mednick, S.A.; Gabrielli, W.F.;

Knop, J.; and Schulsinger, F. The EEG after alcohol administration in

men at risk for alcoholism. Arch Gen Psychiat 40:857-861, 1983.

Propping, P.; Kruger, J.; and Janah, A. Effect of alcohol on genetically

determined variants of the normal electroencephalogram. Psychiat Res

2:85-98, 1980.

Redei, E.; Branch, B.; and Taylor, A.N. Abstracts of the First International

Congress of Neuroendocrinology 293:98, 1986.

Reed, T.E. Racial comparisons of alcohol metabolism: Background, problems,

and results. Alcoholism 2:83-87, 1978.

Russell, M.; Henderson, C.; and Blume, S.B. Children of Alcoholics: A Review

of the Literature. New York: Children of Alcoholics Foundation, Inc.,

1985.

Schuckit, M.A. Subjective responses to alcohol in sons of alcoholics and control

subjects. Arch Gen Psychiat 41:879-884, 1984.

Schuckit, M.A. Ethanol-induced changes in body sway in men at high alcoholism

risk. Arch Gen Psychiat 42:375-379, 1985.

Schuckit, M.A. Genetic and biological markers in alcoholism and drug abuse. In:

Braude, MC., and Chao, H.M., eds. Genetic and Biological Markers in

Drug Abuse and Alcoholism. National Institute on Drug Abuse Research

Monograph No. 66. DHEW Pub. No. (ADM)86-1444. Washington, D.C.:

Supt. of Docs., U.S. Govt. Print. Off., 1986, pp. 97-108.

Schuckit, M.A.; Engstrom, D.; Alpert, R.; and Duby, J. Differences in muscletension response to ethanol in young men with and without family

histories of alcoholism. J Stud Alcohol 42:918-924, 1981.

Schuckit, M.A.; Goodwin, D.W.; and Winokur, G. A study of alcoholism in half

siblings. Am J Psychiat 128:1132-1136, 1972.

Tallarida, R.J., and Murray, R.B. Manual of Pharmacologic Calculations. New

York: Springer Verlag, 1981.

Varga, B., and Nagy, T. Analysis of alpha-rhythms in the electroencephalogram

of alcoholics. Electroenceph Clin Neurophvsiol 12:933, 1960.

338
Vogel, W. The genetic basis of the normal human electroencephalogram.

Humangenetik 10:91-114, 1970.

Vogel, W.; Schalt, E.; Kruger, J.; Propping, P.; and Lehnert, K.F. The

electroencephalogram (EEG) as a research tool in human behavior

genetics: Psychological examinations in healthy males with various

inherited EEG variants. Hum Gen 47:1-45, 1979.

Wallace, R.K. Physiological effects of transcendental meditation. Science

167:1751-1754, 1970.

Walter, D.L. Spectral analysis for electroencephalogram: Mathematical

determination of neurophysiological relationships from records of limited

duration. Exo Neurol 8:155-181, 1963.

Warren, G.H., and Raynes, A.E. Mood changes during three conditions of

alcohol intake. Quart J Stud Alcohol 33:979-989, 1972.

ACKNOWLEDGMENTS

Supported in part by Grants DA-00064, DA-03994, DA-00115 and DA00101 from the National Institute on Drug Abuse, and Grant AA-06252

from the National Institute on Alcohol Abuse and Alcoholism. Portions

of this paper originally appeared in: Lukas, S.E., and Mendelson, J.H.

Electroencephalographic activity and plasma ACTH during ethanolinduced euphoria. Biological Psychiatry 23:141-148, 1988; Kellam,

S.G., Brown C. H., Rubin, B.R., and Ensminger, M.E. Paths leading to

teenage psychiatric symptoms and substance use: developmental

epidemiological studies in Woodlawn. In: Guze, S.B., Earls, F.J., and

Barrett, J.E. eds. Childhood Psychopathology and Development. New

York: Raven Press, 1983, pp. 17-51; Lukas, S.E., Mendelson, J.H.,

Woods, B.T., Mello, N.K., and Teoh, S.K. Topographic mapping of EEG

alpha activity during ethanol-induced intoxication. Journal of Studies on

Alcohol 50:176-185, 1989; Hanstock, C., Rothman, D., Shulman, R.,

Novotny, E., Petroff, O., and Prichard, J. Ethanol observed in human

brain by proton magnetic resonance spectroscopy. Seventh Annual

Meeting Society of Magnetic Resonance in Medicine. San Francisco,

1988. We are grateful to the authors and publishers of these reports for

permission to reproduce their material in this chapter.

339
AUTHORS

Jack H. Mendelson, M.D.1

Professor of Psychiatry (Neuroscience)

Nancy K. Mello, Ph.D.1

Professor of Psychology (Neuroscience)

Scott E. Lukas, Ph.D.1

Assistant Professor of Psychiatry (Pharmacology)

Bryan T. Woods, M.D.2

Associate Professor of Neurology

Siew K. Teoh, M.D.1

Instructor in Psychiatry

1Alcohol and Drug Abuse Research Center

2Department of Neurology

McLean Hospital - Harvard Medical School

Belmont, Massachusetts 02 178

340
CHAPTER 16

Drug Abuse Liability Testing: Human Subject Issues

Herbert D. Kleber, M.D.

INTRODUCTION

Clinical research, in general, is based on a tacit understanding between

science and the larger society. Society is permitting certain risks to be

taken with its members in return for the assurance by scientists that the

research they are conducting is up to both scientific and ethical standards.

Even if the ethics of a trial are justified, society is getting short changed

if the science is inadequate. The results would not be able to be used for

the benefits intended, and individuals would have been subjected to risks

no longer justified by the benefits. The first scientific issue therefore has

to do with whether a trial should be done at all (Marwick 1988). There

needs to be adequate doubt about the outcome. For example, if one has

a drug that structurally is similar to other drugs on the market known to

be potentially abusable, and in animal tests of self-administration and

other measures designed to measure human abuse liability, results are

similar to these existing agents, one would need a very strong rationale

to do human abuse liability testing. Unfortunately, animal testing not

uncommonly is inadequte to the job of predicting human drug abuse.

Certain drugs are self-administered by certain animal species and are not

drugs of abuse in humans while, conversely, other drugs are abused by

humans and are not self-administered by most animal species used in

testing.

Once the necessity for a study is agreed upon, then the design of the trial

becomes important. The design has to be such that the results are likely

to be adequately conclusive. Too small an N to draw conclusions when

a potentially dangerous drug is used is as unethical as an N larger than

necessary for the study. Finally, there is the issue of obtaining an informed

consent. Since, in general, self-administration studies are ones in which

there will be no direct benefit to the subject, volunteers need to clearly

understand this and the potential risks. The issue of compensation versus

risk becomes important. It is also important, of course, to realize that the

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assessment of risks involved in this kind of research requires certain

assumptions or subjective judgments which are at times difficult to make

and upon which reasonable people can disagree.

HISTORICAL BACKGROUND

The technological growth in research sophistication over the past 4 decades

has been accompanied by increased understanding of important ethical

dimensions, particularly regarding the use of human subjects. The low

point in human experimentation was reached during the Nazi experiments

in World War II. Revulsion at these atrocities led to the Nuremberg Code

in 1946. Significant formal changes since then include: in 1953, the

British Medical Research Council’s memorandum on clinical

investigations; in 1964, the Declaration of Helsinki; in 1966, the U.S.

Public Health Service requirement for institutional review of experimental

protocols involving humans; and in 1974, the establishment of a National

Commission for Protection of Human Subjects of Biomedical and

Behavioral Research. Just prior to this, in 1973, the Department of Health,

Education and Welfare had published its first set of proposed regulations

(these were finalized in 1974) on the protection of human research subjects.

Between 1975 and 1978, the National Commission published a series of

reports on various aspects of research involving human subjects. Each

report presented recommendations to the Department of Health, Education

and Welfare (DHEW) Secretary, recommendations which formed the

basis of development of new DHEW and Department of Health and

Human Services (DHHS) regulations. Commission recommendations

have led to the DHHS regulations being far more rational than the original

ones proposed in 1973-74. Since that time, Dr. Robert Levine, a staff

member of the National Commission, has continued to be active in the

field, and it is his writings in particular that have been of great help in

formulating the discussion in this paper (Levine 1986).

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FEDERAL GUIDELINES FOR RESEARCH ON HUMAN

SUBJECTS

The DHHS guidelines for human research include the following points:

1. Risks to subjects are minimized proportionate to the anticipated benefits

and knowledge.

2. Data are monitored to ensure safety of subjects.

3. Selection of subjects is equitable.

4. If subjects are vulnerable, additional safeguards are included.

5. Informed consent is obtained if appropriate.

6. Confidentiality is adequately protected.

The issues to be covered in this paper include the selection of subjects to

be used, the relation of this to the type of drug, and informed consent

issues.

ETHICAL PRINCIPLES USED IN DECISION MAKING

The National Commission for the Protection of Human Subjects of

Biomedical and Behavioral Research (1978) identified three basic

principles of major importance in decision making in this area. They

were: respect for persons, beneficence and justice. Respect for persons

requires the investigator to treat subjects as autonomous individuals whose

informed consent is necessary for participation in the research project. It

follows from this that research subjects should not be considered passive

data sources, but as individuals whose welfare and rights need to be

respected. It is important to keep in mind that respect for persons includes

the idea that if an individual is autonomous, he/she should be left alone

to participate in activities even though such activities may be harmful,

e.g., hang-gliding (Levine 1986). Individuals may be less than autonomous

because of vulnerability, defined as being relatively or absolutely incapable

of protecting their own interest. Vulnerability may occur because of

insufficient power, intelligence, resources. strength, etc. The more

vulnerable the individual, the less autonomous. The informed consent

process needs to reflect safeguards with individuals who are deemed less

autonomous and more vulnerable. As Levine has noted. “At times it is

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essential to recruit vulnerable subjects because no other persons have the

conditions to be studied. Under these circumstances one should generally

select the least vulnerable representatives of those populations” (Levine

1986).

The second ethical principle is beneficence. Two general rules have been

formulated as a complementary expression of a beneficent action

including: 1) do no harm, and 2) maximize possible benefits and minimize

possible harm. The Commission interpreted the principle of beneficence

as creating an obligation to both secure the well-being of the individual

and at the same time develop information that could lead to future societal

benefit. It was important, they reported, to note, however, that securing

societal benefits should not lead to intentional harming of subjects

(National Commission 1978). While individuals taking part in research

may be called upon to accept the risk of injury in the interest of producing

a benefit for themselves or others, a researcher has the obligation not to

take actions that would certainly injure an identified individual. The

practical principles for researchers that flow from the principle of

beneficence are as follows:

1. Protocols must provide valid and generalizable knowledge;

2. The benefits of the research need to be proportionate to the risks;

3.

4.

5.

6.

Since the benefits may be for others, subject well-being must be

protected;

Researchers must try to minimize risk and maximize the benefits of

participation;

Risks should be minimized by excluding subjects more likely to

suffer adverse effects; and finally,

One way of maximizing benefits is to help subjects obtain care after

the study has been completed if they are interested in treatment.

The third principle is that of justice. Justice is seen as requiring both that

a person be treated fairly and that each gets what he/she is due or owed.

Justice can either be comparative or non-comparative. Comparative is

usually the case in research and involves determining what a person is due

by weighing their claims against competing claims of others. Noncomparative justice deals with identifying what a person should do without

regard to others, for example, that innocent persons should not be punished.

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While comparative justice requires the fair sharing of burdens and benefits,

what constitutes fair sharing is often a matter of controversy (Levine

1986). As applied to research the principles of justice can be stated as

follows:

1. The benefits and burdens of research need to be distributed fairly.

2. No single group should bear a disproportionate share of the risk.

3. Vulnerable populations should not be used when other populations

would be suitable study subjects.

4. Use of vulnerable subjects is more justifiable if the research will

improve the understanding or treatment of the condition which makes

the subjects vulnerable.

This last statement implies that, to the extent that drug abuse liability

testing sheds light on those conditions which are predispositions or more

likely to be associated with drug abuse and dependence, it is more justifiable

to do such research with subjects who are vulnerable because they are

already drug abusers. In order to determine what are appropriate groups

for a particular research study, a researcher needs to identify those attributes

that would permit adequate testing of the research hypothesis. As Levine

has pointed out,

In most biomedical and in some behavioral research, those

attributes can and should be stated precisely in biological

terms. In some behavioral and most social research, the

attributes can and should be stated in social terms. An

adequate statement of biological or social attributes that

establishes eligibility for participation in a project includes

criteria for exclusion as well as inclusion.

Levine 1986, p. 92.

As a further corollary of this, one needs to consider what is meant by socalled normal controls or healthy volunteers. Levine again points out,

It should be recognized there are no such persons. Normality

and health are states of being that cannot be proved

scientifically. Thus, such individuals should be described

in scientific publications and research protocols as being

free of certain attributes of non health or non normality.

Levine 1986, p. 93.

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For the research in question here, normal controls often means individuals

who either are totally drug naive or who used drugs but did not exhibit

compulsive or excessive use of such agents.

SELECTION OF SUBJECTS

Subjects to be used for human abuse liability testing can initially be

divided into two groups: treatment seeking volunteers and non-treatment

seeking volunteers. Treatment seeking refers to individuals in trouble

with drugs and seeking help for such problems. In general, it would seem

inappropriate in drug abuse liability testing to use treatment seekers unless

such individuals would derive some direct benefit from their participation.

Without that, the risk of prolonging the abuse or, even worse, having the

individual change his/her mind about wanting treatment and go back to

drug use would appear to outweigh the potential benefits to the larger

society.

Left unanswered by this simple approach are two questions: Is it

appropriate to use as subjects those seeking treatment for abuse of one

category a drug of another category to test; and, is it ethical to use

individuals who are seeking treatment but not for drug abuse, such as

cancer patients who are seeking relief from pain. In regards to the first

question, is it ethical to give a potential drug of abuse, say of the

benzodiazepine group, to an individual seeking treatment for abuse of a

morphine type drug or vice-versa? The underlying question here arises

from the observation that there are major population differences between

drug abusers and others in the liability to abuse certain drugs, raising

implications for using that population in the testing. There are drugs that

appear to have major addictive liability regardless of the psychologic or

biologic characteristics of the population tested, and others that seem

more limited in their appeal and are abused primarily by individuals who

have already shown some propensity to abuse drugs.

