-
STATISTICS IN DRUG RESEARCH
METHODOLOGIES AND RECENT DEVELOPMENTS
SHEIN-CHUNG CHOW Statplus, Inc.
Yardley, Pennsylvania and Temple University
Philadelphia, Pennsylvania
JUN SHAO University of Wisconsin-Madison
Madison, Wisconsin
Copyright 2002 by Marcel Dekker, Inc. All Rights Reserved.
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ISBN: 0-8247-0763-X
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Copyright 2002 by Marcel Dekker, Inc. All Rights Reserved.
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Series Introduction
The primary objectives of the Biostatistics series are to
provide useful ref-erence books for researchers and scientists in
academia, industry, and gov-ernment, and to offer textbooks for
undergraduate and/or graduate coursesin the area of biostatistics.
This book series will provide comprehensiveand unified
presentations of statistical designs and analyses of
importantapplications in biostatistics, such as those in
biopharmaceuticals. A well-balanced summary will be given of
current and recently developed statisticalmethods and
interpretations for both statisticians and
researchers/scientistswith minimal statistical knowledge who are
engaged in applied biostatis-tics. The series is committed to
providing easy-to-understand state-of-the-art references and
textbooks. In each volume, statistical concepts andmethodologies
will be illustrated through real examples.
Pharmaceutical research and development are lengthy and
expensiveprocesses, which involve discovery, formulation,
laboratory work, animalstudies, clinical studies, and regulatory
submission. Research and develop-ment are necessary to provide
substantial evidence regarding the efficacyand safety of a
pharmaceutical entity under investigation prior to regula-tory
approval. In addition, they provide assurance that the
pharmaceuticalentity will possess good characteristics, such as
identity, strength, quality,purity, and stability after regulatory
approval. Statistics plays an importantrole in pharmaceutical
research and development not only to provide a validand fair
assessment of the pharmaceuticals under investigation prior to
reg-ulatory approval, but also to ensure that the pharmaceutical
entities possessgood characteristics with desired accuracy and
reliability. This volume cov-ers several important topics in
pharmaceutical research and development,such as pharmaceutical
validation, including assay and process validation;dissolution
testing and profile comparison; stability analysis;
bioavailabilityand bioequivalence, including the assessment of in
vivo population and indi-vidual bioequivalence and in vitro
bioequivalence testing; and key statisticalprinciples in clinical
development, including randomization, blinding, sub-stantial
evidence, bridging studies, therapeutic
equivalence/noninferioritytrials, analysis of incomplete data,
meta-analysis, quality of life, and med-
Copyright 2002 by Marcel Dekker, Inc. All Rights Reserved.
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iv Series Introduction
ical imaging. This volume provides a challenge to
biostatisticians, phar-maceutical scientists, and regulatory agents
regarding statistical method-ologies and recent developments in
pharmaceutical research, especially forthose issues that remain
unsolved.
Shein-Chung Chow
Copyright 2002 by Marcel Dekker, Inc. All Rights Reserved.
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Biostatistics: A Series of References and Textbooks
Series EditorShein-Chung Chow
President, U.S. OperationsStatPlus, Inc.
Yardley, PennsylvaniaAdjunct ProfessorTemple University
Philadelphia, Pennsylvania
1. Design and Analysis of Animal Studies in Pharmaceutical
Devel-opment, edited by Shein-Chung Chow and Jen-pei Liu
2. Basic Statistics and Pharmaceutical Statistical Applications,
James E.De Muth
3. Design and Analysis of Bioavailability and Bioequivalence
Studies,Second Edition, Revised and Expanded, Shein-Chung Chow
andJen-pei Liu
4. Meta-Analysis in Medicine and Health Policy, edited by Dalene
K.Stangl and Donald A. Berry
5. Generalized Linear Models: A Bayesian Perspective, edited by
DipakK. Dey, Sujit K. Ghosh, and Bani K. Mallick
6. Difference Equations with Public Health Applications, Lemuel
A. Moy6and Asha Seth Kapadia
7. Medical Biostatistics, Abhaya Indrayan and Sanjeev B.
Sarmukaddam8. Statistical Methods for Clinical Trials, Mark X.
Norleans9. Causal Analysis in Biomedicine and Epidemiology: Based
on Minimal
Sufficient Causation, Mikel Aickin10. Statistics in Drug
Research: Methodologies and Recent
Developments, Shein-Chung Chow and Jun Shao
ADDITIONAL VOLUMES IN PREPARATION
Copyright 2002 by Marcel Dekker, Inc. All Rights Reserved.
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Preface
Pharmaceutical research and development is a lengthy process
involvingdrug discovery, laboratory development, animal studies,
clinical develop-ment, regulatory registration, and postmarketing
surveillance. To ensurethe efficacy, safety, and good
characteristics of pharmaceutical products,regulatory agencies have
developed guidances and guidelines for good phar-maceutical
practices to assist the sponsors and researchers in drug
researchand development. Even after a pharmaceutical product is
approved, it mustbe tested for its identity, strength, quality,
purity, and reproducibility be-fore it can be released for use.
This book provides not only a comprehensiveand unified presentation
of designs and analyses utilized at different stagesof
pharmaceutical research and development, but also a well-balanced
sum-mary of current regulatory requirements, methodology for design
and anal-ysis in pharmaceutical science, and recent developments in
the area of drugresearch and development.
This book is a useful reference for pharmaceutical scientists
and bio-statisticians in the pharmaceutical industry, regulatory
agencies, andacademia, and other scientists who are in the related
fields of pharma-ceutical development and health. The primary focus
of this book is on bio-pharmaceutical statistical applications that
commonly occur during variousstages of pharmaceutical research and
development. This book providesclear, illustrated explanations of
how statistical design and methodologycan be used for the
demonstration of quality, safety, and efficacy in phar-maceutical
research and development.
The book contains 12 chapters, which cover various important
topics inpharmaceutical research and development, such as
pharmaceutical valida-tions including assay and process validation,
dissolution testing, stabilityanalysis, bioavailability and
bioequivalence, randomization and blinding,substantial evidence in
clinical development, therapeutic equivalence/non-inferiority
trials, analysis of incomplete data, meta-analysis, quality of
life,and medical imaging. Each chapter is designed to be
self-explanatory forreaders who may not be familiar with the
subject matter. Each chapter
Copyright 2002 by Marcel Dekker, Inc. All Rights Reserved.
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vi Preface
provides a brief history or background, regulatory requirements
(if any),statistical design and methods for data analysis, recent
development, andrelated references.
From Marcel Dekker, Inc., we thank Acquisitions Editor Maria
Allegra,for providing us with the opportunity to work on this
project, and Pro-duction Editor Theresa Stockton for her
outstanding efforts in preparingthis book for publication. We are
deeply indebted to StatPlus, Inc. andthe University of Wisconsin
for their support. We would like to expressour gratitude to Mrs.
JoAnne Pinto of StatPlus, Inc. for her administrativeassistance,
and Mr. Yonghee Lee and Hansheng Wang of the University ofWisconsin
for their considerable assistance in most of the numerical
workduring the preparation of this book.
Finally, we are fully responsible for any errors remaining in
this book.The views expressed are those of the authors and are not
necessarily thoseof their respective company and university. Any
comments and suggestionsthat you may have are very much appreciated
for the preparation of futureeditions of this book.
Shein-Chung ChowJun Shao
Copyright 2002 by Marcel Dekker, Inc. All Rights Reserved.
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Contents
Series Introduction
Preface
Chapter 1. Introduction1.1 Process of Drug Develop
1.1.1 Drug Discover1.1.2 Formulation 1.1.3 Laboratory
Developme1.1.4 Animal Studies1.1.5 Clinical Developme1.1.6
Regulatory Registratio
1.2 Regulatory Requiremen1.2.1 Regulatory Mileston1.2.2
International Conference on Harmonizatio1.2.3 U.S. Regulation1.2.4
Institutional Review Board (I1.2.5 investigational New Drug
Application (IN1.2.6 New Drug Application (N1.2.7 Advisory
Committ
1.3 Good Pharmaceutical Practic
1.4
1.3.11.3.21.3.31.3.4Good Statistics Practice
Good Laboratory Practice (GGood Clinical Practice (Current Good
Manufacturing Practice (cGMP) . FDA Inspection
Copyright 2002 by Marcel Dekker, Inc. All Rights Reserved.
