Statistical Issues in Drug Development (Statistics in Practice) [Hardcover]

Stephen S Senn (Author)

Book Description

ISBN-10: 0470018771 | ISBN-13: 978-0470018774 | Publication Date: March 4, 2008 | Edition: 2

Drug development is the process of finding and producing therapeutically useful pharmaceuticals, turning them into safe and effective medicine, and producing reliable information regarding the appropriate dosage and dosing intervals. With regulatory authorities demanding increasingly higher standards in such developments, statistics has become an intrinsic and critical element in the design and conduct of drug development programmes.

Statistical Issues in Drug Development presents an essential and thought provoking guide to the statistical issues and controversies involved in drug development. 

This highly readable second edition has been updated to include:

• Comprehensive coverage of the design and interpretation of clinical trials.
• Expanded sections on missing data, equivalence, meta-analysis and dose finding.
• An examination of both Bayesian and frequentist methods.
• A new chapter on pharmacogenomics and expanded coverage of pharmaco-epidemiology and pharmaco-economics.
• Coverage of the ICH guidelines, in particular ICH E9, Statistical Principles for Clinical Trials.

It is hoped that the book will stimulate dialogue between statisticians and life scientists working within the pharmaceutical industry. The accessible and wide-ranging coverage make it essential reading for both statisticians and non-statisticians working in the pharmaceutical industry, regulatory bodies and medical research institutes. There is also much to benefit undergraduate and postgraduate students whose courses include a medical statistics component.

Editorial Reviews

Review

For all his contributions to the development and exposition of medical statistics Stephen Senn is awarded the 2009 Bradford Hill Medal by the Royal Statistical Society.

?This book is a thought provoking, intriguing, and often challenging read. The author is unafraid to tackle weighty philosophical and paradigmatic issues, and he generally does so with great skill and insight. ...this excellent book should serve to inspire both statisticians and life scientists.? (Journal of the American Statistical Association, September 2009)

"For statisticians, this should be required reading for anyone considering or starting out on a career in clinical drug development. I am also quite sure that most experienced statisticians would find this a useful book to dip into on occasion ... . This book will not disappoint." (Journal of the Royal Statistical Society: Series A (Statistics in Society), April 2009)

"This book is an outstanding effort from a statistician of heroic proportions. Someone like me is only capable of sitting on the curb and applauding wildly." (Journal of Biopharmaceutical Statistics, Volume 19, Issue 1, 2009)

From the Publisher

This book for non-statisticians explains the statistical issues in drug development to help them plan, analyze and interpret clinical trials. It also examines the commercial pressures, regulatory standards and high scrutiny that accompany this field. --This text refers to an out of print or unavailable edition of this title.

See all Editorial Reviews

Product Details

• Hardcover: 524 pages
• Publisher: Wiley-Interscience; 2 edition (March 4, 2008)
• Language: English
• ISBN-10: 0470018771
• ISBN-13: 978-0470018774
• Product Dimensions: 6.9 x 1.4 x 9.8 inches
• Shipping Weight: 2.3 pounds (View shipping rates and policies)
• Average Customer Review: 5.0 out of 5 stars  See all reviews (1 customer review)
• Amazon Best Sellers Rank: #388,051 in Books (See Top 100 in Books)

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Customer Reviews

Most Helpful Customer Reviews

31 of 31 people found the following review helpful:

5.0 out of 5 stars beautiful expository writing on key issues in drug development and clinical trials, February 6, 2008

By 

Michael R. Chernick "statman31147" (Holland PA) - See all my reviews
(REAL NAME)   

This review is from: Statistical Issues in Drug Development (Hardcover)

Senn is a great writer. He has written an excellent text on cross-over trials that raises many issues about when such design can be used and what their limitations are. This book covers the gamut of issues in drug development concentrating on important and sometimes subtle issues in clinical trials including design and analysis, intention to treat principle, multiple testing, Bayesian and frequentist approaches and interpretations, meta analysis, regulatory issues and ethics. It also covers cross-over designs, pharmacokinetics, pharmacodynamics and pharmacoeconomics.
The introduction gives you a feeling for the approach in the book and how it splits into two parts. Part I, consisting of chapters 2-5, provides some history of the development of statistical methods and some introductory topics that are fundamental to the discussion in Part II.

Part II is the heart of the book where the practical statistical issues in clinical trials are raised. The text is intended for non-statisticians who work in the pharmaceutical industry but to quote part of Senn's preface he states "Although addressed to the life-scientist it is my hope that many statisticians, in particular those studying medical statistics or embarking on a career in drug development, will also find it useful. Above all I hope that it will help communication between the disciplines: a process by which the statistician stands to benefit as much as any other professional in drug development."

I can really appreciate what Senn has done. He explains the issues of intention-to-treat, washout, multiplicity and other problems that I have had to wrestle with and try to explain to MDs and clinical managers. But even more importantly to me than helping me communicate the many issues that I was aware of, he also raises many subtle issues that I was not aware of. This includes questions of bioequivalence, the use of baseline information and particularly percentage change from baseline versus covariate adjustment, problems of inference regarding measurements taken after titration and issuesw in N of 1 trials. I even learned a few new techniques (e.g. Taves minimiization and Atkinson's generalization of it for allocating patients to treatment groups).

The only complaint I can see is that there is not enough detail. However, remember the text was not designed for statisticians and so much of the mathematics and technicalities are deliberately left out.

But Senn does provides a detailed list of relevant references at the end of each chapter that allows the reader to find in texts and journal articles all the detail one might need. Also to aid with communication there is a large glossary of terms at teh back of the book.

This is a great reference for scientists and statisticians as well!