A possible answer at this point might be that certain drugs, on the basis

of their similarity to drugs with previously established high abuse liability

and as a result of defined animal testing appear to be of high abuse

liability, should not be given to any individuals seeking treatment. On the

other hand, drugs with a predicted low abuse potential in relation to the

above information might possibly be given individuals seeking treatment.

Anexampleof this could be the use of a benzodiazepine in certain anxious

opiate or stimulant addicts. Opiate addicts maintained on methadone are

346
well known to abuse certain benzodiazepines such as diazepam and

lorazepam. However, they appear less likely to abuse oxazepam (Kleber

1986, DuPont 1988). Since anxiety is a common problem among opiate

and cocaine abusers, a benzodiazepine that would be useful in treating

anxiety in such patients and yet not be abused would appear to be of

therapeutic benefit. It might thus be ethical to test such a drug on such

treatment seeking patients.

In terms of the second question mentioned above, that is, whether

individuals seeking treatment but not for drug abuse, such as cancer

patients, should be used as subjects for abuse liability testing, again there

might be situations in which they are potentially recruitable. If one has

a potential new opiate, it might be reasonable to test in pain patients, to

ask the question whether it would be self administered beyond the analgesic

relief. Similarly, benzodiazepines need to be tested in patients seeking

treatment for anxiety even though a certain percentage of them may abuse

the drug. It would still appear ethical to test such drugs in these patients

for abuse liability while recognizing the results would have limited

generalizability.

One also has to be careful not to see drug abuse where it does not exist.

I was involved recently in testimony before the Expert Committee on

Drug Dependence of the World Health Organization (WHO) around the

issue of whether clonidine should be scheduled. Clonidine, an alpha 2

adrenergic agonist has been used since 1978 to treat opiate withdrawal

(Gold et al., 1978) and, more recently, to treat withdrawal from alcohol

and nicotine. Unlike opiates which relieve opiate withdrawal by cross

tolerance, clonidine appears to do it by its actions on the locus coereulus

and noradrenergic activity. In general, clonidine does not have desirable

psychic effects and there are less than a dozen cases reported of possible

drug abuse (Schaut and Schnoll 1983), even though it has been given to

millions of people in the decades it has been used to treat hypertension.

However, because it was found in one country to be used by street opiate

addicts, the assumption was made that it must be a drug of abuse.

Overlooked was the more likely possibility that the drug was used to self

medicate opiate withdrawal when narcotics were not available. As one

who has tried to use clonidine for over 10 years in opiate withdrawal and

much of the time has had difficulty getting patients to accept it, it was

abundantly clear that clonidine is not a drug of abuse and fortunately the

Expert Committee agreed with this assessment. The case points up,

however, how easy it is to leap to certain conclusions from inadequate

data bases and the importance of using a variety of indices to prove that

a drug is one of abuse.

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Historically, much of the early research on drug abuse liability testing in

humans was done at the Addiction Research Center (ARC) at the Public

Health Service Hospital in Lexington, Kentucky. The subjects were

prisoners recruited from the prison population at the hospital who

volunteered to take part in the various research projects at the ARC. Since

they were prisoners, they probably would not be considered treatment

seeking individuals, but on the other hand, given the restrictions on using

prisoners for research study, it is likely that such research would not be

permissible in today’s climate. Prisoners are seen as vulnerable subjects

because their consent may not be freely given (Levine 1986). Since they

may not be truly free to refuse to participate and may be excessively

influenced by considerations of money or early release, DHHS regulations

restrict the type of permitted research. Lasagna has argued, however, that

the work done at Lexington at the ARC is very difficult to do in alternative

populations (Lasagna 1977).

One general reason for not using treatment seekers relates to the

observation that today’s drug abuser is more likely to be a polydrug user

than an individual who sticks with one drug. However, even while using

a variety of drugs there is usually one main or favorite drug for most of

such patients. Our clinical experience with cocaine abusers, for example,

suggests that one common reason for relapse when abstinent from cocaine

for a period of time, is use of drugs that they were not previously addicted

to, such as alcohol or marijuana, but which were often used in combination

with cocaine. The feeling induced by these drugs serves as a conditioned

cue leading the individual to crave the preferred drug while, at the same

time, the altered state weakens the individual’s ability to stay away from

the preferred drug. Based on the work of Wikler and associates (Wikler

and Pescor 1967) the conditioning laboratory at the University of

Pennsylvania run by Dr. O’Brien and his associates has emphasized the

role of conditioned cues in drug seeking behavior (O’Brien et al., 1986,

Childress et al., 1988).

The next group of potential subjects are those recruited as volunteers,

usually in return for monetary compensation. In theory, there are three

sub-groups of individuals in the voluntary population among whom abuse

liability might be quite different: individuals with a history of some form

of drug abuse; individuals without such history, and also without any

symptomatology that would require treatment by any of the drugs in

consideration; and a third group that does have symptomatology such as

anxiety, depression, pain or insomnia, for whom these drugs might be

prescribed for clinical reasons. Since it appears that certain drugs may be

more likely to be abused by individuals with an abuse history it would be

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useful to include in the testing some such individuals. Individuals without

such a history are necessary in order to obtain some estimate of whether

the drug is likely to be abused by so called normals. Finally, one gains a

very different kind of information by testing individuals who exhibit

clinical symptoms. Some anxious individuals will not abuse

benzodiazepines while others will.

Thus, among recruited volunteers there are two broad groups and subgroups. The broad groups would be drug naive individuals and individuals

with some history of drug abuse. For drug naive individuals, the question

can be asked, is it ever appropriate to give a drug that the individual is

naive to? There is no firm answer to the question. Some would argue that

it is never ethical to give a drug to someone naive to that class of drug.

Others would argue that the decision to use such individuals relates to the

addictive liability of the class of drugs being studied. It may be more

appropriate to use such individuals with drugs of predicted low abuse

liability such as a benzodiazepine and much less appropriate for drugs of

predicted high abuse liability such as stimulants. This begs the question

of drug classes with intermediate liability such as analgesics and other

sedatives. Although there are not as many epidemiologic studies as one

would like on this subject, the few extant suggest that most individuals

who try narcotic type drugs for non-medical purposes on a few occasions,

do not go on to become addicted. The same is probably true for addicting

sedative type drugs such as barbiturates. Likewise, the vast majority of

individuals who take either of these two classes for a specific medical

indication do not end up continuing their use after the medical indication

has ceased. Thus, the answer for these two classes of drugs is less obvious

than for the benzodiazepines, on the one hand, or stimulant drugs on the

other. (There are also, of course, major variations within a class so that,

for example, a stimulant such as caffeine may have less abuse liability

than a member of another class).

Among drug users, again there are two general groups: users naive to a

particular drug class being studied and users experienced with that

particular drug class. One could further differentiate the class naive users

into controlled users, who have used drugs but always in a controlled

fashion, and individuals who have shown compulsive behavior to one or

more classes of drugs but not to the particular class being studied. Among

users experienced with a particular drug class, one has individuals with

a history of control and those who have demonstrated compulsive addicted

type behavior. Thus the question gets raised again - is it ever appropriate

to give a drug class that an individual is naive to? If individuals are

experienced in benzodiazepine use, can one ethically expose them to

drugs such as stimulants and opiates or vice-versa. There appear to be,

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among benzodiazepine users who become dependent on the drug, three

categories. First, individuals who exhibit dependence on the drug at

therapeutic dosage levels and who, although they have not escalated use,

find it very difficult to stop the use even when their physician feels that

they should. A second group of individuals are primarily multiple drug

abusers with the benzodiazepines used as one among a variety of drugs.

A third group of individuals abuse benzodiazepines at very high doses to

achieve an intoxicated drunken state. Whereas existing data suggest

individuals who abuse the benzodiazepine class are more likely to be

individuals who have abused other drugs including alcohol, this appears

to be less true among persons who became addicted to opiates. Many of

them prior to exposure to opiates had not abused other drugs, although

they may have used substances such as alcohol and marijuana. Although

iatrogenic opiate addiction is not common, it occurs often enough that

one recognizes it can happen to certain individuals. A substantial number

of the soldiers at risk in the military zone during the Vietnam War became

abusers of heroin. The subsequent cessation of such behavior for most

when they left Vietnam suggests that the degrees of addictiveness of this

class of drugs as with many other drug classes depends in part on the

setting and the psychological state of the individual (Robins 1974).

Stimulants are even further removed from the benzodiazepines and tend

to have a relatively high abuse liability even in individuals who have

shown no previous tendency toward drug abuse. Route of use, availability

and setting, however, are factors here as well. Clinicians working with

cocaine abusers often note their surprise that a particular patient has

become a cocaine addict when there appears to be no significant

psychopathology or prior drug abuse. Having said that, it is still important

to keep in mind that the best predictor of cocaine use is heavy recent

marijuana use. Among individuals who have used marijuana less than 10

times, use of cocaine is very unlikely. Among individuals who have used

marijuana 100 times (e.g., averaged twice a week for a year), 75 percent

of such individuals are likely to have at least tried cocaine and 15 percent

will have used cocaine in the last month (Clayton 1985).

The problem therefore arises that it is not always possible to predict, from

structure or animal studies, abuse liability, for example, whether a particular

benzodiazepine is more like diazapam or oxazapam. While there are

certain clues that one can obtain from pharmacokinetic data such as speed

of onset, these may not always be reliable indicators. Therefore, one may

be best off starting with experienced users or. even better. with abusers.

If such persons like a drug and their behavior suggests they would abuse

the drug if available, one still does not know whether non-abusing

individuals would abuse it. Conversely, however, it is probably safe to

surmise that, if persons with a drug abuse history do not abuse such a

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drug, it is probably safe, for the most part, for persons without such a

history. One should also keep in mind one might be thinking of heavy

users rather than abusers in some circumstances.

From a regulatory point of view, if a drug is used and found “interesting”

by abusers, should it be considered a drug of abuse or must it also be

abused by naive subjects. As these data pile up, it will ultimately shed

light on vulnerability to drug abuse in various population sub-groups and

could be eventually used in prevention campaigns. Admittedly, of course,

prediction even when related to class abuse liability is not infallable.

Experienced clinicians have often encountered patients who are cocaine

addicts who do not like opiates and, conversely, opiate addicts who do not

like cocaine. Although there have been speculations about the selfmedicating aspects of such drug choices and other rationales, we are still

not very good at predicting the likelihood of any given individual becoming

a cocaine addict or an opiate addict. This would suggest that it is important

to test for drug abuse liability in individuals who are naive to that class

of drugs even if they abuse other classes.

Thus a number of permutations and problems arise from the need to know

whether certain drugs are attractive primarily to individuals with a drug

abuse history as opposed to the larger population. Risk benefit ratios

arise in such circumstances as manufacturers have to decide whether the

purported advantages of a new drug outweigh its possible abuse liability.

Even with very addicting drugs like cocaine, data from the 1985 National

Household Survey suggest that for every eight individuals who try it, two

continue to use it and one becomes a problem abuser or compulsive user.

Thus roughly 25 percent of individuals who try cocaine continue to use

it at least once a month and roughly half of these get into trouble with the

drug. This is in contrast to alcohol, for example, where estimates suggest

that of those individuals who continue to use alcohol after their first drug

exposure, only about 10 to 15 percent get into trouble with the drug.

One needs a strong rationale for giving drugs of suspected serious abuse

liability to either naive users or experienced abusers. There could be

important therapeutic issues involved. For example, we could use an

opiate with a better side effect profile. In order for the manufacturer to

proceed with such an important compound, one would need animal data

suggesting the better side effect profile and some efficacy testing even

before testingforabuse liability. However. not too soon after, the liability

testing should be done to avoid heavy development cost for a drug that

ends up too addictive to be marketed. A new opiate with fewer side

effects but more addictive liability would probably not be welcomed.

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INFORMED CONSENT

Much has been written about the issue of informed consent and the most

appropriate way to obtain it. This section will not explore all of the

permutations but will primarily cover what is relevant for human drug

abuse liability testing. For the consent of a subject to be valid, it must be

legally competent, voluntary, informed, and comprehending or

understanding. The relationship between the investigator and the subject

differs from ordinary business transactions in which each party is

responsible for informing themselves of the terms and implications of

their agreement. Professionals who are acting upon the lives and health

of others are held to a higher standard and are obliged to inform lay

persons of the consequences of their mutual agreement (Levine 1986).

Creating a condition of informed consent involves both adequate

informing, and paying attention to the process of consenting. The

investigator needs to disclose information that will be relevant to the

subject’s decision whether or not to participate. Such information needs

to include:

1.

2.

3.

4.

5.

6.

The nature of the research project;

The procedures of the study;

The potential risks and benefits;

Assurance that the participation is voluntary. (As a corollary of this,

subjects need to know they can withdraw from the project at any time

and that such declining to participate or withdrawing will not result

in any penalty or loss of benefits);

Protection of confidentiality; and

The opportunity to ask questions.

Researchers need to be aware that the process of consent is more important

than simply getting the subject’s signature on a form. Brady noted in

1979, “a consent form does not informed consent make.” He pointed out

that the usual approach to informing is not the best design for getting the

subject to understand in a meaningful fashion and suggested instead that,

for complicated research activities, subjects would understand more if

they were brought into the research environment and allowed to experience

its routines and procedures (Brady 1979).

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Human abuse liability testing raises certain issues relating to informed

consent in the type of subjects often used. Consent, for example, may be

invalidated by lack of comprehension such as produced by being under

the influence of the drug. Persons under the influence may range from

having very little trouble comprehending to having a total inability to

comprehend. In other cases, the drug use may lead individuals to

overestimate their capabilities and abilities to deal with the procedures.

Informed consent, therefore, needs to be acquired when the individual is

judged to be not intoxicated and able to comprehend the procedure (Levine

1986).

A second issue relates to what subjects should be told about the class of

drugs to be studied. Should the exact class (e.g., stimulants) be divulged

or only that the drug to be administered might be a stimulant, sedative, or

inactive compound? The latter approach appears preferable in that

sufficient information is being provided without compromising the

research aim. How should the wording be done? Is the subject to be told,

in essence, that the purpose is to measure abuse liability or only that he/

she is being asked how much he/she likes or values the feeling of the

drugs to be given. The latter approach again appears the preferable one

but, under risks and benefits, the possibility that the drug could be one of

abuse or dependence needs to be listed.