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viii Contents
1.5 Aim1.5.11.5.21.5.31.5.41.5.51.5.6
of the Book and Outline of,Practical IssueThe Aim and Scope of
the BPharmaceutical ValidatiDissolution TesStability Anal
sBioavailability and BioequivaleRandomization and Blindi
1.5.7i.5.81.5.91.5.101.5.111.5.12
Substantial Evidence in Clinical DevelopmeTherapeutic
Equivalence and Noninferiority Analysis of Incomplete Meta-Analysis
Quality of Statistics in Medical Im
Chapter 2.2.12.2
Pharmaceutical ValidationRegulatory RequirementStandard Cu2.2.1
Model Selecti2.2.2 Weight Select
2.3 Calibration and Assay Re2.4 Assay Validatio
2.4.1 Accuracy 2.4.2 Precision 2.4.3 Other Performance
Characteristics
2.5 In-process Controls and Validat2.6 Multiple-Stage
Chapter 3. Dissolution Testing3.1 USP/NF Dissolution 3.2
Probability of Passing the Dissolution 3.3 Dissolution Profile and
Simil3.4 Methods for Assessing Similar
3.4.1 Model-Dependent Approa3.4.2 Model-Independent Appro3.4.3
The f2 Similarity FaChow and Kis Met3.5
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Contents ix
3.6
3.5.1 The Case of Constant Mean Relative Dissolution Rate3.5.2
The Random Effects Model ApproacChow and Shaos Metho
Chapter 4. Stability Analysis4.14.24.3
Statistical Model and DTesting for Batch-to-Batch VariShelf-Life
Estimat4.3.1 Fixed-Batches Appro4.3.2 Random-Batches Approa4.3.3
Discussion
4.4 Two-Phase Shelf-Li4.4.1 A Two-Phase Linear Regression
Mo4.4.2 The Second-Phase Shelf-Lif4.4.3 Discussion
4.5 Discrete Respo4.5.1 The Case of No Batch-to-Batch
Variatio4.5.2 The Case of Random Batch4.5.34.5.44.5.5
4.6 Multiple Components/Ingredients 4.6.1 Shelf-Life Estimation
with Multiple Responses .4.6.2 Shelf-Life Estimation with Multiple
Ingredients
Testing for Batch-to-Batch VariatiAn Example Ordinal Respons
Chapter 5. Bioavailability and Bioequivalence5.15.25.3
5.4
Average, Population, and Individual Bioequivalence Statistical
Design and Statistical Tests Suggested by the 5.3.1 Testing for
5.3.2 Testing for 5.3.3 Testing for
Alternative Designs for 5.4.1 The 2 3 Crossover De5.4.2 The 2 3
Extra-Reference Des5.4.3 Comparisons
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x Contents
5.5 Tests for 5.5.1 The 2 2 Crossover De5.5.2 The 2 4 Crossover
De5.5.3 The 2 3 Desig
5.6 In Vitro Bioequivalen5.6.1 Six Tests in the FDA Guida5.6.2
Nonprofile Anal5.6.3 Profile Anal
5.7 Sample Size Determinati5.7.1 Sample Size for IBE Tes5.7.2
Sample Size for PBE Testi5.7.3 Sample Size for In Vitro
Bioequivalence Testi
Chapter 6. Randomization and Blinding6.1 Randomization Mo
6.1.1 The Population M6.1.2 The Invoked Population M6.1.3 The
Randomization Mo
6.2 Randomization Meth6.2.1 Complete Randomizatio6.2.2
Permuted-Block Randomizatio6.2.3 Adaptive Randomization6.2.4
Discussion
6.3 The Number of Cente6.4 Effect of Mixed-Up Treatment C6.5
Blinding 6.6 The Integrity of Blin6.7 Analysis Under Breached
Blind
Chapter 7.7.17.2
7.3
Substantial Evidence in Clinical DevelopmentReproducibility
ProbabilThe Estimated Power Appro7.2.1 Two Samples with Equal
Varianc7.2.2 Two Samples with Unequal Variance7.2.3 Parallel-Group
DesiThe Confidence Bound Approach
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Contents xi
7.4 The Bayesian Appro7.4.1 Two Samples with Equal Varianc7.4.2
Two Samples with Unequal Varianc7.4.3 Parallel-Group Des
7.5 Applications and Extensi7.5.1 Substantial Evidence with a
Single Tr7.5.2 Sample Size Adjustmen7.5.3 Trials with Different
De7.5.4 Reproducibility Probabilities for k Tri7.5.5 Binary Dat
7.6 Generalizability 7.6.1 The Frequentist Appro7.6.2 The
Bayesian Appro7.6.3 Applications
Chapter 8. Therapeutic Equivalence and Noninferiority8.1
Equivalence/Noninferiority T
8.1.1 Selection of Cont8.1.2 Hypotheses of
Equivalence/Noninferiority 8.1.3 Equivalence Limits and
Noninferiority Margins . 8.1.4 Design Strateg
8.2 Assessing Therapeutic Equival8.2.1 Two Commonly Used
Approaches8.2.2 Clarification of Conf8.2.3 Equivalence between
Proportio
8.3 Active Control T8.3.1 Establishment of Drug Efficacy in tive
Control
Trials 8.3.2 Flemings Appro
8.4 Assessment of Drug Efficacy in Active Control Trial8.4.1
Two-Group Parallel Design with Normally Distributed
8.5
Data and a Common Varianc8.4.2 Two-Group Parallel Design with
Unequal Variances8.4.3 The General CaActive Control Equivalence
T8.5.1 Active Control Equivalence Tri
Copyright 2002 by Marcel Dekker, Inc. All Rights Reserved.
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xii Contents
8.5.2 Active Control and Placebo Control Trial8.6 A Bayesian
Approach for Active Control Tria
8.6.1 Balanced Design with Known Varianc8.6.2 Unbalanced Design
with Unknown Varianc
8.7 Discussion
Chapter 9. Analysis of Incomplete Data9.19.29.39.4
9.5
9.6
Mechanism of Missing VaThe Power of ANOVA TImputation for
Missing Crossover Desi9.4.1 Estimation of Treatment Eff9.4.2
Assessing Individual Bioequivalen9.4.3 Handling Informative
Missingness by TransformationAnalysis of Last Observati9.5.1
Intention-to-Treat Anal9.5.2 Last Observation Carry-Forw9.5.3
Analysis of Last ObservatiAnalysis of Longitudinal 9.6.1 Selection
M9.6.2 The Method of Groupi
Chapter 10. Meta-Analysis10.1 Traditional Approaches
10.1.1 The Approach of p-Va10.1.2 Treatment-by-Study
Interacti10.1.3 The Average Treatment Differen10.1.4 Quantitative
and Qualitative Interaction
10.2 Testing of No Qualitative Interact10.2.1 Intersection-Union
10.2.2 An Aggregated
10.3 Assessing Drug Eff10.3.1 Simultaneous 10.3.2 Two-Step
10.3.3 Evaluation of Equival
10.4 Multiple Prod
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~ontents Xll" 1"
10.4.1 Parallel De10.4.2 Crossover D
10.5 Bioequivalence St10.5.1 Meta-Analysis fer 10.5.2
Meta-Analysis fcr 10.5.3 Meta-Analysis for
10.6 Discussic
Chapter 11. Quality of Life11.1 Definition and Valida
11.1.1 Definitio11.1.2 Validati11.1.3 Validit11.1.4
Reliabilit11.1.5 Reproducibilit
11.2 Responsiveness and Sensiti11.3 QOL Score
11.3.1 Number cf Composite Sc11.3.2 Subscales to Be Grouped in
Each Composite Score 11.3.3 Optimal Weights cf Subsc11.3.4 An
Exam
11.4 Statistical M11.4.1 ~ime Series 11.4.2 Parallel
Questionna
11.5 Statistical 11.5.1 Multiplicit11.5.2 Sample Size
Determinati11.5.3 Calibration with Life 11.5.4 Utility An
Chapter 12. Medical Imaging12.1 Medical Imaging
12.1.1 Contrast A12.1.2 Diagnostic Radicpharmaceutica12.1.3
Regulatory Requireme12.1.4 Statistical An
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xiv Contents
12.2 ROC Analysi12.2.1 The Roe Cu12.2.2 Characteristics of the
ROC 12.2.3 Comparison of ROC Cur
12.3 The Analysis of Blinded-Reader Stud12.3.1 Design of
Blinded-Reader Stud12.3.2 Assessing Interreader Agree
12.4 Diagnostic Acc12.4.1 Diagnostic Accuracy with an Imperfect
Reference
Test 12.4.2 Diagnostic Accuracy without Gold Standard
12.5 Sample
References
Copyright 2002 by Marcel Dekker, Inc. All Rights Reserved.
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Chapter 1
Introduction
In recent years, a series of prescription drugs were pulled from
the mar-ketplace due to safety problems. Table 1.1.1 lists drugs
recalled by theU.S. Food and Drug Administration (PDA) between 1993
and 2000, andtheir reasons for recall. As it can be seen from Table
1.1.1, the mostcommonly seen reasons for recalls were safety
concerns regarding cardiac/cardiovascular problems and liver
toxicity/failure. This has renewed con-cerns that the drug
development and regulatory approval process moves tooquickly. In
the United States, however, drug development is a lengthy andcostly
process. On average, it takes about 12 years to obtain
regulatoryapproval for a new drug. The cost is estimated to be
approximately 300to 450 million U.S. dollars. In many cases (e.g.,
the development of drugproducts for severe or life-threatening
diseases such as cancer and AIDS), ithas been criticized that the
drug development and regulatory process takestoo long for a
promising drug product to benefit patients with severe
orlife-threatening diseases. The lengthy and costly process of drug
develop-ment is necessary, not only to ensure that the drug under
investigation isefficacious and safe before it can be approved for
use in humans, but also toassure that the drug product meets
regulatory requirements for good drugcharacteristics of identity,
strength (or potency), purity, quality, stability,and
reproducibility after the drug is approved.
Drug development is not only used to efficiently identify
promising com-pounds with fewer false negatives/positives, but its
also utilized to scien-tifically evaluate the safety and efficacy
of these compounds with certaindegrees of accuracy and reliability.
To ensure the success of drug devel-opment, most regulatory
agencies, such as the FDA, have issued numer-ous guidelines and/or
guidances to assist the sponsors in fulfilling regu-latory
requirements of safety and efficacy, and good drug
characteristicsof identity, strength, purity, quality, stability,
and reproducibility. The
Copyright 2002 by Marcel Dekker, Inc. All Rights Reserved.
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2 Chapter i. Introduction
sponsors are strongly recommended to comply with the regulations
andguidelines/guidances set forth by the regulatory agencies for
best pharma-ceutical practices. During the drug development
process, practical issuesin design, execution, analysis, report,
and interpretation of studies thatare necessarily conducted for
regulatory submission, review, and approvalare inevitably
encountered. These practical issues may include violationsor
noncompliance of study protocol, invalid study design, misuse or
abuseof statistics for data analysis, misinterpretations of the
study results, andincorrectly addressed questions with wrong
answers. These practical issuesoften result in a misleading
conclusion for the evaluation of the drug underinvestigation.
