Studies in bioequivalence are the commonly accepted method to
demonstrate therapeutic equivalence between two medicinal products.
Savings in time and cost are substantial when using bioequivalence
as an established surrogate marker of therapeutic equivalence. For
this reason the design, performance and evaluation of
bioequivalence studies have received major attention from academia,
the pharmaceutical industry and health authorities.
Bioequivalence Studies in Drug Development focuses on the
planning, conducting, analysing and reporting of bioequivalence
studies, covering all aspects required by regulatory authorities.
This text presents the required statistical methods, and with an
outstanding practical emphasis, demonstrates their applications
through numerous examples using real data from drug
development.
* Includes all the necessary pharmacokinetic background
information.
* Presents parametric and nonparametric statistical
techniques.
* Describes adequate methods for power and sample size
determination.
* Includes appropriate presentation of results from
bioequivalence studies.
* Provides a practical overview of the design and analysis of
bioequivalence studies.
* Presents the recent developments in methodology, including
population and individual bioequivalence.
* Reviews the regulatory guidelines for such studies, and the
existing global discrepancies.
* Discusses the designs and analyses of drug-drug and food-drug
interaction studies.
Bioequivalence Studies in Drug Development is written in
an accessible style that makes it ideal for pharmaceutical
scientists, clinical pharmacologists, and medical practitioners, as
well as biometricians working in the pharmaceutical industry. It
will also be of great value for professionals from regulatory
bodies assessing bioequivalence studies.
Inhoudsopgave
Preface.
1 Introduction.
1.1 Definitions.
1.2 When are bioequivalence studies performed.
1.3 Design and conduct of bioequivalence studies.
1.4 Aims and structure of the book.
References.
2 Metrics to characterize concentration-time profiles in
single- and multiple-dose bioequivalence studies.
2.1 Introduction.
2.2 Pharmacokinetic characteristics (metrics) for single-dose
studies.
2.3 Pharmacokinetic rate and extent characteristics (metrics)
for multiple-dose studies.
2.4 Conclusions.
References.
3 Basic statistical considerations.
3.1 Introduction.
3.2 Additive and multiplicative model.
3.3 Hypotheses testing.
3.4 The RT/TR crossover design assuming an additive
model.
References.
4 Assessment of average bioequivalence in the RT/TR
design.
4.1 Introduction.
4.2 The RT/TR crossover design assuming a multiplicative
model.
4.3 Test procedures for bioequivalence assessment.
4.4 Conclusions.
References.
5 Power and sample size determination for testing average
bioequivalence in the RT/TR design.
5.1 Introduction.
5.2 Challenging the classical approach.
5.3 Exact power and sample size calculation.
5.4 Modified acceptance ranges.
5.5 Approximate formulas for sample size calculation.
5.6 Exact power and sample size calculation by n Query®.
References.
Appendix.
6 Presentation of bioequivalence studies.
6.1 Introduction.
6.2 Results from a single-dose study.
6.3 Results from a multiple-dose study.
6.4 Conclusions.
References.
7 Designs with more than two formulations.
7.1 Introduction.
7.2 Williams designs.
7.3 Example: Dose linearity study.
7.4 Multiplicity.
7.5 Conclusions.
References.
8 Analysis of pharmacokinetic interactions.
8.1 Introduction.
8.2 Pharmacokinetic drug-drug interaction studies.
8.3 Pharmacokinetic food-drug interactions.
8.4 Goal posts for drug interaction studies including no effect
boundaries.
8.5 Labeling.
8.6 Conclusions.
References.
9 Population and individual bioequivalence.
9.1 Introduction.
9.2 Brief history.
9.3 Study designs and statistical models.
9.4 Population bioequivalence.
9.5 Individual bioequivalence.
9.6 Disaggregate criteria.
9.7 Other approaches.
9.8 Average bioequivalence in replicate designs.
9.9 Example: The anti-hypertensive patch dataset.
9.10 Conclusions.
References.
10 Equivalence assessment in case of clinical
endpoints.
10.1 Introduction.
10.2 Design and testing procedure.
10.3 Power and sample size calculation.
10.4 Conclusions.
Apendix.
References.
Index.
Over de auteur
Dieter Hauschke, ALTANA Pharma, Konstanz, Germany.
Well-respected statistician working in the pharmaceutical industry,
specializing in bioequivalence studies, with over 60 publications
in leading journals.
Volker Steinijans, ALTANA Pharma, Konstanz, Germany. Head
of the Department of Biometry and Clinical Data Management at
ALTANA.
Iris Pigeot, Institute for Statistics, University of
Bremen, Germany. Has over 50 published papers, and also written a
number of books in German.
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