A third issue is confidentiality. Since some subjects will be individuals

with a history of drug abuse or dependence, it is important that subjects

be protected from the consequences that would occur if information about

that were disclosed to employers, insurers, legal authorities, or even to

significant others in the environment. Confidentiality may be breached

if sensitive information is accidently disclosed, if the research records are

subpoenaed, etc. Strategies that have been listed toprotectconfidentiality

include storing the data in locked file cabinets, coding it to hide the

identity of subjects, those having access to the research data destroying

it after the study is completed, and insuring that individual subjects not

be identified when the findings are published. Researchers also may

obtain confidentiality certificates from DHHS and the Department of

Justice which allows the identification of research subjects to be withheld

even if the research records are subpoenaed. Potential threats to

confidentiality as well as measures that investigators will take to protect

it should be discussed explicitly with the subjects before they have to

decide to participate. Researchers should be careful not to make promises

about confidentiality that are impossible to uphold (Lo et al., 1988).

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Institutional review boards are required under DHHS regulation to review

proposed research to insure that it is ethically acceptable and that the

welfare and rights of subjects are protected. It is important to keep in

mind that the Institutional Review Board (IRB) system is not a central

one; that is, each local IRB interprets and implements federal regulations

using its own forms and guidelines. The IRB system does not insure that

research is ethically acceptable. Individual boards may place emphasis

on consent forms and on the risks and benefits of the research rather than

on other ethical issues. Review of the scientific design which can be an

important ethical issue, and of the approach in selecting subjects, is often

left to the funding agencies and their external panels.

CONCLUSION

In the past three decades a number of drugs have been introduced into the

marketplace as non-addicting but turned out otherwise. Meperidine,

methaqualone, and pentazocine are the best known examples that come

to mind. Although these drugs do not produce the major drug abuse

problem of heroin or cocaine, concern in general over diversion of licit

drugs to the illicit market and of iatrogenic addiction has led to enormous

paperwork, detailed regulation, and physician underprescribing of needed

analgesics. Earlier papers have shown that the knowledge base exists

today for rational human drug abuse liability testing that can enable

regulators, manufacturers, researchers, and physicians to have a much

more scientific basis to predict potential abuse liability. This paper has

laid out the human subject issues necessary to consider when doing such

testing. Since animal testing remains imperfect for these purposes, it

appears likely that human testing will remain necessary for a substantial

period to come.

354
REFERENCES

Brady, J.V. A consent form does not informed consent make. IRB: Rev Human Subj

Res 1:6-7, 1979.

Childress, A.R.; McLellan, A.T.; Ehrman, R.; and O’Brien, C.P. Classically

conditioned responses in opioid and cocaine dependence: A role in relapse?

In: Ray, B.A., ed. Learning Factors in Substance Abuse. National Institute on

Drug Abuse Research Monograph No. 84. DHHS Pub:No. (ADM)88-1576.

Washington, DC.: Supt. of Docs., U.S. Govt. Print. Off., 1988. pp. 2543.

Clayton, R.R. Cocaine use in the United States: In a blizzard or just being snowed?

In: Kozel, N.J.,and Adams, E.H., eds. Cocaine Use in America: Epidemiologic

and Clinical Perspectives. National Institute on Drug Abuse Research

Monograph No. 61. DHHS (ADM)85-1414. Washington, D.C.: Supt. of

Docs., U.S. Govt. Print. Off. 1985. pp. 8-34.

Department of Health and Human Services Rules and Regulations. Title 45; Code

of Federal Regulations; Part 46: Revised as of March 8, 1983. Washington,

D.C. U.S. Dept. of Health and Human Services, 1983.

DuPont, R.L., ed. Committee of the Institute for Behavior and Health, Abuse of

Benzodiazepines: the Problems and the Solutions. Am J Drug Alc Abuse 14

(supp. 1):1-69, 1988.

Gold, M.S.; Redmond, Jr., D.E.; and Kleber, H.D. Clonidine blocks acute opiatewithdrawal symptoms. The Lancet: 599-602, September 16, 1987.

Kleber, H.D. The use of psychotropic drugs in the treatment of compulsive opiate

abusers: The rationale for their use. Adv Alcohol Substance Abuse 5: 103-

119, 1986.

Lasagna, L. Prisoner subjects and drug testing. Fed Proc 36:2349-2351, 1977.

Lo, B.; Feigal, D.; Cummins. S.; Hulley, S.B. Addressing ethical issues. In: Hully,

S.B. and Cummings, S.R. eds. Designing Clinical Research. Baltimore:

Williams &Wilkins, 1988, pp. 151-158.

Marwick, C. Philosophy on trial: Examining ethics of clinical investigations. JAMA

260:749-751, 1988.

The National Commission for the Protection of Human Subjects of Biomedical and

Behavioral Research: the Belmont Report: Ethical Principles and Guidelines

for the Protection of Human Subjects of Research. DHEW Pub. No. (05)78-

0012. Washington, D.C.: U.S. Govt. Print. Off, 1978.

O’Brien, C.P.; Ehrman, R.; and Temes, J. Classical conditioning in human opioid

dependence. In: Goldberg, S.R., and Stolerman, I.P. eds. Behavioral Analysis

of Drug Dependence. Orlando, FL: Academic Press, 1986, pp. 329-356.

Robins, L. The Vietnam Drug User Returns: Final Report, Sept. 1973. Special Action

Office Monograph, Ser. A, No. 2, Washington, D.C.: U.S. Govt. Print. Off.

1974.

Schaut, J., and Schnoll, S.H. Four cases of clonidine abuse. Am J Psychiatry 140:1625

1627, 1983.

Wikler, W.A., and Pescor, F.T. Classical conditioning of a morphine abstinence

phenomenon, reinforcement of opioid drinking behavior and “relapse” in

morphine addicted rats. Psychopharmacologia 10:255-284. 1967.

355
ACKNOWLEDGMENTS

This paper was supported by NIDA grant No. P50DA04060.

AUTHOR

Herbert D. Kleber, M.D.

Professor of Psychiatry

Yale University School of Medicine

Director, Substance Abuse Treatment Unit

Connecticut Mental Health Center

34 Park Street

New Haven, Connecticut 06519

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CHAPTER 17

Issues in Human Drug Abuse Liability Testing:

Overview and Prospects for the Future

Joseph V. Brady, Ph.D.

INTRODUCTION

The contents of this volume bear eloquent testimony to the great strides

that have been taken over the past decade or more in the testing of drugs

for abuse liability in humans. Less than 20 years ago there was virtually

only one location in the world where the systematic study of drug

dependence and abuse could be conducted with human subjects. The

successors to those pioneers from the original Addiction Research Center

(ARC) in Lexington, Kentucky who have contributed to this volume can

point with pride to the roots from which this productive research technology

has emerged. The early focus of these laboratories upon opioids clearly

served to advance the basic scientific purpose of pharmacologically

characterizing suchcompounds and facilitating development of safer and

more effective therapeutic agents while reducing the risks of dependence

and abuse. Most of the drugs upon which attention has continued to focus

have well-defined current or potential clinical utility. Knowledge of their

dependence potential and/or abuse liability is of obvious importance with

respect to scheduling both within the United States and internationally.

Under such circumstances, appropriate evaluation, to the extent that it is

possible, prior to marketing is in everyone’s best interest to avoid iatrogenic

dependence and/or self-generated abuse as well as later scheduling after

an expensive post-marketing experience.

We recognize, of course, that dependence and abuse are but some of the

costs, along with other adverse side effects, that must be weighed against

a drug’s potential therapeutic efficacy. Ordinarily, a drug will not be

tested for dependence potential and/or abuse liability until other aspects

of efficacy and safety have been evaluated in a scientifically sound and

systematic manner. It is of obvious importance then, that the assessment

techniques that provide estimates of dependence and/or abuse risks meet

the highest standards of validity and reliability. Such standards can be

attained however, only when procedural foundations are conceptually

and methodologically sound. Fundamental issues, in this respect, focus

upon the identification, definition, and measurement of adverse effects in

general, and drug abuse in particular, as manifest in the natural ecology.

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CONCEPTUAL AND DEFINITIONAL ISSUES

In this latter regard, the interchangeable quasi-technical use of terms like

“addiction,” “dependence” and “abuse” as imprecise referents for a

bewildering range of phenomena and experiential pseudo-phenomena

continues to produce a degree of semantic and taxonomic confusion that

is perpetuated in even the most current and authoritative treatments of the

subject (e.g., Rinaldi et al., 1988; Johanson et al., 1987). The terms

themselves, persistently reified as substantive noun “things” that enter

into subject-predicate relationships with other “things” (and affect, as

well as are in turn affected by these other “things”), are seldom accorded

appropriate conceptual status as constructs emerging from observed

relationships between specifiable antecedents (biological and social) and

definable consequences (biochemical, physiological, and behavioral).

Within this relational context, the analysis of interacting biological and

behavioral events would seem to provide a basis for defining these

constructs more operationally and specifying the conditions under which

a unifying conceptual framework can be developed for this prominent

aspect of drug use and misuse.

At least some definitional clarity has been attained by dividing the vast

array of events that characterize this domain into two reasonably exclusive

categories based upon explicitly operational criteria (Brady and Lukas

1984). Such a division is illustrated in figure 1, for example, by

distinguishing between events that occur before and events that occur

after actual substance intake. The defining operations of the “before”

class, on the one hand, include proactive drug-seeking, drugdiscrimination, and drug-taking behaviors. The defining operations of

the “after” class, on the other hand, emphasize the reactive biochemical,

physiological, and behavioral changes associated with tolerance and an

abstinence syndrome when drug is withdrawn. Interactions between

these proactive and reactive processes are of course, commonplace but

their relative contributions vary with different pharmacological agents as

a function of dose, environmental circumstances, and previous drug history

(Mendelson and Mello 1982). Even more to the point of the topic to

which this volume is addressed, the methods used to evaluate these

distinguishable pharmacological actions are quite different.

The procedures described for human drug abuse liability testing in the

present volume for example, share a clear focus upon proactive drug

seeking and drug taking measures (i.e., reinforcing functions and selfadministration performances). In addition, the treatment of self-report

(i.e., “subjective effects”) and drug discrimination measures emphasize

their close conceptual and procedural ties. In contrast, little attention has

been focused upon the reactive physiological-dependence measures that

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characterize tolerance and withdrawal. The relevance and importance of

this distinction between the proactive abuse liability and reactive

dependence potential operations resides in the fact that from the perspective

of drug abuse liability testing in humans - the topic to which this volume

is addressed - their defining functions are not coextensive, they do not

invariably occur together, and the methods by which they are evaluated

differ. Proactive drug-seeking, drug discrimination, and drug selfadministration performances as cardinal signs in the assessment of abuse

liability for example, can be maintained in strength by use patterns and

doses of compounds (e.g., cocaine) that produce no significant tolerance

or withdrawal - the reactive changes traditionally associated with

dependence potential. On the other hand, there are tolerance and

abstinence-producing compounds (e.g., propranolol) that neither generate

nor maintain drug self-administration.

It is important to emphasize that these distinctions between abuse liability

and dependence potential are not merely academic since they bear directly

upon the issues of validity and reliability. The methodological

contributions described in the present volume document several

converging lines of evidence - convergent operations, if you will - that

Figure 1: Schematic characterization - Drug abuse liability and dependence

processes.

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confirm the reliability and broad generality of observations relating the

functions of drugs as both discriminative and reinforcing stimuli to the

drug seeking and drug taking behaviors that define misuse and abuse.

Moreover, the orderliness of the data relating these stimulus functions to

independently derived measures of a drug’s physicochemical properties

and pharmacological activity (Griffiths et al., 1978; Brady et al., 1983),

speaks directly to their construct validity in evaluating the contribution

of such testing procedures for the assessment of abuse liability. But the

issue of predictive validity on the other hand, has continued to plague

even the most conscientious efforts precisely because it has been unclear

as to just how drug abuse - the purported phenomena to be predicted - is

to be appropriately identified, defined and measured in the natural ecology.

Despite the persistence of differing opinions in these regards, operations

that involve drug seeking, drug discrimination, and drug taking

performances are clearly recognized as prominent and common features

of the misuse and abuse process.

The point here of course, is that the validity of human testing procedures

for assessing the stimulus functions of drugs are not to be judged on the

basis of predicting “drug dependence” (i.e., tolerance and abstinence) nor

even “drug abuse” (i.e., drug seeking and drug taking plus behavioral

toxicity). Rather, their predictive validity resides in the evaluation of

“abuse liability” (i.e., the likelihood that a given physiologically or

behaviorally toxic substance will maintain drug seeking and drug taking

under at least some conditions). An extensive array of biochemical

substances have abuse liability under some conditions within the

framework of this definition, and an evaluation of the stimulus functions

of drugs provides information about at least these prominent aspects of

the assessment process. To this extent, human drug abuse liability testing

can be seen to have “face validity.” Not only can it be determined whether

there are at least some conditions under which a drug will be discriminated

and self-administered (i.e., evidence of “inherent” reinforcing and

discriminate functions), but to a significant extent, the range of those

conditions can be defined (i.e., differences related to physicochemical

structure, dose, time course, etc.) and the influence of circumstances (i.e.,

environmental contingencies, deprivation, etc.) in potentiating or

attenuating such stimulus functions can be evaluated.

This broader environmental perspective of course, emphasizes not only

the complexity of the etiologic and maintaining factors that characterize

drug abuse but as well the web of social myths that surround the domain.

These myths and expectations function in curious ways to exacerbate the

problem by perpetuating notions and explanations that endow terms like

“addiction,” “loss of control” and “abstinence avoidance” with unde360
served explanatory powers (Levine 1978; Mello 1972; Maisto and Schefft

1977; Falk 1983). One advantage of the human testing situation should

be its operational orientation which, though certainly not culture-free in

any literal sense, does strive for definitional precision in clarifying the

variables which institute and maintain drug abuse as well as the range of

associated behavioral antecedents and biomedical consequences. Of

particular interest in this regard for example, is the experimental evidence

that the environmental context in which drug-taking occurs can

dramatically alter the reinforcing function of even the most abusable

substances. This contextual malleability of a drug’s reinforcing efficacy

has recently been documented with both cocaine (Spealman 1979) and

nicotine (Goldberg and Spealman 1982) revealing that both drugs can

have either pronounced reinforcing or punishing effects depending upon

environmental contingency conditions. Such contextual malleability may

well hold the key to at least some of the apparent inconsistencies in the

results of human drug abuse liability testing. Furthermore, the results of

recent laboratory studies suggest that excessive and chronic substance

misuse and abuse may represent a set of behaviors for which others might

have substituted (and intermittently do) rather than a highly specific

disorder or disease state (Falk and Tang 1988; Vuchinich and Tucker

1988).