A brief description of the process of drug development is given
in 1.1.Regulatory requirements for obtaining drug approval is
briefly introducedin 1.2. 1.3 reviews the concepts of good
laboratory practice (GLP), goodclinical practice (GCP), and current
good manufacturing practices (cGMP)for good pharmaceutical
practices. The role of good statistics practice(GSP) in good
pharmaceutical practices is discussed in 1.4. The last sec-tion
provides a description of the aim and scope of this book and an
outlineof a number of practical issues in various stages of the
drug developmentprocess that are studied in the subsequent
.chapters.
Table 1.1.1. Recalled Drugs Between 1993o2000
Drug Name Drug Type Year Reason for RecallPropulsid Heartburn
2000Rezulin Diabetes 2000Raxar Antibiotic 1999Hismanal Allergy
1999Duract Arthritis 1998Posicor Blood pressure 1998Seldane Allergy
1998Redux Diet 1997Pondimin Diet 1997Manoplax Congestive heart
1993
failure
Cardiac problemsLiver toxicityCardiovascular problemsCardiac
problemsLiver failureDangerous drug interactionDangerous drug
interactionPossible heart valve damagePossible heart valve
damageIncreased risk of death
Source: U.S. Food and Drug Administration; compiled from AP wire
reports
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1.1. Process of Drug Development 3
1.1 Process of Drug Development
The ultimate goal of the drug development process is to produce
new drugproducts for marketing. The drug development process,
involving drug dis-covery, formulation, laboratory development,
animal studies for toxicity,clinical development, and regulatory
registration, is a continual process. Itconsists of different
phases of development, including nonclinical develop-merit (e.g.,
drug discovery, formulation, and laboratory development),
pre-clinical development (e.g., animal studies), and clinical
development (e.g.,clinical studies). These phases may occur in
sequential order or be over-lapped during the development process.
To provide a better understandingof the drug development process,
critical stages or phases of drug develop-ment are briefly and
separately outlined below.
1.1.1 Drug Discovery
Drug discovery consists of two phases, namely drug screening and
drug leadoptimization. The purpose of drug screening is to identify
a stable and re-producible compound with fewer false-negative and
false-positive results.At the drug screening phase, the mess
compounds are necessarily screenedto distinguish those that are
active from those that are not. For this pur-pose, a multiple-stage
procedure is usually employed. A compound mustpass all stages to be
active. The commonly encountered problem in drugscreening for
activity is the choice of dose. In practice, the dose is
oftenchosen either too low to show activity or too high to exhibit
a toxic effect.Drug screening for activities could be a general
screening, based on phar-macological activities in animals or in
vitro assays, or a targeted screeningbased on specific activities,
such as that of an enzyme. Pharmacologicalactivity is usually
referred to as the selective biological activity of
chemicalsubstances on living matter. A chemical substance is called
a drug if ithas selective activity with medical value in the
treatment of disease. Leadoptimization is a process of finding a
compound with some advantages overrelated leads based on some
physical and/or chemical properties. To effi-ciently identify a
stable and reproducible compound during the process ofdrug
screening and lead optimization, statistical quality control based
onsome established standards for acceptance and rejection is
critical. The suc-cess rate for identifying a promisir[g active
compound is relatively low. Asa result, there may be only a few
compounds that are identified as promis-ing active compounds. These
identified compounds have to pass the stagesof laboratory
development and animal studies before they can be used inhumans. In
practice, it is estimated that about one in 8 to 10 times
103compounds screened may finally reach the stage of clinical
development forhuman testing.
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4 Chapter 1. Introduction
1.1.2 Formulation
When a new drug is discovered, it is important to develop an
appropri-ate dosage form /or formulation) for the drug so that it
can be deliveredefficiently to the site of action of the body for
the intended disease. It is nec-essary to develop appropriate
formulation with an adequate dose to achieveoptimal therapeutic
effect in patients with the intended disease. The com-monly seen
pharmaceutical dosage forms include tablet, capsule, powder,liquid
suspension, aerosol, cream, gel, solution, inhalation, lotion,
paste,suspension, and suppository. Formulation is a synthesis of a
new chemicalentity, which modifies the structure ,to enhance
biologic activity. At theinitial development of formulation, a
small amount of the drug productunder development/investigation is
usually produced for laboratory testingsuch as solubility and
accelerated stability. The optimization of formula-tions usually
occurs in a scale-up from the laboratory batch to commercialor
production batch, process control, and validation. The purpose of
theoptimization of formulations is to optimize the responses of the
drug de-livery system by identifying critical formulations and/or
process variablestliat can be manipulated or a~e controllable. The
optimization of formu-lation helps in meeting regulatory
requirements for identity, strength /orpotency/, quality, purity,
stability, and reproducibility of the drug product.
1.1.3 Laboratory Development
During the drug development process, laboratory development
usually ap-plies to nonclinical safety studies, such as animal
studies and in vitro as-says studies. For each newly discovered
compound, the FDA requires thatanalytical methods and test
procedures be developed for determining theactive ingredient(s) of
the compound in compliance with USP/NF (UnitedStates Pharmacopedia
and National Formulary) standards for the identity,strength,
quality, purity, stability, and reproducibility of the compound.
Ananalytical method is usually developed based on some instrument,
such ashigh-performance liquid chromatography (HPLC). As a result,
the estab-lishment of the standard curve for calibration of an
instrument is criticalfor the assurance of accuracy and reliability
of the results obtained from theanalytical method or test
procedures. The FDA indicates that an instru-ment must be suitable
for its intended purposes and be capable of producingvalid results
with a certain degree of accuracy and reliability. An
analyticalmethod is usually validated according to some performance
characteristicssuch as accuracy, precision, linearity, range,
specificity, limit of detection,limit of quantitation, and
ruggedness as specified in the USP/NF standards.The instrument used
for the development qf an analytical method or testprocedures must
be calibrated, inspected, ahd checked routinely according
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1.1. Process o[ Drug Development 5
to written procedures for suitability, sensitivity, and
responsiveness.
1.1.4 Animal StudiesIn drug development, because certain
toxicities, such as the impairment offertility, teratology,
mutagenicity, and overdosage, cannot be investigatedethically in
humans, the toxicity of the drug product is usually assessedin
either in vitro assays or animal models. Animal models are often
con-sidered as a surrogate for human testing, under the assumption
that theycan be predictive of the results in humans. Animal studies
involve doseselection, toxicological testing for toxicity and
carcinogenicity, and animalpharmacokinetics. For the selection of
an appropriate dose, dose-response(dose:ranging) studies in animals
are usually conducted to determine effective dose, such as the
median effective dose (EDs0). In addition, druginteraction, such as
potentiation, inhibition, similar joint action, synergism,and
antagonism, are also studied. In general, animal toxicity studies
areintended to alert the clinical investigators of the potential
toxic effects asso-ciated with the investigational drugs so that
those effects may be watchedfor during the clinical investigations.
In most circumstances, acute andsubacute toxicity studies are
typically conducted in rodent and nonrodentmammalian species. It is
necessary to conduct segments I, II, and III repro-ductive toxicity
studies and chronic and carcinogenic studies to provide thecomplete
spectrum of toxicological effects an investigational drug can
elicit.In addition, it is necessary to perform absorption
distribution, metabolism,and excretion (ADME) studies in animals in
order to identify those phar-macokinetic parameters that are
similar to those in humans and to verifythe applicability of the
animal species used in the toxicological tests.
1.1.5 Clinical Development
Clinical development involves phases 1-4 of clinical
investigation. The pri-mary objective of phase 1 is not only to
determine the metabolism andpharmacologic activities of the drug in
humans, the side effects associatedwith increasing doses, and the
early evidence on effectiveness, but also toobtain sufficient
information about the drugs pharmacokinetics and phar-macological
effects to permit the design of well-controlled and
scientificallyvalid phase 2 studies. Phase 2 studies are the first
controlled clinical stud-ies of the drug. The primary objectives of
phase 2 studies are not only tofirst evaluate the effectiveness of
a drug based on clinical endpoints for aparticular indication or
indications in patients with the disease or conditionunder study,
but also to determine the dosing ranges and doses for phase3
studies and the common short-term side effects and risks associated
withthe drug. Phase 3 studies are expanded controlled and
uncontrolled tri-
Copyright 2002 by Marcel Dekker, Inc. All Rights Reserved.
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Chapter 1. Introduction
als. The primary objectives are to (a) gather additional
information aboutthe effectiveness and safety needed to evaluate
the overall benefit-risk re-lationship of the drug, and (b) to
provide an adequate basis for physicianlabeling. Phase 4 studies
are usually conducted to further elucidate theincidence of adverse
reactions and determine the effect of a drug on mor-bidity or
mortality. Phase 4 studies are considered useful
market-orientedcomparison studies against competitor products.
According to the 1988 FDA guideline, the efficacy and safety of
a studydrug can only be established through the conduct of adequate
and well-controlled cl.ipical trials (FDA, 1988). Table 1.1.2 lists
characteristics of adequate and well-controlled study as specified
in 21 CFR 314.126.
