Pharmaceutical Statistics Using SAS

Additional Book Details

Pharmaceutical Statistics Using SAS: A Practical Guide offers extensive coverage of cutting-edge biostatistical methodology used in drug development and the practical problems facing today's drug developers. Written by well-known experts in the pharmaceutical industry Alex Dmitrienko, Christy Chuang-Stein, and Ralph D'Agostino, it provides relevant tutorial material and SAS examples to help readers new to a certain area of drug development quickly understand and learn popular data analysis methods and apply them to real-life problems. Step-by-step, the book introduces a wide range of data analysis problems encountered in drug development and illustrates them using a wealth of case studies from actual pre-clinical experiments and clinical studies. The book also provides SAS code for solving the problems.

Among the topics addressed are these:

drug discovery experiments to identify promising chemical compounds animal studies to assess the toxicological profile of these compounds clinical pharmacology studies to examine the properties of new drugs in healthy human subjects Phase II and Phase III clinical trials to establish therapeutic benefits of experimental drugs.

Additional features include a discussion of methodological issues, practical advice from subject-matter experts, and review of relevant regulatory guidelines. Most chapters are self-contained and include a fair amount of high-level introductory material to make them accessible to a broad audience of pharmaceutical scientists. This book will also serve as a useful reference for regulatory scientists as well as academic researchers and graduate students.

Book Review

"This book is an ideal overview of some of the many important issues arising in the pharmaceutical industry, and can be read as such. Students anticipating a career in pharmaceutical statistics will benefit particularly: these are topics that form the backbone of statistics in the industry but that are not generally taught as part of an M.S. or Ph.D. program. Implementation using SAS is admirably detailed, but even non-users of SAS will find the book useful."

Raymond J. Carroll

Distinguished Professor of Statistics, Nutrition and Toxicology

Texas A and M University

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