METHODOLOGICAL ISSUES

As a corollary of this contextual malleability of course, it must be

recognized that there is a degree of inter-individual variability in reactivity

to various chemical substances and that this reactivity can be modified by

prior drug experience. This complicates the problem of insuring the

validity and reliability of human drug abuse liability testing and requires

not only assurances with regard to proximal drug free exposure in

assessment settings but controls for drug-taking histories. Simple random

assignment to drug and control groups is not likely to be sufficient in

assuring the adequacy of an evaluation based on small samples. Care

must be taken as well to insure the representatives of the population tested

are distributed equally with respect to such obvious factors as age and

gender. Likely attrition rates in human drug abuse liability studies that

take weeks or months to complete (including follow-up) must be

anticipated in screening volunteers and establishing incentive conditions.

Important considerations relevant to endpoint analysis must be taken into

account as well to avoid loss of data for those who do not complete the

testing since those compliant with long and difficult studies are not always

representative of the general population of potential absers.

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ETHICAL ISSUES

In a volume so richly endowed with experienced and sophisticated authorinvestigators, these obligatory prescriptions must seem like so much

“carrying coals to Newcastle.” But in focusing on the human element in

the drug abuse liability testing process, they do call attention to the ethical

issues that must be confronted in evaluating the state of the art and science

in this continuingly controversial domain (Brady 1979b). In keeping

with my penchant for definitional priorities, let me first address the topic

from the conceptual and methodological perspective that my card-carrying

radical behavioral credentials require. Ethics would seem to be most

parsimoniously viewed as a composite of values and morals. Values are

the things people say are important to them - “justice,” “liberty,”

“happiness” - and are for the most part abstractions. Morals, on the other

hand, are the practices which the community rewards and punishes -

“mother love,” and “double parking.” These foundations of our ethical

standards are of course not immutable and can often be inobvious conflict

- people have been known to say one thing and do another, in case you

hadn’t noticed! All of which is by way of acknowledging that we live in

a consequentialist society and our standards, even our ethical standards,

change as our practices bring us into contact with the environmental

effects of those performances.

But the ethical issues raised by the use of human participants in testing

the abuse liability of drugs are certainly not new or unique. Their roots

can be traced at least as far back as the ancient controversies of vivisection

and the more modem conflicts that have developed in the wake of the

industrial revolution and the “fear of technology.” And although

technological transposition and public policy continue to provide the

common thread which binds the problematic aspects of all human

experimentation, it is of interest to consider why human drug abuse liability

testing studies of the type so extensively treated in this volume are likely

to attract special scrutiny.

There is one fundamental set of relationships which, if not unique to

human drug abuse liability testing initiatives is at least displayed with

“lightning rod” prominence in the “helping professions” at the forefront

of these efforts. A basic concern in this regard focuses upon the so-called

“boundarv problem.” Understated in obviously oversimplified form, it

is not always crystal clear to either the patient-subject or doctor-researcher,

much less to the spectator-public, just where the practice of the “helping

professions” ends on the one hand, and the conduct of drug testing and

orresearchbegins on the other. The difficulty in establishing this boundary

arises largely because the setting, personnel, and maneuvers which

characterize these interacting domains are frequently the same. Moreover,

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human experimentation with its primary objective of generating new

knowledge rather than helping a given individual was not differentiated

conceptually before the 19th century. Until that time, it was embedded

in the context of practice with no special ethical obligations formulated

since the ethic governing practice (i.e., “no harm,” “preserve life”) was

presumed sufficient for such experimental efforts generally viewed as

attempts at patient benefit.

But the blurring of this boundary between research, testing, and practice

can now be seen to have profound ethical significance, first and obviously

because of the potential for conflicts of interest; and secondly because of

the different ways in which uncertainty is to be viewed in the two

enterprises. In the first instance, conflicts arise because the patientsubject who places himself in the hands of a practitioner-researcher does

so primarily, if not exclusively, for personal benefit; whereas the doctorinvestigator who accepts responsibility for invasion of the person

commonly takes a much broader view of the benefits to be derived from

the quest for new knowledge. At a minimum, under such circumstances

there is the potential for a conflict of objectives, if not of methods and

procedures. In the second instance, the conditions of uncertainty involved

in the practice of a professional with a person presenting for direct

individual treatment benefit are, by tradition, a private matter between

doctor and patient with less stringent requirements for public scrutiny.

On the other hand, the hypotheses and uncertainties associated with testing

and the research quest for new knowledge - rather than direct individual

benefit - clearly call for evaluation and validation by public assessment

since the public is presumed to be the beneficiary of such new knowledge

and must, for the most part, bear the burden (i.e., costs) of the research

activity involved in its acquisition.

For all of these reasons, it has now become a matter of some import to be

able to distinguish between drug testing research and medical practice

since they are obviously under somewhat different contingency controls.

Research and/or drug testing, for example, are clearly activities directed

toward the development of or contribution to new or at least generalizable

knowledge. They are characterized by explicit objectives and formal

procedures designed to attain these objectives. Both are commonly set

forth in a testing and/or research protocol.

This research and/or testing activity must be distinguished from the

engagement in professional practice solely for the enhancement of an

individual’s well-being, with reasonable expectation of success as the

standard. Indeed, the maintaining consequences of the “routine and

accepted practice of’ the helping professions have, by long and honored

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tradition, focused exclusively upon patient benefit. There are, of course,

instances where testing and/or research on the one hand and practice on

the other, may coexist as is apparent from the contents of this volume

(e.g., monitoring the effects and/or evaluating the effectiveness of

treatment), but the aims and purposes, if not the methods and procedures,

can, for the most part, be readily distinguished. Nonetheless, borderline

areas do exist like innovative therapy, practice for the benefit of others,

and nonvalidated practice. But the absence of precision or validation

upon which to base an expectation of success in practice does not of itself

define research and/or testing! Morally relevant concerns emerge on

both sides of a dilemma posed by the potential for bad practice in the

name of research on the one hand and research interference with treatment

or service delivery on the other. There is obvious need, in the best interest

of patient-subject and doctor-investigator alike, for clarification about

which procedures are essential for treatment and which are introduced for

research and testing purposes.

Among the more salient issues in this ethics domain is the so-called “risk/

benefit ratio.” While it is clear that some balancing of costs and returns

is necessary even in the domain of scientific testing investigations, the

very use of terms “risk” and “benefit” to characterize these normative

considerations in relationship to human drug abuse liability testing

activities may be inappropriate at best and prejudicial at worst. An

important advance is reflected in the emphasis upon “knowledge” as the

product of such activity rather then “benefit” in the sense that the latter

term is conventionally used in the context of professional practice. More

importantly, the use of the term “risk,” again carried over in large part

from the practice context, creates the presumption that such effort should

not be undertaken because of inherent “harms,” and that these “harms”

can only be outweighed by attendant “benefits,” again conceptualized

from the perspective of the individual “patient.” Considered from a

somewhat broader perspective, of course, all research and testing aims at

certain valued returns or outcomes (e.g., increased knowledge, scientific

understanding, helpful practical applications) and involves certain costs,

including in some, but certainly not all, instances, possible harms (i.e.,

either individual or societal). The ethical task, in the face of these potential

conflicts of obligation, simply said (but not so simply done!) is to insure

an equitable balance between these costs and returns.

Such a characterization of the research and testing enterprise accords

well, of course, with the basically “consequentialist” roots of normative

ethical principles in Greek thought and Judeo-Christian tradition. But the

conventional consequentialism of the practice ethic limits relevant

consequences, for the most part, to the individual patient, and by

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implication, limits experimentation and testing to that which is directly

beneficial for that individual. This creates obvious problems for the

moral justification of human drug abuse liability testing with such patient

populations based upon the social value of the generalizable knowledge

it produces. Indeed, the evident conflicts involved are clearly reflected

in the traditional discomfort of patients and practitioners alike with such

social value arguments in favor of research and/or testing participation

when personal welfare considerations are of prime concern.

The moral force of these individual concerns notwithstanding, all of the

recent codes which provide norms for the conduct and testing with human

subjects (i.e., Nuremberg, Helsinki, The United States Department of

Health Education and Welfare (DHEW), the American Psychological

Association (APA)) subscribe in principal to a “bonum communum”

defense of such initiatives. The countervailing influence to this “scientific

rationalism” has been the rise of “western individualism” emphasizing

self-determination as the basis of a political philosophy organized around

the interpersonal contract. Perhaps the most significant consequence of

this latter development has been the autonomous challenge to traditional

paternalistic ethical norms that accepted, without question, “benefit” as

a substitute for “consent.” As a result, the right of individuals, as

individuals, not to be “helped” is now being strongly defended.

Under such circumstances, it is hardly surprising that the “consent doctrine”

has become the dominant ethical issue in research and testing with human

subjects. The primary justification for requiring “informed consent,” as

distinct from a “consent form” (Brady 1979a), resides in the right of

individuals to self-determine the use of their own persons, independently

of any consideration of costs and returns. By implication, then, even

cases which involve negligible or nonexistent costs would require consent

to research participation. But what may not be so obvious is that this basic

self-determination justification of the consent doctrine is a double-edged

sword which also protects the right of an individual to participate in

research which may not be cost-free or even harmless. In fact, considering

these grounds alone, an argument can be made for limiting ethical oversight

obligations to insuring the adequacy of consent procedures in the

monitoring of research and drug testing activities.

Be this as it may, a second justification for the consent doctrine focuses

upon protection of the person by insuring awareness of research objectives

and procedures. At a minimum, this second justification preserves the

right of research participants to make judgments in terms of the person’s

own values rather than proceed on the assumption that investigator’s

“advancement of knowledge” objectives are necessarily synonymous

with “universal beneficence.” It is the two qualifying descriptors, “free”

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and “informed,” then that are presumed to express distinctions between

the self-determination and protection justifications of the consent doctrine.

It is usually possible in practice to estimate the “degrees of freedom” in

a choice situation by identifying alternative options. Infringements upon

such “voluntarism” (a term preferable to “freedom” from a behavioral

perspective) can be subtle in nature, however, and it is not morally sufficient

merely to limit “force, fraud, deceit, duress, over-reaching, or other ulterior

forms of constraint or coercion,” as the extant codes and regulations

require. True voluntariness depends upon the number of realistic options

available and the extent of the individual’s knowledge of these alternatives.

There is, of course, generally good agreement regarding the substantive

nature of the information which should be made available to research and

testing participants on the basis of a “reasonable person” (rather than a

“fully informed”) criterion. And no efforts have been spared to insure that

investigators inform research testing volunteers with respect to the

purposes, procedures, attendant discomforts, alternatives, and of course,

their right to withdraw at any time without prejudice. The regulations and

guidelines which have been promulgated in this regard provide for potent

contingency management of the investigator’s “informing” performances

by negatively consequating even the faintest suggestion of compliance

failure. But what of the human volunteers “knowing” or “comprehending”

behaviors? With rare exceptions, no provisions appear to have been made

for this “bottom-line” consideration in any of the ethical doctrines which

have emerged in the human subject domain. What appears to be at issue

is the “knowingness” of the subject and the evident difficulty in making

determinations thereof based in-whole or in-part upon an evaluation of

the investigator’s informing behaviors. Even in those majority cases

(hopefully!) where the subject can be presumed to have taken an active

role in the information transfer, the formal characteristics of the procedure

frequently suggest a heavy dependence upon “echoic” control (Skinner

1957) of the consent response. Parallels involving recitations of the

“Lord’s Prayer” or renditions of the “Star Spangled Banner”: (“Oh say

can you ...” consent) are not altogether facetious.

In contrast, of course, contingency management of the “knowing” features

of the procedure would require performance evidence that the subject’s

consent repertoire is under consequential rather than antecedent control.

Despite the hue and cry about additional burdens thus imposed upon the

research enterprise, there do appear to be some investigative settings in

which these basic requirements for “voluntary” and “knowing” consent

can be approximated. At least one enlightened approach has been

developed by Dr. Charles O’Brien at the Veterans Administration Hospital

and University of Pennsylvania School of Medicine in Philadelphia.

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Volunteers in Dr. O’Brien’s drug testing programs are provided with

instructional material and required to pass written and oral examinations

on relevant experimental procedures, and the possible consequences

thereof, before presentation of the consent formalities and participation

in the research and/or drug testing are permitted.

These examples are obviously somewhat parochial and leave many

difficult unanswered questions in research areas where the relevant

knowledge of the informed subjects is less readily determined. But they

do serve to emphasize the distinction between what is provided as

information by the investigator and what is comprehended by the subject

- more succinctly the distinction between “informed” and “knowing”

consent. And lest these differences appear to fall in the realm of trivial

semantic hair-splitting, consider the controversial subject-selection and

special testing population problems with which this issue makes contact.

Ethnic minorities and the poor, frequently with limited educational

backgrounds, are very often the most likely volunteers for the human

drug abuse liability testing programs which are the focus of this conference

report.

FUTURE PROSPECTS

But so much for preaching to the converted. What of future prospects?

It is obvious that explosive advances in new knowledgeof neurotransmitter

and receptor dynamics will greatly enhance the development of effective

therapeutic agents in areas that make direct contact with behavioral

interactions and their subjective collaterals. It is equally obvious of

course, that the very nature of such chemical interventions increases their

vulnerability to misuse and abuse. By the same token, the potential for

achieving unparalleled degrees of specificity in drug action afforded by

sophisticated neurochemical analyses should make it possible to identify

and parcel out desirable and undesirable features in characterizing the

pharmacological activity of therapeutically promising agents. A critical

element in this process will doubtless be the human assay methodologies

that have been the focus of the contributions to this volume. The continued

development and refinement of such human drug abuse liability testing

procedures must keep pace with the pharmacological advances that will

inevitably follow the progressive enlightenment produced by everexpanding neural and behavioral science initiatives.

It might be argued in fact, that such human drug assay procedures should

aspire to an even more prominent role in the advancement of safe and

effective pharmacologic agents to the extent that their intimate contact

with the behavioral repertoire of primary interest in this process - that of

367
the drug-taking human - makes them privy to effects and outcomes not

always anticipated in pursuing the pharmacological equivalence approach

to drug abuse liability testing. It seems reasonable to expect, for example,

that the feedback from such human drug testing evaluations will enhance

the process of drug development to the extent that valid and reliable

behavioral changes can be identified and operationally defined in the

productive give and take between the pharmacologists’ bench and the

clinical laboratory.