Table 1.1.2. Characteristics of an Adequate and Well-Controlled
Study
CriterionObjectivesMethods of analysis
Design
Selection of subjects
Assignment of subjects
Participants of studies
Assessment of responsesAssessment of the effect
CharacteristicsClear statement of investigation purposeSummary
of proposed or actual methods ofanalysisValid comparison with a
control to providea quantitative assess~nent of drug effectAdequate
assurance of the disease orconditions under studyMinimization of
bias and assurance ofcomparability of groupsMinimization of bias on
the part of subjects,observations, and analysisWell defined and
reliableRequirements of appropriate statisticalmethods
1.1.6 Regulatory Registration
.At the end of clinical development, the sponsor is required to
submit all ofthe information collected from the studies conducted
at different phases ofdrug development for regulatory review and
approval. Regulatory reviewis a very intensive process, which
involves reviewers from different disci-plines such as chemistry,
toxicology, clinical pharmacology, medicine, andbiostatistics. The
purpose of this intensive review is to make sure that thereis
substantial evidence to support the safety and efficacy of the drug
prod-uct under investigation. In addition, the r~view assures that
the proposed
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1.2. ~egul~or~ Requirements 7
labeling for the investigational drug is appropriate for the
target patientpopulation with the intended indication. At the stage
of regulatory regis-tration, it is helpful to build up a
communication with the FDA for adviceon deficiencies or concerns
regarding the safety and efficacy of the investi-gational drug. The
FDA may approve the drug product if the sponsor hascommitted to
conduct additional clinical studies to address the
deficienciesand/or concerns/issues raised during the regulatory
review/approval pro-cess. These additional clinical studies are
usually referred to as phase 3Bstudies or pending approval clinical
studies.
1.2 Regulatory Requirements
1.2.1 Regulatory Milestones
A century ago, the pharmaceutical industry in the United States
was es-sentially unregulated. Drug companies could advertise their
products astreatments for any and all diseases. The first effective
legislation regardingdrug products can be traced back to the
Biologics Act of 1902. This wasPrecipated by a tragedy involving
diptheria antitoxin contaminated withtetanus, which resulted in the
death of 12 children and subsequently led tothe passage of the Pure
Food and Drugs Act of 1906. The purpose of thisact was to prevent
misbranding and adulteration of food and drugs and yetthe scope is
rather limited. In 1912, the Sherley Amendment to the actwas passed
to prohibit the labeling of medicines with false and
fraudulentclaims. The concept of testing marketed drugs in human
subjects did notbecome a public issue until the Elixir
Sulfanilamide disaster occurred inthe late 1930s. The disaster was
regarding a liquid formulation of a sulfadrug, which had never been
tested in humans before its marketing. Thisdrug caused more than
i00 deaths and raised the safety concern that ledto the passing of
the Federal Food, Drug, and Cosmetic Act in 1938. Thisact extended
regulatory regulation to cosmetics and therapeutic devices.More
importantly, it requires the pharmaceutical companies to submit
fullreports of investigations regarding the safety of new drugs. In
1962, asignificant Kefauver-Harris Drug Amendment was passed, which
not onlystrengthened the safety requirements for new drugs, but
also establishedan efficacy requirement for new drugs for the first
time. In 1984, Congresspassed the Price Competition and Patent Term
Restoration Act to providean increased patent protection to
compensate for patent life lost duringthe approval process. Based
on this act, the FDA was authorized to ap-prove generic drugs only
based on bioavailability and bioequivalence trialson healthy
subjects.
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Chapter 1. Introduction
1.2.2 International Conference on Harmonization
For the marketing approval of pharmaceutical entities, the
regulatory pro-cess and requirements may vary from country (region)
to country (region).The necessity to standardize these similar and
yet different regulatory re-quirements has been recognized by both
regulatory authorities and thepharmaceutical industry. Hence, the
International Conference on Harmo-nization (ICH), which consists of
the European Community (EC), Japan,and the United States, was
organized to provide an opportunity for impor-tant initiatives to
be developed by regulatory authorities as well as
industryassociations for the promotion of international
harmonization of regulatoryrequirements. The ICH, however, is only
concerned with tripartite har-monization of technical requirements
for the registration of pharmaceuticalproducts among the three
regions of the EC, Japan, and the United States.That is, the
information generated in any of the three areas of the EC,Japan and
the United States would be acceptable to the other two
areas.Basically, the ICH consists of six parties that operate in
these three re-gions, which include the European Commission of the
European Union,the European Federation of Pharmaceutical Industries
Association (EF-PIA), the Japanese Ministry of Health and Welfare
(MHW), the JapanesePharmaceutical Manufacturers Association (JPMA),
the Center for DrugEvaluation and Research (CDER) of FDA, and the
Pharmaceutical Re-search and Manufacturers of America (PhRMA). To
assist sponsors in thedrug development process, the ICH has issued
a number of guidelines anddraft guidances. These guidelines and
guidances are summarized in Table1.2.1.
1.2.3 U.S. Regulations
In this section, for illustration purposes, we focus on the
regulatory processand requirements currently adopted in the United
States. The current regu-lations for conducting studies, regulatory
submission, review, and approvalof results for pharmaceutical
entities (including drugs, biological products,and medical devices
under investigation) in the United States can be foundin the Code
of Federal Regulations (CFR). Table 1.2.2 lists the most rele-vant
regulations with respect to drug development and approval. The
Cen-ter for Drug Evaluation and Research (CDER) of the FDA has
jurisdictionover the administration of regulations and the approval
of pharmaceuticalproducts classified as drugs. These regulations
include investigational newdrug application (IND) and new drug
application (NDA) for new drugs,orphan drugs, and over-the-counter
(OTC) human drugs and abbreviatednew drug application (ANDA) for
generic drugs.
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1.2. Regulatory Requirements 9
Table 1.2.1. ICH Clinical Guidelines and Draft Guidelines
GuidelinesSafety1 S1A: The need for long-term rodent
carcinogenicity studies of
pharmaceuticals2 SIB: Testing for carcinogenicity of
pharmaceuticals3 S1C: Dose selection for carcinogenicity studies of
pharmaceuticals4 S1C(R): Guidance on dose selection for
carcinogenicity studies
pharmaceuticals: Addendum on a limit dose and related notes5
S2A: Specific aspects of regulatory genotoxicity tests for
pharmaceuticals6 S2B: Genotoxicity: A standard battery for
genotoxicity testing of
pharmaceuticals7 SJA: Toxicokinetics: The assessment of systemic
exposure in
toxicity studies8 SJB: Pharmacokinetics: Guideline for repeated
dose tissue
distribution studies9 S4A: Duration of chronic toxicity testing
in animals (rodent and
nonrodent toxicity testing)10 S5A: Detection of toxicity to
reproduction for medicinal products11 S5B: Detection of toxicity to
reproduction for medicinal products:
Addendum on toxicity to male fertility12 $6: Preclinical safety
evaluation of biotechnology -- derived
pharmaceuticalsJoint Safety/Efficacy1 M4: Common technical
document
Efficacy1 E1A: The extent of population exposure to assess
clinical safety
for drugs intended for long-term treatment of
non-life-threatening conditions
2 E2A: Clinical safety data management: Definitions and
standardsfor expedited reporting
3 E2B:Data elements for transmission of individual case report
forms4 E2C: Clinical safety data management: Periodic safety
update
reports for marketed drugs5 EJ: Structure and content of
clinical studies
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10 Chapter 1. Introduction
Table 1.2.1. (Continued)
Efficacy6 E4: Dose-response information to support drug
registration7 E5: Ethnic factors in the acceptability of foreign
clinical data8 E6: Good clinical practice: Consolidated guideline9
ET: Studies in support of special populations: Geriatrics
10 E8: General considerations for clinical trials11 E9:
Statistical principles for clinical trials12 Ell: Clinical
investigation of medicinal products in the
pediatric populationQuality
56789
Q1A:Q1B:Q1C:Q2A:Q2B:Q3A:Q3B:Q3C:
Stability testing of new drug substances and
productsPhotostability testing of new drug substances and
productsStability testing for new dosage formsTest on validation of
analytical proceduresValidation of analytical procedures:
MethodologyImpurities in new drug substancesImpurities in new drug
productsImpurities: Residual solvents
Q5A: Viral safety evaluation of biotechnology products
derivedfrom cell lines of human or animal origin
10 Q5B: Quality of biotechnology products: analysis of
theexpression construct in cells used for production of
r-DNAderived protein products
11 Q5C: Quality of biotechnology products: Stability testing
ofbiotechnological/biological products
12 Q5D: Quality of biotechnology/biological products:
Derivationand characterization of cell substrates used for
productionof biotechnological/biological products
13 Q6A: Specifications: Test procedures and acceptance criteria
fornew drug substances and new drug products:
Chemicalsubstances
14 Q6B: Test procedures and acceptance criteria for
biotechno-logical/biological products
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1.2. Regulatory Requirements 11
Table 1.2.1. (Continued)
Draft GuidelinesSafety1 $7: Safety pharmacology studies for
human pharmaceuticalsEfficacy1 El0: Choice of control group in
clinical trials2 EI2A: Principles for clinical evaluation of new
antihypertensive
drugsQuality1 Q1A(R): Stability testing of new drug substances
and products2 Q3A(R): Impurities in new drug substances3 Q3B(R):
Impurities in new drug products4 QTA: Good manufacturing practice
for active pharmaceutical
ingredients
Table 1.2.2. U.S. Codes of Federal Regulation (CFR) for Clinical
TrialsUsed to Approve Pharmaceutical Entities
CFR Number Regulations21 CFR 5O21 CFR 5621 CFR 312
Subpart E21 CFR 314
Subpart CSubpart H
21 CFR 601
Subpart E21 CFR 31621 CFR 32021 CFR 33021 CFR 81221 CFR 81421
CFR 6021 CFR 20121 CFR 202
Protection of human subjectsInstitutional review boards
(IRB)Investigational new drug application (IND)Treatment INDNew
drug application (NDA)Abbreviated applicationsAccelerated
approvalEstablishment license and product license applications
(ELA and PLA)Accelerated approvalOrphan drugsBioavailability and
bioequivalence requirementsOver-the-counter (OTC) human
drugsInvestigational device exemptions (IDE)Premarket approval of
medical devices (PMA)Patent term restorationLabelingPrescription
drug advertsing
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12 Chapter 1. Introduction
1.2.4 Institutional Review Board (IRB)
Since 1971, the FDA has required that all proposed clinical
studies bereviewed both by the FDA and an institutional review
board (IRB). Theresponsibilities of an IRB are to evaluate the
ethical acceptability of theproposed clinical research and to
examine the scientific validity of the studyto the extent needed to
be confident that the study does not expose itssubjects to an
unreasonable risk. The composition and function of an IRBare
subject to the FDA requirements. Section 56.107 in Part 56 of 21CFR
states that each IRB should have at least five members with
varyingbackgrounds to promote a con~plete review of research
activities commonlyconducted by the institution. Note that in order
to avoid conflict of interestand to provide an unbiased and
objective evaluation of scientific merits,ethical conduct of
clinical trials, and protection of human subjects, theCFR enforces
a very strict requirement for the composition of members ofan IRB.
These strict requirements include (i) no IRB is entirely composedof
one gender, (ii) no IRB may consist entirely of members of one
profession,(iii) each IRB should include at least one member whose
primary concernsare in the scientific area and at least one member
whose primary concernsare in nonscientific area, and (iv) no IRB
should have a member participatein the IRBs initial or continuous
review of any project in which the memberhas a conflicting
interest, except to provide information requested by theIRB.
1.2.5 Investigational New Drug Application (IND)
Before a drug can be studied in humans, its sponsor must submit
an INDto the FDA. Unless notified otherwise, the sponsor may begin
to investi-gate the drug 30 day~ after the FDA has received the
application. TheIND requirements extend throughout the period
during which a drug is un-der study. By the time an IND is filed,
the sponsor should have sufficientinformation about the chemistry,
manufacturing, and controls of the drugsubstance and drug product
to ensure the identity, strength, quality, purity,stability, and
reproducibility of the investigational drug covered by the IND.In
addition, the sponsorshould provide adequate information about
phar-macological studies for absorption, distribution, metabolism,
and excretion(ADME), and acute, subacute, and chronic toxicological
studies and repro-ductive tests in various animal species to
support that the investigationaldrug is reasonably safe to be
evaluated in humans.
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1.3. Good Pharmaceutical Practices 13
1.2.6 New Drug Application (NDA)For the approval of a new drug,
the FDA requires that at least two ad-equate well-controlled
clinical studies be conducted in humans to demon-strate substantial
evidence of the effectiveness and safety of the drug. Sub-stantial
evidence can be obtained through adequate and
well-controlledclinical investigations. Section 314.50 of 21 CFR
specifies the format andcontent of an NDA, which contains the
application form (365H), index,summary, technical sections, samples
and labeling, and case report formsand tabulations. The technical
sections include chemistry, manufactur-ing, and controls (CMC),
nonclinical pharmacology and toxicology, humanpharmacology and
bioavailability, microbiology (for anti-infective drugs),clinical
data, and statistics. As a result, the reviewing disciplines
includechemistry reviewers for the CMC section; pharmacology
reviewers for non-clinical pharmacology and toxicology; medical
reviewers for clinical datasection; and statistical reviewers for
statistical technical section.
1.2.7 Advisory Committee
The FDA has also established advisory committees in designated
drugclasses and subspecialities each consisting of clinical,
pharmacological, andstatistical experts and one consumer advocate
(not employed by the FDA).The responsibilities of the committees
are to review the data presented inthe NDAs and to advise the FDA
as to whether there exists substantialevidence of safety and
effectiveness based on adequate and well-controlledclinical
studies. As a result, the advisory committees address the
followingquestions posted by the FDA followed by an intensive
discussion at the endof the advisory committee meeting:
1. Are there two or more adequate and well-controlled
trials?
2. Have the patient populations been well enough
characteristized?
3. Has the dose-response relationship been sufficiently
characterized?4. Do you recommend the use of the drug for the
indication sought by
the sponsor for the intended patient population?Note that the
FDA usually follows the recommendations made by the advi-sory
committee for marketing approval, though they do not have to
legally.
1.3 Good Pharmaceutical Practices
To ensure the success of drug development in compliance with
regulatoryrequirements for approval, good pharmaceutical practices
have to be imple-
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Chapter 1. Introduction
mented. Good pharmaceutical practices are established standards
to assurethe drug under investigation meets the requirements of the
Federal Food,Drug, and Cosmetic Act related to safety and efficacy
before marketingapproval and drug characteristics of identity,
strength, quality, purity, sta-bility, and reproducibility after
approval. Good pharmaceutical practicesinclude good laboratory
practice (GLP), good clinical practice (GCP), current good
manufacturing practice (cGMP). GLP, GCP, arid cGMP areregulations
governing the conduct of preclinical safety studies and in
vitrostudies, clinical studies, and the conduct of manufacturing
operations, re-spectively. GLP, GCP, and cGMP are briefly described
in the subsequentsections.
1.3.1 Good Laboratory Fractice (GLP)Good laboratory practice
(GLP) for nonclinical laboratory studies is cod-ified in 21 CFR 58.
GLP applies to animal and in vitro studies for safetyassessment.
Similar to cGMP, GLP covers regulations with respect to
re-quirements for organization and personnel, facilities,
equipment, testingfacilities operations, test and control articles,
protocol for and conduct ofa nonclinical laboratory study, records
and reports, and disqualification oftesting facilities. GLP
requires the existence of a quality assurance unit(QAU). The QAUs
responsibilities include that (i) sampling plan, procedure,
acceptance/rejection criteria are properly documented, (ii)
anyidentified deviations from standard operating procedure (SOP) or
protocolare properly corrected and documented, (iii) internal
audits are properlyconducted and documented, and (iv) form 483
notice of observations as theresult of an FDAs inspection are
properly addressed and documented.
1.3.2 Good Clinical Practice (GCP)Good clinical practice (GCP)
is usually referred to as a set of standards forclinical studies to
achieve and maintain high-quality clinical research in asensible
and responsible manner. The FDA, the Committee for
ProprietaryMedicinal Products (CPMP) for the European Community,
the Ministryof Health and Welfare of Japan, and agencies in other
countries have eachissued guidelines on good clinical practices.
For example, the FDA pro-mulgated a number of regulations and
guidelines governing the conduct ofclinical studies from which data
was to be used to support applications formarketing approval of
drug products. The FDA regulations referring toGCP are specified in
CFR parts 50 (protection of human subjects), 56 (in-stitutional
review boards, IRB), 312 (investigational new drug
application,IND), and 314 (new drug application, NDA). Note that in
1992, Dr. B. Lisook at the FDA assembled a GCP packet to assist
sponsors in the
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1.3. Good Pharmaceutical Practices 15
planning, execution, data analysis, and submission of results to
the FDA(Lisook, 1992). On the other hand, the European Community
establishedprinciples for their own GCP standards in all four
phases of clinical in-vestigation of medicinal products in July
1990. The ICH also issued theGuideline on Good Clinical Practice:
Consolidated Guideline. This guide-line defines the
responsibilities of sponsors, monitors, and investigators inthe
initiation, conduct, documentation, and verification of clinical
studiesto establish the credibility of data and to protect the
rights and integrityof study participants.
In essence, GCP deals with patients protection and the equality
of dataused to prove the efficacy and safety of a drug product. GCP
engures thatall data, information, and documents .related to a
clinical study can beconfirmed as being properly generated,
recorded, and reported through theinstitution by independent
audits.
1.3.3 Current Good Manufacturing Practice (cGMP)cGMP was
promulgated in 1962 as part of the Federal Food, Drug and Cos-metic
Act to afford greater consumer protection during the manufacture
ofpharmaceutical products, cGMP is now codified in 21 CFR 211,
whichprovides minimum requirements for the manufacture, processing,
packing,and holding of a drug product. Its purpose is to assure
that the drug prod-uct meets the requirements of safety, identity,
strength, quality, and puritycharacteristics that it purports to
possess, cGMP covers regulations withrespect to requirements for
organization and personnel, buildings and facil-ities, equipment,
control of components and drug product containers andclosures,
production and process control, packing and process control,
hold-ing and distribution, laboratory controls, records and
reports, and returnedand salvaged drug products. Failure to comply
with cGMP renders the drugadulterated and the person responsible
subject to regulatory action.
Record retention is an important part of cGMP. The FDA suggests
thatrecord retention should follow the principles of (i) two years
after FDAapproval of research or marketing permit, (ii) five years
after applicationfor IND, and (iii) two years if no application
filed.
1.3.4 FDA Inspection
One of the FDAs major responsibilities is to enforce the Federal
Food,Drug, and Cosmetic Act for the protection of public health.
This is oftendone through the FDA Facility Inspection Program,
which is to assure thatthe manufacturer is in compliance with all
applicable FDA regulations. Thepurpose of an FDA inspection is
multifold. First, it is to determine and to
Copyright 2002 by Marcel Dekker, Inc. All Rights Reserved.
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16 Chapter 1. Introduction
evaluate a firms adherence to the concepts of cGMP. Second, it
is to ensurethat production and control procedures include all
reasonable precautionsto ensure the identity, strength, quality,
purity, stability, and reproducibil-ity of the finished products.
In addition, it is to identify deficiencies thatcould lead to the
manufacturing and distribution of products in violationof the
Federal Food, Drug, and Cosmetic Act. Furthermore, it is to
obtaincorrection of those deficiencies and to ensure that new drugs
are manufac-tured by essentially the same procedures and the same
formulations as theproducts used as the basis for approval.