The final point to be made regarding the future prospects for human

testing contributions to drug abuse liability assessment calls attention to

one of the more complex issues in an already mind-boggling domain -

that of polydrug use and the effects of drug combinations. The relative

dearth of systematic research information in this area is of course a

reflection of the rather primitive state of knowledge regarding drug

interactions at the level of both the laboratory and the clinic. And yet it

is in precisely this area where the human testing facility is likely to make

a unique contribution to the evaluation of novel interaction effects.

Certainly, the current lively interest in human drug abuse liability testing,

generously reflected in the rich fare that graces this volume, more than

guarantees the availability of a well-grounded foundation for the

conceptual, methodological, and procedural advances that will berequired

to meet these present and future challenges.

368
REFERENCES

Brady, J.V. A consent form does not informed consent make. IRB 1(7):6-7,

1979a.

Brady, J.V. Perspectives on research with human subjects. The Behav Therapist

2(5):913, 1979b.

Brady, J.V., and Lukas, S.E. Testing Drugs for Physical Dependence Potential

and Abuse Liability. National Institute on Drug Abuse Research

Monograph No. 52, DHHS Pub. No. (ADM) 84-1332. Washington, D.C.:

Supt. of Docs., U.S. Govt. Print. Off., 1984.

Brady, J.V.; Lukas, S.E.; and Hienz, R.D. Relationship between reinforcing

properties and sensory/motor toxicity of CNS depressants: Implications

for the assessment of abuse liability. In: Harris, L.S., ed. Problems of

Drug Dependence 1982 National Institute on Drug Abuse Research

Monograph No. 43 Washington, D.C.: Supt. of Docs., U.S. Govt. Print.

Off., 1983. pp. 196-202.

Falk, J.L. Drug dependence: Myth or motive? Pharmacol Biochem Behav 19:385-

391, 1983.

Falk, J.L., and Tang, M. What schedule-induced polydipsia can tell us about

alcoholism. Alcoholism: Clin Exp Res 1988, in press.

Goldberg, S.R., and Spealman, R.D. Maintenance and suppression of behavior by

intravenous nicotine injections in squirrel monkeys. Fed Proc 41:216-220,

1982.

Griffiths, R.R.; Brady, J.V.; and Snell, J.D. Relationship between anorectic and

reinforcing properties of appetite suppressant drugs: Implications for

assessment of abuse liability. Biol Psychiat 13(2):283-290, 1978.

Johanson, C.; Woolverton, W.L.; and Schuster, C.R. Evaluating laboratory

models of drug dependence. In: Meltzer, H., ed. Psychopharmacology;

The Third Generation of Progress. New York: Raven Press, 1987.

Levine, H.G. The discovery of addiction: Changing concepts of habitual

drunkenness in America. J Stud Alcohol 39: 143-174, 1978.

Maisto, S.A., and Schefft, B.K. The constructs of craving for alcohol and loss of

control drinking: Help or hindrance to research. Addict Behav 2:207-217,

1977.

Mello, N.K. A semantic aspect of alcoholism. In: Cappell, H.D. and LeBlanc,

A.E., eds. Biologic and Behavioural Approaches to Drug Dependence.

Toronto: Addiction Research Foundation of Ontario, 1972, pp. 73-87.

Mendelson, J.H. and Mello, N.K. Commonly abused drugs. In: Petersdorf, R.G.;

Adams, R.D.; Braunwald, E.; Isselbacher, K.J.; Martin, J.B.; and Wilson,

J.D., eds. Harrison’s Principles of Internal Medicine, Chapter 241. New

York: McGraw Hill Book Co., 1982.

Rinaldi, R.C.; Steindler, E.M.; Wilford, B.B.; and Goodwin, D. Clarification and

Standardization of Substance Abuse Terminology. J Amer Med Assoc

259(4):555-557, 1988.

Skinner, B.F. Verbal Behavior. New York: Appleton-Century-Crofts, 1957.

369
Spealman, R.D. Behavior maintained by termination of a schedule of selfadministered cocaine. Science 204:1231-1233, 1979.

Vuchinich, R.D., and Tucker, J.A. Contributions from behavioral theories of

choice to an analysis of alcohol abuse. J Abnorm Psych 97:181-195, 1988.

AUTHOR

Joseph V. Brady, Ph.D.

Professor of Behavioral Biology and Neuroscience

The Johns Hopkins University

School of Medicine

Baltimore, Maryland 21205

370
CHAPTER 18

Conference Summary and Perspectives on Human

Drug Abuse Liability Testing

November 5-6, 1988 - Scanticon Conference Center - Princeton, NJ

Mary Jeanne Kreek, M.D.

This two day conference, “Testing for Abuse Liability of Drugs in

Humans,” the culmination of an effort initiated by the Committee on

Problems of Drug Dependence (CPDD), was planned, developed and

brought to fruition by the enlightened, devoted, diligent and very talented

efforts of Dr. Marian W. Fischman and Dr. Nancy Mello, current CoChairmen of the Human Testing Committee. This conference was

appropriately co-sponsored by three United States Federal Agencies, the

Drug Enforcement Agency (DEA), the Food and Drug Administration

(FDA) and The National Institute on Drug Abuse (NIDA), all recognizing

the need for further activity in this area of abuse liability assessment.

This meeting in part also reflected the earlier thoughtful contributions of

the CPDD Human Testing Committee from the time that it was formed

around five years ago and especially the efforts of its earlier Chairman,

Dr. Charles O’Brien, and earlier Co-Chairman, Dr. Loretta Finnegan.

The efforts of this relatively new Human Testing Committee were fully

supported by my predecessor, Dr. Theodore Cicero, who was Chairman

of the Executive Committee (now renamed the Board of Directors) of the

CPDD, then by myself during my two, one-year terms as Chairman of the

Executive Committee and Chairman of the, by then renamed, Board of

Directors of the CPDD and especially during the current two, one-year

terms of Dr. William Dewey, as Chairman of the Board of Directors of

the Committee on Problems of Drug Dependence.

For many years, CPDD has sponsored and supported, in part, an active

and highly respected pre-clinical program in abuse liability testing of

new drugs under development, new chemicals which may be developed

into new drugs, as well as sometimes already well-known compounds or

approved drugs with newly suspected or recognized abuse liability

potential. For many years this program was focused on testing of opiate

371
drugs and their congeners. In the last few years, an additional active

program of testing of drugs in the stimulant and depressant classes as well

as other related areas has been developed. As part of this program, many

new testing procedures have been developed, others modified and all

tests validated for use in abuse liability testing. Many different university

as well as federal laboratories have participated in these efforts.

In recent years, it has become apparent to CPDD that abuse liability

testing of new drugs in humans which was already being carried out, but

to a limited extent only, in several governmental and academic laboratories,

is an extremely important endeavor, one for which many new techniques

have been developed recently, or are being developed and for which old

techniques have been further refined in recent years. It was also recognized

by CPDD that abuse liability testing in humans is an effort which logically

should be nurtured by CPDD and coordinated under the broader Drug

Testing Program which has up to this time carried out both chemical and

in vitro laboratory procedures as part of its effort, in addition to the very

well developed multi-center Animal Testing Program.

Therefore, the Clinical Testing Committee of CPDD was formed and

given the mandate to determine what role CPDD could and should play

in this area of urgent need. It was soon recognized that, in the tradition

of CPDD, coordination of a scientific meeting designed to bring together

both experts in this area and those in potential need for use of the techniques

of abuse liability testing in humans, including appropriate persons from

academic, governmental and corporate sectors, was needed. The Board

of Directors of CPDD agreed that holding such a conference was a high

priority need. The result has been this meeting.

During the two days of this conference, superb presentations were made

by speakers from the United States and from abroad. The meeting was

very informative throughout, both in the state-of-the-art scientific

presentations providing specific information about human testing

procedures, and also the didactic lectures on current mandatory procedures

and desirable future procedures with respect to regulatory issues which

must be addressed with respect to drug abuse liability testing in humans.

The conference also included many lively discussions on public policy

issues, federal and corporate perspectives on this topic and the ethics of

human research in this challenging area of drug abuse liability testing.

Many of these presentations and discussions are to be included in the

forthcoming NIDA monograph resulting from this conference.

However, in summarizing this conference, it is clear that certain very

important questions remain to be answered. Also the future role that

372
CPDD should play in this effort of abuse liability testing in humans

remains to be defined. Some of the more difficult, yet pressing questions

to be answered include the following:

(1) Which drugs, or classes of drugs, should be evaluated

for abuse liability?

- Drugs related chemically or by pharmacodynamic actions

to drugs known to have an abuse potential or which are

already abused or used non-medically?

- All drugs in the psychotropic drug classes?

- All drugs known to affect learning and memory?

- All drugs known to have some direct effects, either a

primary effect or a side effect on the central nervous system?

- All drugs known to have a primary or secondary direct or

indirect effect on the central nervous system?

(2) Who should make the decision as to whether a specific

drug or a class of drugs should undergo abuse liability

testing in humans?

- The Federal Government (FDA, DEA, other agencies)?

- The corporate sector (a single company developing the

drug; a coalition of companies within an umbrella

organization, e.g. the Pharmaceutical Manufacturers

Association)?

- The academic sector?

- Consumer groups or other groups of lay persons?

(3) How is the decision with respect to whether or not any

given drug or class of drugs is to be tested to be reached?

- Is a decision to be made to determine whether it is desirable,

essential, or in fact mandatory that a specific drug be tested?

- What group or groups should confer in the decision to

suggest or demand that a specific drug undergo such abuse

liability testing in humans and also decide how and where

such testing should be performed and which tests should

be performed?

- What kind of expertise is needed to reach a decision that

balances on one hand what is desirable, essential, or

mandatory, with the recognition of limitations of existing

373
resources for such abuse liability testing in humans,

including limitations of funds and skilled staff to expand

existing resources or to develop new ones?

- What group or groups should resolve the issues of relative

cost compared with the relative benefit of such abuse

liability testing in humans for a specific agent?

(4) When in the course of new drug development should

such abuse liability testing in humans be performed?

- As part of Phase I, that is, the first introduction of the drug

into humans?

- As part of Phase II, the first use of drugs for the target

condition in patients with the disorder under study?

- During Phase III, when wide-scale clinical trials of the

drug are being carried out in target populations?

- During Phase IV, after large scale clinical trials have been

completed and frequently a New Drug Application has

been approved, as part of post-marketing surveillance?

- After identification of actual abuse or non-medical use of

the agent has been made by epidemiological or postmarketing surveillance studies?

(5) What kinds of specific tests for drug abuse liability

assessment in humans should be performed and by

whom?

- Should drug discrimination testing be performed?

- Should testing for reinforcement properties of the drug be

performed?

- Should other related or unrelated indices which may

indicate abuse liability potential, such as testing of the

effects of the drug on neuroendocrine or on neurotransmitter

systems, be performed?

- By what means will sites be identified and recognized,

within the academic, governmental and commercial

sectors, where validated testing procedures are ongoing

and where clinical research or evaluation workers skilled

in carrying out such procedures are available, or

alternatively, where testing procedures developed

elsewhere could be set up and validated and staff could be

trained for carrying out such procedures?

374
(6) Who should be tested, that is what kinds of volunteer

subjects should undergo the experimental testing for

abuse liability of drugs?

- Any normal volunteer subject?

- Volunteer subjects with a history of substance abuse or

addiction of any kind?

- Volunteer subjects with a history of substance abuse or

addiction involving compounds similar to the drug to be

studied?

- Volunteer patient subjects with the condition for which

the drug is to be targeted in appropriate therapeutics?

(7) By what mechanisms can ongoing surveillance for

appropriate use of therapeutic agents, as contrasted with

inappropriate or non-medical use of such agents, or even

illicit trafficking, misuse, abuse, and possibly addiction

to such agents, be identified, both before and following

any FDA New Drug Approval, given the constraints of

confidentiality and the complexities of the health care

system which currently exist in a country like the United

States?

These are some of the more important issues raised during the conference,

some of which were partially addressed during the conference and its

open discussions, though none were fully answered. Many of these

questions as well as other related issues are crucial for the further

development and application of procedures for abuse liability testing of

drugs in humans.

Finally, the question of what should be the continuing role of the Committee

on Problems of Drug Dependence, in view of its very long 60 year history

of scientific inquiry and communications in areas related to drug abuse

and dependence liability as well as its almost equally long history of

preclinical abuse liability testing. Certainly as evidenced by this

conference, CPDD has ample expertise within its members and its

colleagues to reach out to both the scientific community and the policy

making community to address issues related to this topic. CPDD also has

the enthusiasm about the topic and insights into the ramifications of such

testing as well as a commitment to the concept of need for further abuse

liability testing in humans at this time. However, decisions still will have

to be made as to what is the most appropriate, acceptable and feasible role

of the Committee on Problems of Drug Dependence in testing for abuse

liability in humans in the future.

375
All of us who are members of CPDD as well as others who attended and

hopefully benefitted from this meeting, wish to express our special

gratitude to Drs. Fischman and Mello for their tireless efforts in the

development and presentation of this conference. All of us from CPDD

would also like to thank our colleagues in the federal agencies which cosponsored this meeting, DEA, FDA and NIDA for their help and support.

Finally, we would like to thank all of those who attended and actively

participated in this conference, from the academic, corporate and public

policy sectors.

AUTHOR

Mary Jeanne Kreek, M.D.