Basically, the FDA may initiate different types of inspections
dependingupon the circumstances at different stages of drug
research and develop-ment. These types of inspections include
routine scheduled/unscheduled,survey, compliant, recall,
bioresearch monitoring, government contract, andpreapproval
inspections. The process of a FDA inspection usually beginswith a
notice of inspection (form 482). The sponsor should beprepared
foran FDA inspection upon the receipt of 482. After the inspection,
the FDAinspector(s) will prepare an establishment inspection report
(EIR) includ-ing 483 notice of observations. The sponsor should
address 483 issues fullyin response to the FDA Local Field Office.
If no action is required as theresult of the sponsors response to
483 and EIR, the sponsor is considered tohave met the requirement
of the FDAs inspection. However, if an actionis required, samples
will be sent to the FDA District Office ComplianceOffice and a
warning letter will be issued. Failure to comply with cGMP,GLP,
and/or GCP could subject the sponsor to a regulatory action, suchas
seizure, injunction, prosecution, citation (483 notice of
observations),detention (hold of shipment), fine, affection of
license or permits, or importdetention. For a better understanding,
Figure 1.3.1 provides a flowchartfor the FDA inspection
process.
In the FDAs inspection for GLP, cGMP, and GCP, some
commonlyobserved errors should be avoided. These errors inlcude (i)
document notsigned, (ii) incomplete records, e.g., missing date,
time, specification num-ber, batch number, and anything else left
blank, etc., (iii) correction notsigned, (iv) out of specific
condition, e.g., not performed at proper time specified in the
study protocol, (v) incorrect sampling plan, e.g., sampleswere not
uniformly and randomly selected from the target population
toconstitute a representative sample, (vi) incorrect information,
e.g., wrongcalculation and typos in date and transposed number,
etc., and (vii) incor-rect techniques, e.g., inappropriate use of
pencil, blue ink, white out/liquidpaper, and crossed out mistakes.
The FDA inspection for GLP, cGMP, andGCP assures not only that the
sponsor is in compliance with all applicableFDA regulations during
the drug development process, but also that thedrug product meets
regulatory requirements for the good drug characteris-tics of
identity, strength, quality, purity, Stability, and
reproducibility.
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1.3. Good Pharmaceutical Practices 17
482Notice of Inspection
ERIEstablishment
Inspection Report
[Notice of Observations[~
(gz product samples)/
FDA Local Field Office
Supervisor
Action Required483 & EIR
& Samples sent to
FDADistrict Office
Compliance Officer
No Action Requiredin response to
483 & EIR
Discussed inExit Interview
copy sent toCompany
Company Responseto 483
FDADistrict Director
Warning Letterissued
Figure 1.3.1. FDA Inspection Process
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18 Chapter 1. Introduction
1.4 Good Statistics Practice
Good statistics practice (GSP) is defined as a set of
statistical principlesfor the best pharmaceutical practices in
design and analysis of studies con-ducted at various stages of drug
research and development (Chow, 1997a).The purpose of GSP is not
only to minimize bias but also to minimizevariability that may
occur before, during, and after the conduct of thestudies. More
importantly, GSP provides a valid and fair assessment ofthe drug
product under study. The concept of GSP can be seen in
manyguidelines and guidances that were issued by the FDA at various
stagesof drug research and development. These guidelines and
guidances includegood laboratory practice (GLP), good clinical
practice (GCP), current manufacturing practice (cGMP), and good
regulatory practice (GRP). 6ther example of GSP is the guideline on
Statistical Principles in ClinicalTrials recently issued by the
International Conference on Harmonization(ICH, 1998b). As a result,
GSP can not only provide accuracy and reliabil-ity of the results
derived from the studies, but also assure the vMidity andintegrity
of the studies.
The implementation of GSP in pharmaceutical research and
develop-ment is a team project that requires mutual communication,
confidence,respect, and cooperation among statisticians,
pharmaceutical scientists inthe related areas, and regulatory
agents. The implementation of GSP in-volves some key factors that
have an impact on the success of GSP. Thesefactors include (i)
regulatory requirements for statistics, (ii) the dissemi-nation of
the concept of statistics, (iii) appropriate use of statistics,
(iv)effective communication and flexibility, and (v) statistical
training. Thesefactors are briefly described below.
In the pharmaceutical development and approval process,
regulatory re-quirements for statistics are the key to the
implementation of GSP. Theynot only enforce the use of statistics
but also establish standards for sta-tistical evaluation of the
drug products under investigation. An unbiasedstatistical
evaluation helps pharmaceutical scientists and regulatory agentsin
determining (i) whether the drug product has the claimed
effectivenessand safety for the intended disease, and (ii) whether
the drug productpossesses good drug characteristics such as the
proper identity, strength,quality, purity, and stability.
In addition to regulatory requirements, it is always helpful to
dissemi-nate the concept of statistical principles described above
whenever possible.It is important for pharmaceutical scientists and
regulatory agents to rec-ognize that (i) a valid statistical
inference is necessary to provide a fairassessment with certain
assurance regarding the uncertainty of the drugproduct under
investigation, (ii) an invMid design and analysis may resultin a
misleading or wrong conclusion about the drug product, and
(iii)
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1.4. Good Statistics Practice 19
larger sample size is often required to increase statistical
power and preci-sion of the studies. The dissemination of the
concept of statistics is criticalto establish the pharmaceutical
scientists and regulatory agents brief instatistics for scientific
excellence.
One of the commonly encountered problems in drug research and
devel-opment is the misuse or sometimes the abuse of Statistics in
some studies.The misuse or abuse of statistics is critical, which
may result in either hay-ing the right question with the wrong
answer or having the right answer forthe wrong question. For
example, for a given study, suppose that a rightset of hypotheses
(the right question) is established to reflect the study
objective. A misused statistical test may provide a misleading
or wronganswer to the right question. On the other hand, in many
clinical trials,point hypotheses for equality (the wrong question)
are often wrongly usedfor establishment of equivalence. In this
case, we have right answer (forequality) for the wrong question. As
a result, it is recommended that ap-propriate statistical methods
be chosen to reflect the design which shouldbe able to address the
scientific or medical questions regarding the intendedstudy
objectives for implementation of GSP.
Communication and flexibility are important factors to the
success ofGSP. Inefficient communication between statisticians and
pharmaceuticalscientists or regulatory agents may result in a
misunderstanding of theintended study objectives and consequently
an invalid design and/or in-appropriate statistical methods. Thus,
effective communications amongstatisticians, pharmaceutical
scientists and regulatory agents is essentialfor the implementation
of GSP. In addition, in many studies, the assump-tion of a
statistical design or model may not be met due to the nature ofthe
drug product under investigation, experimental environment,
and/orother causes related/unrelated to the studies. In this case,
the traditionalapproach of doing everything by the book does not
help. In practice, sinceconcerns from a pharmaceutical scientist or
the regulatory agent may trans-late into a constraint for a valid
statistical design and appropriate statisticalanalysis, it is
suggested that a flexible and yet innovative solution be de-veloped
under the constraints for the implementation of GSP.
Since regulatory requirements for the drug development and
approvalprocess vary from drug to drug and country to country,
various designsand/or statistical methods are often required for a
valid assessment of adrug product. Therefore, it is suggested that
statistical continued/advancededucation and training programs be
routinely held for both statisticians andnonstatisticians including
pharmaceutical scientists and regulatory agents.The purpose of such
a continued/advanced education and/or training pro-gram is
threefold. First, it enhances communications within the
statis-tical community. Statisticians can certainly benefit from
such a trainingand/or educational program by acquiring more
practical experience and
Copyright 2002 by Marcel Dekker, Inc. All Rights Reserved.
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2O Chapter 1. Introduction
knowledge. In addition, it provides the opportunity to
share/exchange in-formation, ideas and/or concepts regarding drug
development between pro-fessional societies. Finally, it identifies
critical practical and/or regulatoryissues that are commonly
encountered in the drug development and regu-latory approval
process. A panel discussion from different disciplines mayresult in
some consensus to resolve the issues
, which helps in establishing
standards of statistical principles for implementation of
GSP.
1.5 Aim of the Book and Outline of PracticalIssues
1.5.1 The Aim and Scope of the Book
As indicated earlier, drug development is a lengthy and costly
process. Thepurpose of this lengthy and costly process is not only
to ensure the safetyand efficacy of the drug under investigation
before approval, but also toassure the drug possesses some good
drug characteristics such as identity,strength, quality, purity,
and stability after approval. Statistics plays an im-por.tant role
in the process of drug research and development. In the processof
drug development, misusing, abusing, or not using statistics often
resultsin misleading results/conclusions and inflating the false
positive/negativerates. Appropriate use of statistics provides a
fair and unbiased assessmentof the drug under investigation with a
certain degree of accuracy and re-liability. The concept of good
statistics practice in design, analysis, andinterpretation of
studies conducted during the drug development process isthe key to
the success of drug development.
This book is intended to provide a well-balanced summarization
of cur-rent and emerging practical issues and the corresponding
statistical method-ologies in various stages of drug research and
development. Our emphasis ison recent development in regulatory
requirement and statistical methodol-ogy for these practical
issues. It is our goal to fill the gap between pharma-Ceutical and
statistical disciplines and to provide a comprehensive
referencebook for pharmaceutical scientists and biostatisticians in
the area of drugresearch and development.
The scope of this book covers practical issues from nonclinical,
pre-clinical, and clinical areas. Previous sections of this chapter
provide anintroduction to the drug development process and
regulatory requirementfor approving a drug product and an overview
of good pharmaceutical prac-tices and good statistics practice.
Nonclinical and preclinical applicationsare presented in Chapter 2
through Chapter 5. Practical issues that arecommonly seen in
clinical development are discussed in Chapter 6 through
Copyright 2002 by Marcel Dekker, Inc. All Rights Reserved.
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1.5. Aim of the Book and Outline of Practical Issues 21
Chapter 12.The following is an outline of the practical issues
covered in this book
and what each of Chapters 2-12 covers.
1.5.2 Pharmaceutical Validation
As indicated by Bergum and Utter (2000), pharmaceutical
validationstarted in the early 1970s with assay verification.
However, most of theFDAs attention was directed toward the
validation of sterile processes ofinjectable products. In the early
1980s, the FDA began to focus on the vali-dation of nonsterile
processes such as solid dosage, semisolid dosage,
liquids,suspensions, and aerosols. Basically, pharmaceutical
validation includes thevalidation of laboratory instruments, such
as gas chromatography (GC),and high-performance liquid
chromatography (HPLC), or analytical meth-ods developed based on
these instruments and manufacturing processes forspecific
compounds. The cGMP requires that the sponsors establish
thereliability of test results through the appropriate validation
of the test re-sults at appropriate intervals (21 CFR 210 and 211).
More specifically,the cGMP requires that the accuracy and
reliability of the test results beestablished and validated. The
purpose of analytical method validation isto ensure that the assay
result meets the proper standards of accuracy andreliability, while
the purpose of the manufacturing process is to ensure thatthe
rnanufacturing process does what it purports to do (Chow,
1997b).
The USP/NF defines the validation of analytical methods as the
processby which it is established, in laboratory studies, that
performance charac-teristics of the methods meet the requirements
for the intended analyticalapplication (USP/NF, 2000). The
analytical application could be a drugpotency assay for potency and
stability studies, immunoassay for the invitro activity of an
antibody or antigen, or a biological assay for the invivo activity.
The performance characteristics include accuracy,
precision,selectivity (or specificity), linearity, range, limit of
detection, limit of quan-titation, and ruggedness which are useful
measures for the assessment ofthe accuracy and reliability of the
assay results. In practice, the selectionof a model and/or weights
for the standard curve in calibration is criticalfor assurance of
the accuracy and reliability of the assay results.
Statisticalmethods for evaluation of the analytical method based on
each performancecharacteristic under the selected model with
appropriate weight are neces-sarily developed and justified in
compliance with regulatory requirementsfor good validation
practice.
The FDA defines process validation as establishing documented
evi-dence which provides a high degree of assurance that a specific
process willconsistently produce a product meeting its
predetermined specifications and
Copyright 2002 by Marcel Dekker, Inc. All Rights Reserved.
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22 Chapter 1. Introduction
quality characteristics (FDA, 1987a). A manufacturing process is
necessar-ily validated to ensure that it does what it purports to
do. A valid processassures that the final product has a high
probability of meeting the stan-dards for identity, strength,
quality, purity, stability, and reproducibilityof the drug product.
A manufacturing process is a continuous process in-volving a number
of critical stages. A manufacturing process is consideredvalidated
if at least three batches (or lots) pass the required USP/NF
tests.A batch is considered to pass the USP/NF tests if each
critical stage andthe final product meet the USP/NF specifications
for identity, strength,quality, purity, stability, and
reproducibility. USP/NF tests are referredto as tests for potency,
content uniformity (weight variation), disintegra-tion,
dissolution, and stability, which are usually conducted according
tothe testing plan, sampling plan, and acceptance criteria as
specified in theUSP/NF. In practice, it is of interest to establish
in-house specificationlimits for each USP/NF tests at each critical
stage of the manufacturingprocess, so that if the test results meet
the in-house specification limits,there is a high probability that
future batches (lots) will also meet theUSP/NF specifications prior
to the expiration dating period.
More details regarding regulatory requirements and statistical
issues forselection of an appropriate standard curve in calibration
for assay develop-ment and validation are given in Chapter 2. Also
included in Chapter 2are the concept of in-process controls and
process validation and statisticalmethods for establishment of
in-house specification limits.
1.5.3 Dissolution Testing
For oral solid dosage forms of drug products, dissolution
testing is usuallyconducted to assess the rate and extent of drug
release. The purpose ofdissolution testing is multifold. First, it
is to ensure that a certain amountof the drug product will be
released at a specific time point after adminis-tration in order
for the drug to be efficiently delivered to the site of actionfor
optimal therapeutic effect. Second, it is to ensure that the
dissolution ofthe drug product meets the acceptance limits for
quality assurance beforethe drug product is released to the
marketplace. Finally, it is to monitorwhether the dissolution of
the drug product meets the product specificationlimits prior to the
expiration dating period (or shelf-life) of the drug prod-uct. For
a valid and fair assessment of the dissolution of the drug
product,specific sampling plan, acceptance criteria, and testing
procedure are nec-essarily conducted in order to meet regulatory
requirements for accuracyand reliability (USP/NF, 2000). The USP/NF
suggests that a three-stagesampling plan be adopted. At each stage,
a set of criteria must be metin order to pass the test. A set of
in-hou~se specification limits is usuallyconsidered to ensure that
there is a high probability of passing the USP/NF
Copyright 2002 by Marcel Dekker, Inc. All Rights Reserved.
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1.5. Aim of the Book and Outline of Practical Issues 23
dissolution test if the test results meet the in-house
specification limits.Recently, the in vitro dissolution testing has
often been considered a
surrogate for in vivo bioequivalence testing, which in turn
serves as a sur-rogate for clinical outcomes. When two drug
products are bioequivalentto each other, it is assumed that they
reach the same therapeutic effect orthat they are therapeutically
equivalent. Under the assumption that thereis a correlation between
the in vitro dissolution testing and the in vivobioequivalence
testing, the FDA requires that dissolution profiles betweenthe two
.drug products be compared, in addition to the usual USP test
fordissolution. The FDA recommends a similarity factor, which is
known asthe f2 similarity factor, be evaluated to determine whether
two drug prod-ucts have similar dissolution profiles. The use of
the f2 similarity factorhas received much criticism since it was
introduced by the FDA.
In practice, it is of interest to evaluate the probability of
passing dis-solution testing according to the sampling plan and
acceptance criteria asspecified by the USP/NF. The information is
useful for the construct ofin-house specification limits for the
quality control and assurance of futurebatches of the drug product.
In addition, it is of particular interest to studythe statistical
properties of the f2 similarity factor as suggested by the FDAfor
dissolution profile comparison.
Chapter 3 provides an extensive discussion regarding the
evaluation ofthe probability of passing the USP/NF dissolution test
and statistical as-sessment of similarity between dissolution
profiles, including a review of thef2 similarity factor and a
discussion of some recently developed methods.
1.5.4 Stability Analysis
For each drug product on the market, the FDA requires that an
expira-tion dating period (or shelf-life) be indicated on the
immediate containerof the drug product. The expiration dating
period (or shelf-life) is definedas the interval at which the drug
characteristics remain unchanged. Asindicated in the FDA Stability
Guideline (FDA, 1987b) and in the stabil-ity guideline published by
the International Conference on Harmonization(ICH, 1993), the
shelf-life can be determined as the time interval at whichthe lower
product specification intersects the 95% confidence lower boundof
the average degradation curve of the drug product. In practice,
stabilitystudies are usually conducted to characterize the
degradation curve of thedrug product under appropriate storage
conditions. The FDA and ICHstability guidelines require that at
least three batches (lots) and prefer-ably more batches be tested
for the establishment of a single shelf-life forthe drug product.
It is suggested that stability testing be performed at athree-month
interval for the first year, a six-month interval for the
second
Copyright 2002 by Marcel Dekker, Inc. All Rights Reserved.
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24 Chapter 1. Introduction
year, and yearly after that. Stability test results can be
combined for theestablishment of a single shelf-life if there is no
batch-to-batch variation. Apreliminary test for batch similarity
should be performed at the 25% levelof significance before the data
can be combined for analysis.
In recent years, the study of the effectiveness and safety of
combinationdrug products, which may or may not have been approved
by regulatoryagencies, has attracted much attention. The relative
proportions of indi-vidual drug products in the combination drug
product and the potentialdrug-to-drug interaction (over time) may
have an impact on the stabilityof the combined drug product. A
typical approach is to consider the mini-mum of the shelf-lives
observed from the individual drug products based onthe percent of
label claim. This method, however, is not only too conser-vative to
be of practical interest, but it also lacks statistical
justification.Therefore, how to establish the shelf-life of a
combination drug producthas become an interesting scientific
question. This question also applies toChinese herbal medicines,
which often contain a number of active ingredi-ents with different
ratios. In practice, it is, therefore, of interest to
explorestatistical methods for the shelf-life estimation of drug
products with mul-tiple components. Other statistical issues
related to stability include thedevelopment of statistical methods
for shelf-life estimation of frozen drugproducts, practical issues
and considerations in stability design and anal-ysis (such as the
use of matrixing) and bracketing designs and shelf-lifeestimation
with discrete responses.
Chapter 4 provides a comprehensive review of statistical designs
andmethods for stability analysis. In addition, statistical methods
and recentdevelopment for two phase shelf-life estimation of frozen
drug products,stability analysis with discrete responses, and
shelf-life estimation of drugproducts with multiple components are
discussed.
1.5.5 Bioavailability and Bioequivalence
When a brand-name drug is going off patent, the sponsors can
file an ab-breviated new drug application (ANDA) for generic
approval. For approvalof generic copies of a brand-name drug, the
FDA requires that a bioequiv-alence trial be conducted to provide
evidence of bioequivalence in drugabsorption (FDA, 1992; 2000a).