Associate Professor and Physician

Rockefeller University

1230 York Avenue

New York, New York 10021

376
Index

ACTH and alcohol levels 81, 313-317

Addiction liability see Drug abuse

liability

Addiction Research Center (ARC) 17,

57, 307, 348, 357

methods for assessment of drug

abuse potential 53-57, 101

methods for assessment of

subjective effects of drugs 53-

55

Single Dose Questionnaire 58

Addiction Research Center Inventory

(ARCI) 176, 307

Benzedrine Group Scale (BG)

212

development of 58, 76-81, 124

Lysergic Acid Diethylamide

(LSD) scale 12, 78, 82, 84, 127

Morphine-Benzedrine Group

(MBG) 12, 60, 77, 79, 81, 84,

88, 124-126, 212

benzodiazepines and 134

Pentobarbital Chlorpromazine

Alcohol Group (PCAG) 78,

134,212

sedative drugs and 125

stimulants and 214

Administrative Procedure Act 23

Advisory Committee on Drug

Addiction of the National Research

Council (1929) 2

Alcohol see also Ethanol

euphoria and 52, 314-315

historical view of subjective

effects of 43-44

reinforcing properties of 198-202

behavioral correlates of 3 11-316

neuroendocrine correlates of 311-

316

neurophysiologic correlates of

311-316

self-administration, clinical

studies of 147-159

marijuana and 153, 157-159

polydrug abuse and 153, 159-

162

tobacco smoking and 161

Alcohol interactions with

amitriptyline 298-299

benzodiazepine 290, 296-297

fluoxetine 299

psychotropic drugs 287

tobacco 161

zimelidine 298-299

Alcohol intoxication

ACTH and 315-316

anticipation of 163-166

cortisol and 315-316

EEG activity and 315-316

family history and 328-329

Neuroendocrine,

neurophysiologic and

behavioral correlates 311-317

recall of 163,316

subjective reactions to 321-322

tobacco smoking and 161

topographic mapping of EEG

alpha and 317-331

Alprazolam

regulatory control in Sweden 268

U.S. population experience with

258

Amitriptyline interactions with ethanol

298-299

Amphetamines

abuse of 61-62

benzphetamine, reinforcing

properties of 178-181

d-amphetamine

physiologic effects of 173

reinforcing properties of 174

stimulus properties of drug

discrimination 115-117

subjective effects of 113

euphoria and 57

historical view of

addiction to 55

subjective effects of 49

iatrogenic dependence on 3

Anesthetic, local

lidocaine 223-224

procaine 2, 223-224

377
Index

Animal models of drug abuse liability

9, 12, 27

legislation and 7-8

CPDD supported studies of 37 1

drug discrimination methods in

102

opioids and 114

non-opioid drugs and 115

drug self-administration methods

147

local anesthetics 222

similarity to human drug

preference 172, 177, 211-

213

validation of 172

FDA assumptions about 9-14

limitations of 14

psychoactive drugs and 13- 14

Anorectics

fenfluramine 88, 116

phenylpropanolamine 116- 117,

178

Anti-Drug Abuse Act (1986) 38

Anti-Drug Abuse Act (1988) 1

Antidepressants

amitriptyline 298

desipramine 224-225

fluoxetine 299, 301

methadone, abuse and 235-236

zimelidine 298-301

Antihistamines

cimetidine 294

tripelennamine 14, 234-235, 238

Anxiety

5-HT3 antagonists and 301

benzodiazepines and 191

diazepam and 192- 193

drug reinforcement and 189-191

measures of 189- 19 1

Anxiolytics see also Benzodiazepines

buspirone 11, 88, 136

methods to assess abuse liability

of 123-143

ARC see Addiction Research Center

ARCI see Addiction Research Center

Inventory

378

Barbiturates

abuse of 62-63

methohexital 268

pentobarbital 11, 125-126

phenobarbital 63, 126, 268

historical view of addiction to 55

preference for 238

secobarbital 125-126

BEAM see Topographic mapping of

EEG alpha activity

Behavioral pharmacology, advances in

60

Benzedrine Group Scale (BG) see

Addiction Research Center Inventory

Benzodiazepines 15,258 see also

specific drug listings

abuse liability of 135, 186-187

demonstrated in case reports

232

general population’s

experience with 257-258

types of abuse 349-350

age distribution of users 291

alcohol use and 290

alprazolam 258, 268

anxiety and 191

chlordiazepoxide 125,258, 268

clonazepam 268

clorazepate 268

desmethyldiazepam 297

diazepam 11, 15-16, 116-117,

125-126, 174, 187-188, 192-

198, 202-205, 238, 258-261,

268

ethanol interactions and 296-297

flunitrazepam 268

flurazepam 187

iatrogenic dependence on 4

lorazepam 126, 187, 268

medical emergencies and 258-261

midazolam 11, 268

nitrazepam 268

oxazepam 16, 126, 268

physical dependence and 233

polydrug abuse and 289-290

prazepam 125
Index

preference for 238

prescriptions for 29

forgeries of in Sweden 277

reinforcing properties of 186-187

temazepam 258

triazolam 11, 126, 258, 268

Benzphetamine, reinforcing properties

of 178-181

Chlorpromazine, subject ratings of 125

Cimetidine 294

Citalopram for alcoholism treatment

300-301

BG scale see Addiction Research

Center Inventory

Buprenorphine

abuse potential of 65-66

comparisons with opiate agonists

64-65

Clinical studies see also Ethics in

clinical research

abuse liability of new drugs 17

advantages of inpatient studies

148

heroin self-administration,

suppression and 148

regulatory control of 64

stimulus properties of 110, 112,

114

tobacco smoking and 161

Buspirone

clinical studies and 11

subject ratings of 136

subjective effects data on 88

Butorphanol 11-12, 88

stimulus properties of 110, 112,

114

Caffeine

patterns of use and abuse 88

reinforcing effects of 178

subjective effects of 88

stimulus properties of drug

discrimination studies of 115-

116

Case reports

assessment of drug abuse liability

and 231 -240

limitations of 232-233

phase 2 and phase 3 testing and

232-233

phase 4 testing and 232-233

Chloral hydrate, regulatory control in

Sweden 268

Chlordiazepoxide

regulatory control in Sweden 268

behavioral pharmacology of drug

abuse 148

buspirone 11, 136

DHHS research guidelines for

343

drug choice procedures 171-205

drug discrimination methods and

101-121

drug interactions and 149, 287-

302

epidemiological data vs. 247

FDA regulations and 8-9, 14-18

importance of to CPDD 372

issues in 341-354

legislation and 8

measurement of subjective and

physiologic effects 73-89

New Drug Application

requirements 17

neuroendocrine, neurophysiologic

and behavioral correlates 311-

317

new drug development 374

NMR spectroscopy 331-332

pharmacotherapy evaluation 148

predictive validity of abuse

liability 9, 14-18. 124, 125

reasons for 8, 14-15, 17, 373

self-administration procedures in

147-166

stimulants and 211-227

topographic mapping of EEG

alpha activity 317-331

Clomethiazole, regulatory control in

Sweden 268

Clonazepam, regulatory control in

subject ratings of 125 Sweden 268

379
Index

Clonidine, scheduling issues and 347

Clorazepate, regulatory control in

Sweden 268

Cocaine

abuse and relapse 348

abuse liability 5, 11

acute tolerance and 221-222

compared to procaine 2

crack 5, 257

d-amphetamine, similarity to 214

epidemiologic studies of abuse

242-263

health consequences of use 243-

247,253

heart-rate, effects on 214-221

historical view of

addiction 55

subjective effects of 47-48, 60

medical emergency and 256

self-administration 217-221, 255-

257

self-reports of dependence on

245-246

single dose studies of 213-216

withdrawal symptoms, reported

by ECA 245

Codeine

abuse liability of 2

procaine and 2

euphoria and 52

Cognitive performance in abuse

liability testing of sedatives 138

Committee on Addictions 1948 56

Committee on Problems of Drug

Dependence (CPDD) 2,371-376

Comparative drug testing

epidemiologic data, description

and analysis of 241-263

interview survey methods and

247

Comprehensive Drug Abuse Prevention

and Control Act see Controlled

Substances Act

Computer data bases available in

Sweden 270-275

Concurrent access schedule 129

380

Consent doctrine see Ethics in clinical

research

Controlled Substance Analogue

Enforcement Act 38

Controlled Substances Act (CSA)

(1970) 7-8, 12-14, 18, 23, 27-29, 31

analogues and 39

closed system of distribution 22

drug control procedures 22-24

of 1970 61, 78

precursors 34

reason for 21

role of research 61

Cortisol, alcohol intoxication and 312-

316

CPDD see Committee on Problems of

Drug Dependence

Crime Control Act (1984) 36

CSA see Controlled Substances Act

Cumulative dose procedure 196

effects on drug preference 198

Cyclazocine 11-12

Cyclopropane, subjective effects 52

DAWN see Drug Abuse Warning

Network

DEA see Drug Enforcement

Administration

Declaration of Helsinki (1964) 342

Demerol see meperidine

Department of Health and Human

Services (DHHS) 21-24

human research guidelines 343

confidentiality 343

informed consent 343

Department of Health, Education and

Welfare (DHEW) 23

Depression, drug abuse and 252-254

Desipramine, cocaine selfadministration and 224-225

Desmethyldiazepam 297

Desomorphine 50-51

DHEW see Department of Health,

Education and Welfare

DHHS see Department of Health and

Human Services

Diagnostic and Statistical Manual of
Index

Mental Disorders, third edition (DSM

III) 68

antisocial personality disorder

250-251

DIS correspondence with 243,

241

major depression 252-254

panic disorder 252-254

Diagnostic Interview Schedule (DIS)

see National Institute of Mental

Health Epidemiologic Catchment

Area (ECA) Program

Diazepam 11, 16

anxiety and 192-193

history of alcohol abuse and 202-

205

interaction with methadone 15, 16

population’s experience with 258-

261

regulatory control in Sweden 268

reinforcing properties of 174,

187-188, 192-198, 202-205

stimulus properties of 116- 117

subject ratings of 125-126, 238

Diethylpropion, reinforcing properties

of 178-181

Dihydromorphinone (Dilaudid) 50-51

euphoria and 52

Dilaudid see dihydromorphinone

DIS see National Institute of Mental

Health Epidemiologic Catchment

Area (ECA) Program

Discriminative stimulus properties of,

psychomotor stimulants 183-186

Drug Abuse, definition of 350-361

FDA regulatory responsibilities X9

vulnerability/risk for 5

withdrawal, avoidance and 66

Drug Abuse Warning Network

(DAWN)

cocaine, within drug comparison

255-257

methaqualone 26

quality of data for comparative

drug testing 261-262

Drug abuse liability 15

anxiolytics and sedative/

hypnotics, history of 62-63

benzodiazepines 135

cocaine and 216

definition of 9, 66, 123, 242, 350-

361

drug potency and 5

drug solubility and 5

environmental factors

contributing to

contextual malleability 193-

198, 307-311, 361

cost 5

peer pressure 5

social milieu and 5

epidemiologic studies in U.S.