The FDA indicates that an approvedgeneric copy of a brand-name drug
can serve as the substitute of the brand-name drug. However, the
FDA does not indicate that two approved genericcopies of the same
brand-name drugs can be used interchangeably. As moregeneric drugs
become available, the safety of drug interchangeability
amonggeneric drugs of the same brand-name drug is of great concern
to consumersand the regulatory agencies as well.
Copyright 2002 by Marcel Dekker, Inc. All Rights Reserved.
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1.5. Aim of the Book and Outline of Practical Issues 25
The concept of drug interchangeability can be divided into
prescribabil-ity and switchability. Prescribability is referred to
as a physicians choicefor prescribing an appropriate drug between
the brand-name drug and itsgeneric copies, while switchability is
the switc.h from a brand-name drugor its generic copies to its
generic copies within the same patient. TheFDA suggests that the
population bioequivalence be assessed to addressprescribability.
For switchability, the concept of individual bioequivalenceis
recommended. In practice, it is of interest to explore the
statistical prop-erties of the bioequivalence criteria for both
population bioequivalence andindividual bioequivalence, as proposed
by the FDA.
In a recent FDA guidance on population bioequivalence and
individ-ual bioequivalence, the FDA recommends the method proposed
by Hyslop,Hsuan, and Holder (2000) for assessment of population
bioequivalence andindividual bioequivalence (FDA, 2001). In
addition, the FDA recommendsthat a two-sequence, four-period (2 x
4) crossover design be used and thata two-sequence, three-period (2
x 3) crossover design may be used as alternative to the 2 x 4
crossover design if necessary. Although a detailedstatistical
procedure for assessment of individual bioequivalence under a2 x 4
crossover design is provided in the FDA draft guidance, little or
noinformation regarding statistical procedures for (i) assessment
of individualbioequivalence under a 2 x 3 crossover design and (ii)
assessment of popu-lation bioequivalence under either a 2 x 2, 2 x
3, or 2 x 4 crossover designis given.
Chapter 5 provides details of recent development on criteria and
sta-tistical methods for assessment of population bioequivalence
and individ-ual bioequivalence under various crossover designs. In
addition, statisticalmethods for assessment of in vitro
bioequivalence are also discussed.
1.5.6 Randomization and Blinding
The ultimate goal of most clinical trials is to demonstrate the
safety andefficacy of the study drug products. A typical approach
is to first showthat there is a significant difference between the
study drug product withthe control (e.g., a placebo or an active
control agent) with some statis-tical assurance. Power for
detection of a clinically meaningful differenceis then obtained to
determine the chance of correctly detecting the differ-ence when
such a difference truly exists. Statistical inference or
assuranceon the uncertainties regarding the drug products under
investigation canonly be obtained under a probability structure of
the uncertainties. Theprobability structure cannot be established
without randomization. As aresult, randomization plays an important
role in clinical trials. If there is norandomization, then there is
no probability structure, and hence, there isno statistical
inference on which the uncertainties can be drawn. Random-
Copyright 2002 by Marcel Dekker, Inc. All Rights Reserved.
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26 Chapter 1. Introduction
ization not only generates comparable groups of patients who
constituterepresentative samples from the intended patient
population, but also en-able valid statistical tests for clinical
evaluation of the study drug product.
In clinical trials, bias often occurs due to the knowledge of
the identityof treatment. To avoid such a bias, blinding is
commonly employed toblock the indentity of treatments. In practice,
it is of interest to determinethe integrity of blinding based on
the probability of correctly guessing thetreatment codes. When the
integrity of blinding is questionable, adjustmentshould be made in
statistical inference on the efficacy of the study drug.
In Chapter 6, the concept of randomization, randomization models
andmethods, and blinding are introduced, followed by discussions of
practi-cal issues related to randomization and blinding, such as
the selection ofthe number of study centers in a multicenter trial,
the effect of mixed-uprandomization schedule, assessment of
integrity of blinding, and inferenceunder breached blindness.
1.5.7 Substantial Evidence in Clinical Development
For the approval of a new drug product, the FDA requires that
substantialevidence regarding the safety and efficacy of the drug
product be providedthrough the conduct of at least two adequate and
well-controlled clinicaltrials. The purpose for having at least two
adequate and well-controlledclinical trials is not only to ensure
that the clinical results observed from thetwo clinical trials are
reproducible, but also to provide valuable informationregarding
generalizability of the results to a similar but different
patientpopulation.
In recent years, regulatory agencies are constantly challenged
for scien-tific justification of the requirement that at least two
adequate and well-controlled clinical trials are necessary for
generalizability and reproducibil-ity. In some cases, the
variability associated with a powered clinical trialmay be
relatively small, and/or the observed p-value is relatively
small.These facts are often used to argue against the requirement
of at least twoadequate and well-controlled trials. Note that,
under certain circumstance,the FDA Modernization Act of 1997
includes a provision to allow datafrom one adequate and
well-controlled clinical trial investigation and con-firmatory
evidence to establish effectiveness for risk/benefit assessment
ofdrug and biological candidates for approval. Thus, if one can
show a highprobability of observing a significant result in future
studies given that asignificant result has been observed in a
clinical trial that is similar to futurestudies, then the observed
result from one clinical trial may be sufficient tofulfill the
regulatory requirement.
The concept of reproducibility probability and generalizability
probabil-
Copyright 2002 by Marcel Dekker, Inc. All Rights Reserved.
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1.5. Aim of the Book and Outline of Practical Issues 27
ity of a positive clinical result is introduced in Chapter 7.
Several statisticalmethods for evaluation of these probabilities
based on observed clinical re-sults are proposed. Applications such
as bridging studies are also included.
1.5.8 Therapeutic Equivalence and Noninferiority
In drug research and development, therapeutic equivalence and
noninferi-ority trials have become increasingly popular.
Therapeutic equivalence/noninferiority trials usually involve the
comparison of a test drug with acontrol. The assessment of
therapeutic equivalence/noninferiority dependsupon the choice of a
clinically meaningful difference which may vary fromindication to
indication and from therapy to therapy.
For the establishment of the safety and efficacy of a new drug
prod-uct, the FDA prefers that placebo-control clinical trials be
considered ifpossible. However, in many cases, placebo-control
clinical trials may notbe feasible, such as with anti-infective
agents. In addition, it may not beethical to conduct
placebo-control clinical trials for patients with severe
orlife-threatening diseases, such a cancer or AIDS. As a result,
active con-trol trials are preferred in these situations as
alternative clinical trials overplacebo-control clinical
trials.
Basically, the primary objective of an active control trial is
either toshow noninferiority or therapeutic equivalence. Without
the inclusion of aplacebo, the active control trial could lead to
the conclusion that the testdrug and the active control agent are
either both effective or both ineffec-tive. In practice, it is then
of particular interest to develop an appropriatestatistical
methodology for providing direct evidence of the safety and
effi-cacy of the study drug provided that the safety and efficacy
information ofthe active control agent as compared to a placebo is
available.
Chapter 8 introduces the concepts of therapeutic equivalence and
nonin-feriority tests in clinical research, including the selection
of controls, intervalhypotheses for equivalence/noninferiority, and
equivalence lirnit or nonin-feriority margin. Two commonly used
statistical methods for assessment oftherapeutic
equivalence/noninferiority, the two one-sided tests procedureand
the confidence interval approach, are introduced and some related
sta-tistical issues are discussed. Also included in this chapter,
are discussions onactive control trials and active control
equivalence trials in clinical develop-ment. Statistical methods
for determination of direct evidence of efficacyof a test drug
product relative to a placebo in an active control trial
arestudied.
Copyright 2002 by Marcel Dekker, Inc. All Rights Reserved.
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28 Chapter 1. Introduction
1.5.9 Analysis of Incomplete Data
In clinical trials, dropouts and missing values may occur due to
medicalevaluations, administrative considerations, or other reasons
unrelated tothe conduct of the trials. As a result of dropouts or
missing values, theobserved clinical data are incomplete. When
dropouts or missing valuesare not related to the main response
variable used to evaluate treatmenteffects, i.e., a dropout or
missing value is at random, statistical inferencecan be made by
conditioning on the observed incomplete data. Chapter 9studies the
effect of the rate of missing values on the statistical power ofthe
tests for treatment effects. The result is useful for the
determination ofsample size in planning a clinical trial to account
for possible missing valuesin order to achieve the desired power.
In some cases, information providedby auxiliary variables can be
used to improve the statistical power, whichis also discussed in
Chapter 9.
When dropouts or missing values are related to the main response
vari-able used to evaluate treatment effects, the evaluation of
treatment effectsbetween patients who stay and patients who drop
out is necessary to providea fair and unbiased assessment of the
treatment effect. As indicated in theICH guideline, the primary
analysis of clinical trials should be the one basedon the
intention-to-treat population. The analysis of this kind is
referredto as the intention-to-treat analysis. For efficacy
evaluation, the intention-to-treat population is usually defined as
all randomized patients who haveat least one post-treatment
assessment regardless of noncompliance anddropouts. For safety
assessment, the intention-to-treat population includesall
randomized patients who take any amount of study medications.
Whendropouts occur during the conduct of clinical trials with
repeated measure-ments, the approach using the concept of last
observation carried forward(LOCF) is recommended. The validity of
this approach has been challengedby many researchers. Chapter 9
provides a comprehensive evaluation of theLOCF analysis. Some other
methods providing valid statistical inferencein analysis of last
observation and analysis of longitudinal data, which areuseful when
the LOCF analysis fails, are also introduced in Chapter 9.
1.5.10 Meta-Analysis
Meta-analysis is a systematic reviewing strate