241-263

euphoria and 52, 54-66

euphoria and 52, 54-66

MDA 31

MDE31

MDMA 31

N-hydroxy-MDA 3 1

overview 357-368

physical dependence and 51

prediction of 290-292, 359

dysphoria and 162

euphoria and 162

issues affecting 162

polydrug use and 165-166

self-medication and 189-190

subjective effects and 43-49

as predictors of 63-64

subjective effects relation to

101-102

Drug abuse liability assessment 50-63,

73-76, 101

animal studies and FDA 10-11,

13-14

anxiolytics and sedative/

hypnotics and 123-143

appropriate subject populations

for 142, 375

ARCI see Addiction Research

Center Inventory

381
Index

case reports in 231-240

clinical studies and 9, 14-18, 124-

125

clinical subject issues 341-354

comparison to a standard drug

141

concurrent measures of drug

effect and performance 136-

138,141

DEA drug control procedures 21-

40

ethical issues in 362-367

dose-response evaluation 141

drug interactions pharmacokinetic

and pharmacodynamic 287-302

drug preference 16, I97-198, 201

environmental context and 127,

361

epidemiologic data and 241-263

FDA requirements 7-18

goals of 3-4

historical perspectives on 43-68

human subject issues 341-354

importance of 1, 3

legislation based on 7-19, 61

maximizing accuracy of 84-85

measures of subjective and

physiologic effects 73-89, 127,

312-313

methodology for 101, 127, 135-

142

issues in 67, 135, 140-142,

249,361

choosing appropriate methods

for 374-375

drug choice procedures 171-

205

drug discrimination methods

117-121 vs. acute effects

profiles 109-114

emphasis on proactive or

reactive events 358-359

progressive ratio methods

130, 149-153

self-administration 124, 128-

135 147-166

self-report measures 211-227

validity for assessment of 136,

360

narcotics control, factor in 50

NMR and 331-332

physiological measures of 73, 8 1

predictive validity 124—limits of

subjective effects measures 82-

84

progressive ratio schedule 130,

149-153

implications for prevention of

drug abuse 1

psychiatric disorders and 249-255

replication 142

route of drug administration and

5, 18

subjective measures of 73, 124-

127,211

Drug abuse prevention in Sweden 278

280

Drug analogues, legislation to control

38-39

Drug choice procedures 123, 130, 172-

205

Drug combinations, regulatory issues

and 14

Drug Control Amendments 61

of 1965 55, 60

Drug control, underprescribing and 354

Drug craving 17,225

Drug dependence

definition of 350-367

definition of addiction as 56

FDA discussion of 17

methaqualone and 25-26

physical dependence 17, 24, 27,

33-34, 51. 53, 58, 60, 63, 67,

294-295

potential for 359

psychological dependence 17, 27,

33-34

measures of 237

methaqualone 26

self-reported 235

Drug development 1

382
Index

Drug discrimination methods 101-121 authority for 23

animal studies 102, 115-117 basis for 22, 24

clinical studies 103-118 changing scheduling

developments, advantages of 101 classification of drug 23

discrimination performance 105 criteria for 8-9

drug abuse liability assessment effects of 27

and 118-120 in Sweden 267-268

drug choice procedures 123, 130, drug seizures in 1987 21

172-205 emergency drug scheduling

compared to animal models 211- regulations and 36-38

212 abuse potential, definition of

non-opioid clinical studies and 30

115-117 chemical and physical

novel drug assessment and 109- properties of drugs 32

114 control actions 27-28

opioids, clinical studies and 103- current pattern of abuse 32

114 definitions 35

pharmacological specificity 118- drug analogues 38-39

119 drug dependence 33-34

relation to subjective effects immediate precursors 34

indices 105-109 pharmacological effects 31

Drug dose public health risk and 33

assessment of abuse liability and scope, duration and

84-85 significance of drug abuse

FDA and therapeutic dose range 32

16 history of 21-22

form, evaluation of abuse international treaty obligations

potential 14 39-40

pharmacokinetic interaction and methaqualone and 25-26

288 need for scientific data 24-25

response characteristics 15 responsibilities of 21

response evaluation in assessment prototypic abused drugs 30

141 restriction of availability of drugs

single dose paradigm, cocaine 4, 22-40

213-216 Drug half-lives

therapeutic dose range 8, 16-18 diazepam 13

Drug effects, difference from drug use in different species 13

patterns 150 physical dependence and 294-295

Drug Enforcement Administration drug interactions and 295-299

(DEA) 21-40 Drug interactions

budget of 21 alcohol and

drug control procedures 22-24 benzodiazepines 296

effects of control 27-29 psychotropic drugs 287

traditional drug scheduling 12, tobacco 161

29-36 cocaine and desipramine 224-226

definitions of 35 consequent behaviors affected by

383
Index

292

pharmacodynamic 287-302

pharmacokinetic 287-302

potential for in abusing

populations 289-290

treatment approaches and 299-

301

Drug potency, abuse liability and 5

Drug preference

cumulative dose procedure and

198

prediction of abuse potential and

1 6

prior abuse history and 16

subjective effect reports, relation

to 197,201

Drug reinforcement 60

analysis of 148

behavioral correlates of 311-316

drug absorption and distribution

and 293

drug choice procedures and 130,

172-205

drug self-administration and 128-

131

euphoria and 2 13

measures of 128-131

neuroendocrine correlates of 311-

316

neurophysiologic correlates of

311-316

prediction of 148

progressive ratio methods and

130, 149-153

self-reported drug effects and

211-227

Drug self-administration

abuse liability, as predictor of 124

animal models of 86, 147, 212-

213

similarity to human drug

preference 172-173

validation of 172-173

clinical studies of 86, 147-166

alcohol 152, 154-156

cocaine 216-222

384

concurrent marijuana and

alcohol 152, 157, 159

daily dose ingestion

procedures 128-135

heroin 152

marijuana 152, 156-157

models of 147

operant procedures for 149-

162

opioids 152-153

correspondence between subject

ratings and 131-134

correlations with subjective and

physiological effects 172-173

measure of drug reinforcing

effects 128-131

operational definitions of 149-150

operant procedures for study of

150-153

polydrug abuse and 153, 159-162

procedures 147-166

sedatives and 128

Drug solubility, abuse liability and 5

Drug use patterns, different from drug

effects 150

Drug withdrawal 60

5-HT, antagonists and 301

avoidance of 66

cocaine and 245

defining addiction 62

methnqualone 26

opium 46

opioids, expectancy and 233-234

DSM III-R see Diagnostic and

Statistical Manual of Mental

Disorders

ECA see National Institute of Mental

Health Epidemiologic Catchment

Area (ECA) Program

EEG see Electroencephalograph

Electroencephalograph

alpha activity, alcohol effects on

81, 317-318, 327-328

behavioral correlates of 327

family alcoholism history and

321-329
Index

recording procedure 319

topographic mapping of alpha

activity 317-318, 329-330

Epidemiological studies of drug abuse

188, 241-263, 267-281

clinical and administrative data

and 275-277

controlled drugs in Sweden 268

drug abuse liability, defined 242-

255

factors contributing to drug abuse

liability 5

intervention strategies in Sweden

277-279

methodology for 241-242

defined daily dose (DDD) in

Sweden 273-274

drug use data bases available

in Sweden 270-275

prescribed daily dose (PDD)

in Sweden 273,275

problems in Sweden 269-270

random allocation designs

255-261

statistics used in ECA 245

prescription drugs

forgeries in Sweden 277

survey in Sweden 27 1

quality of data obtained in 261-

262

U.S. studies 241-263

Ethanol also see Alcohol 16,294

5-HT, antagonists and 301

Amitriptyline and 298

Benzodiazepines and 296-298

fluoxetine, amitriptyline and 299

zimelidine and 298

Ethics in clinical research 341-346,

362-367

beneficence and 344

boundary problem and 362-363

confidentiality and 352-353

federal guidelines for 343

historical precedents and 362

informed consent issues and 352-

354

consent doctrine and 365-367

prisoner populations and 348

justice and 344-345, 362

morality and 362,364

principles used 343-346

respect for persons and 343

risk/benefit ratio 341, 352, 364-

365

subject selection 346-352

Ethylene anesthetic gas, subjective

effects of 52

Euphoria 56

alcohol and 52, 314-316

amphetamine and 57

belladonna and 47

cocaine and 48

codeine and 52

drug abuse liability and 66, 75

drug reinforcement and 211-212

hashish and 47

heroin and 52, 57

morphine and 54, 57

operant methods to assess 312-

313

opiates and 59

opium and 47

prediction of drug abuse liability

and 63-64, 162-166

reinforcement and 213

topographic mapping and 317-

329

FDA see Food and Drug

Administration

Federal Food, Drug, and Cosmetic Act

(FD&C Act) 7-8, 39

Fenfluramine 88

stimulus properties of 116

Fentanyl 11

analogues of 37

p-fluorofentanyl 7

regulatory control in Sweden 268

Flunitrazepam, regulatory control in

Sweden 268

Fluoxetine

alcoholism treatment and 301

ethanol. interactions with 299

385
Hydromorphone 12

discrimination performance 106,

109

Index

Flurazepam, reinforcing properties of

187

Food and Drug Administration (FDA)

7, 28, 55, 60

clinical studies, use for 17-18

dosage forms 14

drug abuse liability 10

drug combinations 14-15

drug labeling sections 9

regulatory responsibilities

regarding drug abuse 8-9

views on human abuse liability

testing 8

Genetic factors

alcohol abuse risk, and 310-311

drug abuse risk, and 310-311

Grinspoon v. Drug Enforcement

Administration 28

Hallucinogens

historical view of subjective

effects of 48-49

MDA 31, 37

MDE 31

MDMA 7, 13, 27

mescaline 48-49

N-hydroxy-MDA 31

patterns of abuse 82-83

phencyclidine 12, 163, 236-237

Harrison Licensing Act 50, 77

Hashish 47

Heart rate, cocaine and 2 14-22 1

Heroin

epidemiologic studies of abuse of

242-263

euphoria and 52, 57

health consequences of use 243-

247,253

self-administration studies 152,

161

self-reported drug dependence

245-246

tobacco smoking and 16 1

withdrawal symptoms reported by

ECA 245

Hexapropymate, regulatory control in

Sweden 268

regulatory control in Sweden 268

stimulus properties of 104, 110,

112, 114, 119

Iatrogenic addiction/dependence on

amphetamines 3

benzodiazepines 4

cocaine 48

narcotics 349

sedatives 349

IND see Investigational New Drug

Informed consent see Ethics in clinical

research

Inhalants, historical view of subjective

effects of 47

International treaties on drug control 50

Convention on Psychotropic

Substances (1971) 39

Single Convention on Narcotic

Drugs (1961) 39

Investigational New Drug (IND),

regulations and human testing 9

Ketobemidone, regulatory control in

Sweden 268

Lexington group see Addiction

Research Center

Lidocaine

self-report questionnaires and 223

self-administration and 223-224

Loperamide, decision to decontrol 16

Lorazepam

regulatory control in Sweden 268

reinforcing properties of 187

subjective ratings of 126

LSD Scale see Addiction Research

Center Inventory

Lysergic Acid Diethylamide Scale

(LSD) see Addiction Research Center

Inventory

Magnetic resonance imaging (MRI) see

Nuclear magnetic resonance

spectroscopy

Magnetic resonance spectroscopy

(MRS) see Nuclear magnetic

386
Index

resonance spectroscopy

Marijuana

as a predictor of cocaine use 350

alcohol and 157,159

Cannabis Indica 44

addiction to 55

subjective effects of 47

drug discrimination studies 115-

116

epidemiologic studies of abuse of

242-263

hashish, historical view of

subjective effects of 47

health consequences of use 243-

247,253

self-administration and

clinical studies of 156-157

alcohol and 153, 157-159

tobacco and 159-162

self-reported drug dependence

245-246

withdrawal symptoms reported by

ECA 245-246

Mazindol

reinforcing properties of 178

stimulus properties of 116-117

MBG Scale see Addiction Research

Center Inventory

MDA

abuse liability 3 1

analogues of 37

MDE abuse liability 31

MDMA 7, 13, 27

abuse liability 31

Meperidine (Demerol)

abuse of 354

analogues of 37

initial assessment for abuse

liability 51

pethidine, regulatory control in

Sweden 268

Meprobamate

regulatory control in Sweden 268

subject ratings of 126

Mescaline, historical view of subjective

Methadone

addictive liability 54

antidepressant use and 235-236

effects of naloxone on 15

diazepam and 15

polydrug abuse and 236

regulatory control in Sweden 268

tobacco smoking and 161

Methaqualone

abuse of 25-26, 354

regulatory control history of 25-

26

subject ratings of 125-126

withdrawal from 26

Methohexital, regulatory control in

Sweden 268

Methyprylon, regulatory control in

Sweden 268

Midazolam 11

regulatory control in Sweden 268

Morphine

abuse in Sweden 267

abuse liability of 2

effects of 75

euphoria and 54

isolation from opium 47

regulatory control in Sweden 268

Morphine-Benzedrine Group Scale

(MBG) see Addiction Research

Center Inventory

N-hydroxy-MDA, abuse potential of 31

Nalbuphine, stimulus properties of 110

Naloxone

methadone and 15

pentazocine and 14,235

Naltrexone, heroin self-administration

and 148

Narcotics Manufacturing Act (1960) 78

National Academy of Science National

Research Council, the Committee on

Drug Addiction (1929) 50

National Commission for Protection of

Human Subjects of Biomedical and

Behavioral Research (1974) 342

National Institute on Drug Abuse

effects 48-49 (NIDA) 1, 8

387
Index

National Institute of Mental Health

Epidemiologic Catchment Area

(ECA) Program 242

Diagnostic Interview Schedule

(DIS) 242-263

DSM III correspondence with

243

limitations of 243

followup data, one year 249

population tested 243

statistics used 245

New Drug and Antibiotic regulations

and human testing 7-8, 17

New Drug Application 24

Nicotine 14

polacrilex gum 88

stimulus properties of 115

NIDA see National Institute on Drug

Abuse

Nitrazepam, regulatory control in

Sweden 268

Nitrous oxide, subjective effects 47, 52

NMR see Nuclear magnetic resonance

spectroscopy

Nuclear magnetic resonance

spectroscopy 331-332

Nuremberg Code (1946) 342

Opioid drugs also see Opium

analgesics

codeine 3, 52

drug thresholds, measurement

of 51

rationale for CPDD’s program

to develop dependence free

2

antidepressants and 224-225, 235-

236

ARC and 357

desomorphine 50-51

dextromethorphan

dihydromorphinone 50-52

drug discrimination methods and

103-115

euphoria and 59

fentanyl 11, 37, 268

heroin 52, 57, 152, 161, 242-263

Opioid mixed agonist/antagonists

buprenorphine 64-66, 110, 112,

114, 148, 161

butorphanol 11-12, 88, 110, 112,

114

nalbuphine 110

pentazocine 4, 11 - 12, 103, 106,

109-110, 112, 114, 119,235,

268, 354

tobacco smoking and 161

Opium

historical view of

addiction to 55

subjective effects of 46-47

nepenthes 43-44

Oxazepam

onset time 16

subject ratings of 126

regulatory control in Sweden 268

Panic disorder

drug abuse and 252-254

PCP, abuse of 163, 236-237

PCAG Scale see Addiction Research

Center Inventory

Pentazocine 11 - 12 see also T’s and

Blues

abuse of 354

hydromorphone 12, 103, 106,

109-110, 112, 114, 119,268

ketobemidone 268

loperamide 16

meperidine 37, 51, 354

methadone 15, 54, 161, 235, 236,

268

morphine 2, 47, 54, 75, 267-268

naloxone 14-15, 235

naltrexone 148

opium 43-44, 46-47, 55

p-fluorofentanyl 7

physiologic effects of 173

propoxyphene 238

self-administration of 152-153

subjective effects of 60, 173

tobacco smoking and 161

withdrawal, expectancy and 233,

234

388
Index

abuse with antihistamines 4

discriminative stimulus,

properties of 104, 106, 109-

110, 112, 114, 119

naloxone and 14,235

regulatory control in Sweden 268

Pentobarbital 11

subject ratings of 125, 126

Pentobarbital Chlorpromazine Alcohol

Group Scale (PCAG) see Addiction

Research Center Inventory

Pharmacodynamics 287-302

animal models and 7

drug interactions and 290-292

Pharmacokinetics 287-302

animal models and ‘7

drug interactions and 293-296

Pharmacologic equivalence of drugs

federal legislation and 78

methods for assessment of 77-79

Pharmacological efficacy studies 17

Phase 4 Drug Testing, case reports in

231-240

Phencyclidine, abuse of 12, 163, 236-

237

Phenmetrazine

reinforcing properties of 178-181

stimulus properties of 116-117

Phenobarbital

abuse of 63

regulatory control in Sweden 268

subject ratings of 126

Phenoperidine

regulatory control in Sweden 268

Phenylpropanolamine (PPA)

reinforcing properties of 178

stimulus properties of 116-117

Physical dependence see Drug

dependence

Physiologic drug effects

abuse liability assessment by

measurement of 73-89

amphetamines 172

assessment, current methods for

82

historical perspectives 73-76

opiates 172

sedatives 172

Picenadol 88

Piritramide, regulatory control in

Sweden 268

Polydrug abuse

benzodiazepine abuse and 289-

290

confounding effects of 238. 287-

288

implications for abuse liability

assessment 165-166

in benzodiazepine abusers 289-

290

predictions about risk and 307-

308

self-administration studies 153,

159-162

subject selection and 307-308

tobacco smoking and 159-162

POMS see Profile of Mood States

PPA see Phenylpropanolamine

Prazepam, subject ratings of 125

Primary prevention of drug abuse 1

Proactive drug abuse liability 358-359

Procaine 2

self-administration of 223-224

stimulus properties of 223

Profile of Mood States (POMS)

alcohol and 199

sedatives and 134

stimulants and 2 14

use in choice procedures 175

Progressive ratio methods 130, 149-153

Propoxyphene 238

Psychological dependence see Drug

dependence

Psychomotor stimulants, reinforcing

properties 177-186

Psychopharmacology

behavioral 102

history of 47, 55-56

Pyrithyldione, regulatory control in

Sweden 268

Reactive drug dependence potential

358-359

389
Index

Risk benefit ratio 364-365

Risk for drug abuse

behavioral factors in 307-309

biologic factors in 307-308

genetic factors in 310-311

social factors in 308-309

Secobarbital, subject ratings of 125126

Sedative/hypnotics see also Anxiolytics

barbiturates 11-12, 55, 62-63,

125-126, 238, 268

chloral hydrate 268

cyclopropane 52

environmental context of use and

193-198

hexapropymate 268

meprobamate 126,268

methaqualone 25-26, 125-126,

354

methods for assessing abuse

liability of 123-143

validity of abuse liability

assessment methods 136

concurrent methods 136-138

test populations for 139-140

methyprylon 268

nitrous oxide 47, 52

physiologic effects of 172-173

reinforcing effects of 193-198

sales in Sweden 272, 274, 279

subjective effects of 172-173

Self-medication, as explanation for

drug abuse 189-190

Serotonin uptake inhibitors

alcoholism treatment and 300-301

fluoxetine 299, 301

zimelidine 298-301

Single Dose Questionnaire

development of 76-79

drug discrimination 106

first used 58

sedative studies and 126

Stimulants 211-227

amphetamines 3, 12, 49, 55, 57,

61-62, 115-117, 173-174, 178-

181

caffeine 88, 115-116, 178

390

cocaine 2, 5, 11, 47-48, 55, 60,

213-222, 242-263, 348

diethylpropion 178-181

mazindol 116-117, 178

nicotine 14, 88, 115

STRIDE see System to Retrieve

Information from Drug Evidence

Subject populations see also Ethics in

clinical research

appropriate testing 4-5, 118, 288,

346-351

drug abusers 174, 307-308,

348-350

for testing sedative abuse 139-

140, 142

normal volunteers 173-174,

348-350

at risk for drug abuse 66-67

drug scheduling issues and 347

ECA 243-244

ethical considerations and 346-

352

federal guidelines for using 343

human subject issues 8, 14, 16

older subjects 192

polydrug abusers 239

informed consent 348, 352-354,

365-367

polydrug abuse and 307-308, 348

post-addict 17

prior abuse history, drug

preference and 16

prisoner 348

risk for substance abuse and 310-

311

with pre-existing anxiety 189-190

Subjective drug effects 58, 74

abuse liability, relation to 101-

102, 162-166

abuse liability assessment and 73-

89

alcohol intoxication and 321-322

amphetamines 49, 172

assessment of 56-57, 75

ARC 53-54, 57

consistency of findings 89-90
Index

practical applications of 86,

88

theoretical basis for 74, 75

assessment methodology

basic methods for 75, 83,212

drug discrimination and 106-

109

historical view 55-63

instrumental methods for 312-

313, 320

validation of measures 81-84

cyclopropane 52

drug abuse and 76

ethylene anesthetic gas 52

evolution of formal screening for

abuse liability 49-55

FDA discussion of 15-16

historical perspectives 43-68, 73-

76

onset of drug effects 15-16

opioids and 15, 163, 173

polydrug abusers and 239

psychopathology, confounding

effects on 239

relation to drug preference 197,

202

sedatives 172

self-rating scales 57

use to predict abuse liability 63-

64, 82, 84

Sweden, regulatory control of narcotic

and psychotropic drugs 268

Swedish Diagnosis and Therapy Survey

271

Swedish Spontaneous Adverse Drug

Reaction Reporting System 275

System to Retrieve Information from

Drug Evidence (STRIDE) 261

T’s and Blues 14

history of use 234, 235

polydrug abuse and 238

TAC see Phencyclidine

Talwin see Pentazocine

THC see Marijuana

TIC see Phencyclidine

Tilidine 14, 88

Tobacco

drug interactions and 161

historical view of

introduced in Europe 45

subjective effects of 45-46

polydrug use and 159-162

self-administration 159-161

Tolerance

DIS assessed 246

FDA discussion of 17-18

Topographic mapping of EEG alpha

activity 317-331

brain electrical activity mapping

(BEAM)

methods 318-321

statistical issues 329-33 1

during alcohol intoxication 3 17-

331

Triazolam 11

subject ratings of 126

regulatory control in Sweden 268

Tripelennamine and pentazocine see

T’s and Blues

Viqualine as alcoholism treatment 300-

301

Zimelidine

alcoholism treatment and 300-301

interactions with ethanol 298-299

Zolpidem 88

391

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GPO Stock #017-024-01218-1 $4.50 NTIS PB #85-1503651/AS $21.95

52 TESTING DRUGS FOR PHYSICAL DEPENDENCE POTENTIAL AND ABUSE

LIABILITY. Joseph V. Brady, Ph.D.. and Scott E. Lukas, Ph.D., eds.

GPO Stock #017-024-01204-1 $4.25 NTIS PB $85-150373/AS $21.95

53 PHARMACOLOGICAL ADJUNCTS IN SMOKING CESSATION. John Grabowski,

Ph.D., and Sharon M. Hall, Ph.D., eds.

GPO Stock #017-024-01266-1 $3.50 NCADI out of stock

NTIS PB #89-123186/AS $21.95

54 MECHANISMS OF TOLERANCE AND DEPENDENCE. Charles Wm. Sharp,

Ph.D., ed.

GPO out of stock NTIS PB #89-103279/AS 936.95

56 ETIOLOGY OF DRUG ABUSE: IMPLICATIONS FOR PREVENTION. Coryl LaRue

Jones, Ph.D., and Robert J. Battjes, D.S.W., eds.

GPO Stock #017-024-01250-5 $6.50 NTIS PB #89-123160/AS $28.95

57 SELF-REPORT METHODS OF ESTIMATING DRUG USE: MEETING CURRENT

CHALLENGES TO VALIDITY. Beatrice A. Rouse, Ph.D., Nicholas J.

Kozel, M.S., and Louise G. Richards, Ph.D., eds.

GPO Stock #017-024-01246-7 $4.25 NTIS PB #88-248083/AS $21.95

58 PROGRESS IN THE DEVELOPMENT OF COST-EFFECTIVE TREATMENT FOR DRUG

ABUSERS. Rebecca S. Ashery, D.S.W., ed.

GPO Stock #017-024-01247-5 $4.25 NTIS PB #89-125017/AS

59 CURRENT RESEARCH ON THE CONSEQUENCES OF MATERNAL DRUG ABUSE.

Theodore M. Pinkert, M.D.. J.D., ed.

GPO Stock #017-024-01249-1 $2.50 NTIS PB #89-125025/AS

60 PRENATAL DRUG EXPOSURE: KINETICS AND DYNAMICS. C. Nora Chiang,

Ph.D., and Charles C. Lee, Ph.D., eds.

GPO Stock #017-024-01257-2 $3.50 NTIS PB #89-124564/AS

61 COCAINE USE IN AMERICA: EPIDEMIOLOGIC AND CLINICAL PERSPECTIVES.

Nicholas J. Kozel, M.S., and Edgar H. Adams, M.S., eds.

GPO Stock #017-024-01258-1 $5

62 NEUROSCIENCE METHODS IN DRUG ABUSE RESEARCH. Roger M. Brown,

Ph.D., and David P. Friedman. Ph.D., eds.

GPO Stock #017-024-01260-2 $3.50 NTIS PB #89-130660/AS

395
63 PREVENTION RESEARCH: DETERRING DRUG ABUSE AMONG CHILDREN AND

ADOLESCENTS. Catherine S. Bell. M.S., and Robert Battjes.

D.S.W., eds.

GPO Stock #Ol7-024-01263-7 $5.50

64 PHENCYCLIDINE: AN UPDATE. Doris H. Clouet. Ph.D., ed.

GPO Stock #Ol7-024-131281-5 $6.50

65 WOMEN AND DRUGS: A NEW ERA FOR RESEARCH. Barbara A. Ray, Ph.D.,

and Monique C. Braude, Ph.D., eds.

GPO Stock #017-024-01283-1 $3.25 NTIS PB #89-130637/AS

66 GENETIC AND BIOLOGICAL MARKERS IN DRUG ABUSE AND ALCOHOLISM.

Monique C. Braude, Ph.D.. and Helen M. Chao, Ph.D eds.

GPO Stock #017-024-01291-2 $3.50 NCADI out of stock

NTIS PB #89-134423/AS $21.95

68 STRATEGIES FOR RESEARCH ON THE INTERACTIONS OF DRUGS OF ABUSE.

Monioue C. Graude, Ph.D.. and Harold M. Ginzburg, M.D., J.D., M.P.H.

eds.

GPO Stock $017-024-131296-3 $6.50 NTIS PB #89-134936/AS

69 OPIOID PEPTIDES: MEDICINAL CHEMISTRY. Rao S. Rapaka, Ph.D.;

Gene Barnett, Ph.D.; and Richard L. Hawks, Ph.D., eds.

GPO Stock #017-024-1297-1 $11 NTIS PB #83-158422/AS $36.95

70 OPIOID PEPTIDES: MOLECULAR PHARMACOLOGY, BIOSYNTHESIS, AND

ANALYSIS. Rao S. Rapaka, Ph.D., and Richard L. Hawks. Ph.D., eds.

GPO Stock #Ol7-024-1298-0 $12 NTIS PB #89-158430/AS $42.95

71 OPIATE RECEPTOR SUBTYPES AND GRAIN FUNCTION. Roger M. Brown,

Ph.D.; Doris H. Clouet, Ph.D.: and David P. Friedman, Ph.D., eds.

GPO Stock #017-024-01303-O $6 PB #89-151955/AS $28.95

72 RELAPSE AND RECOVERY IN DRUG ABUSE. Frank M Tims, Ph.D., and

Carl G. Leukefeld, D.S.W., eds.

GPO Stock #013-024-01302-1 $6 PB #89-151963/AS $28.35

73 URINE TESTING FOR DRUGS OF ABUSE. Richard L. Hawhs, Ph.D.. and

C. Nora Chiang, Ph.D., eds.

GPO Stock #Ol7-024-1313-7 $3.75 PB #89-151971/AS $21.95

74 NEUROBIOLOGY DF BEHAVIORAL CONTROL IN DRUG ABUSE Stephen I

Szara, M.D., D.Sc., ed.

GPO Stock #Ol7-024-1314-5 $3.75 PB #89-151989/AS $21.95

75 PROGRESS IN OPIOID RESEARCH. PROCEEDINGS OF THE 1986 INTERNATIONAL NARCOTICS RESEARCH CONFERENCE. John W. Holaday, Ph.D.;

Ping-Yee Law, Ph.D.; and Albert Herz, M.D., eds.

GPO Stock #017-024-01315-3 $21

396
76 PROBLEMS OF DRUG DEPENDENCE, 1986. PROCEEDINGS OF THE 48TH

ANNUAL SCIENTIFIC MEETING, THE COMMITTEE ON PROBLEMS OF DRUG

DEPENDENCE, INC. Louis S. Harris, Ph.D., ed.

GPO Stock #017-024-1316-1 $16 NTIS PB #88-208lll/AS $44.95

77 ADOLESCENT DRUG ABUSE: ANALYSES OF TREATMENT RESEARCH.

Elizabeth R. Rahdert, Ph.D., and John Grabowski, Ph.D., eds

GPO Stock #017-024-01348-O $4 NTIS PB #89-125488/AS

78 THE ROLE OF NEUROPLASTICITY IN THE RESPONSE TO DRUGS

David P. Friedman. Ph.D., and Doris H. Clouet, Ph.D., eds

GPO Stock #017-O24-131330-7 $6

79 STRUCTURE-ACTIVITY RELATIONSHIPS OF THE CANNABINOIDS

Rao S. Rapaka, Ph.D., and Alexandros Makriyannis. Ph.D., eds.

GPO Stock #017-023-01331-5 $6

80 NEEDLE-SHARING AMONG INTRAVENOUS DRUG ABUSERS: NATIONAL AND

INTERNATIONAL PERSPECTIVES. Robert J. Battjes, D.S.W., and Roy W.

Pickens, Ph.D., eds.

GPO Stock #017-024-01345-5 $5.50

81 PROBLEMS OF DRUG DEPENDENCE, 1987. PROCEEDINGS OF THE 49TH

ANNUAL SCIENTIFIC MEETING, THE COMMITTEE ON PROBLEMS OF DRUG

DEPENDENCE, INC. Louis S. Harris, Ph.D., ed.

GPO Stock #017-024-01354-4 $17

82 OPIOIDS IN THE HIPPOCAMPUS. Jacqueline F. McGinty, Ph.D., and

David P. Friedman, Ph.D. eds.

GPO Stock #017-024-01344-7 $4.25

83 HEALTH HAZARDS OF NITRITE INHALANTS. Harry W. Haverkos, M.D. and

John A. Dougherty, Ph.D., eds.

GPO Stock #017-024-01351-O $3.25 NTIS PB #89-125496/AS

84 LEARNING FACTORS IN SUBSTANCE ABUSE. Barbara A. Ray, Ph.D., ed

GPO Stock #017-024-01353-6 NTIS PB #89-125504/AS

85 EPIDEMIOLOGY OF INHALANT ABUSE: AN UPDATE. Raquel A Crider, Ph.D.,

and Beatrice A. Rouse, Ph.D.. eds.

GPO Stock #017-024-01360-9 $5.50 NTIS PB #89-123178/AS

86 COMPULSORY TREATMENT OF DRUG ABUSE: RESEARCH AND CLINICAL

PRACTICE. Carl G. Leukefeld. D.S.W., and Frank M. Tims, Ph.D., eds

GPO Stock #017-024-01352-8 $7.50 NTIS PB #89-151977/AS 328.95

87 OPIOID PEPTIDES: AN UPDATE. Rao S. Rapaka, Ph.D., and Bhola N.

Dhawan, M.D., eds.

GPO Stock #017-024-01366-8 $7

88 MECHANISMS OF COCAINE ABUSE AND TOXICITY. Doris H. Clouet, Ph.D.,

Khursheed Ashar, Ph.D., Roger M. Brown, Ph.D., eds.

GPO Stock #017-024-01359-5 $11 NTIS PB #89-125512/AS

397
89 BIOLOGICAL VULNERABILITY TO DRUG ABUSE. Roy W. Pickens. Ph.D.,

and Dace S. Svikis, B.A.. eds.

GPO Stock #017-022-01054-2 $5 NTIS PB #89-125520/AS

90 PROBLEMS OF DRUG CEPENDENCE. 1988. PROCEEDINGS OF THE 5OTH ANNUAL

SCIENTIFIC MEETING. THE COMMITTEE ON PROBLEMS OF DRUG DEPENDENCE.

INC., Louis S. Harris, Ph.D.. ed.

GPO Stock #017-024-01362-5 $17

31 DRUGS IN THE WORKPLACE: RESEARCH AND EVALUATION DATA

92 TESTING FOR ABUSE LIABILITY OF DRUGS IN HUMANS. Marian W.

Fishman, Ph.D., and Nancy K. Mello. Ph.D., eds.

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DHHS Publication No. (ADM) 89-1613

Alcohol, Drug Abuse, and Mental Health Administration

Printed 1989