Pharmaceutical Statistics Using SAS: A Practical Guide
- 9h 43m
- Alex Dmitrienko, Christy Chuang-Stein, Ralph D'Agostino
- SAS Institute
- 2007
This essential new book 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, 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.
In this Book
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Pharmaceutical Statistics Using SAS—A Practical Guide
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Statistics in Drug Development
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Modern Classification Methods for Drug Discovery
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Model Building Techniques in Drug Discovery
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Statistical Considerations in Analytical Method Validation
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Some Statistical Considerations in Nonclinical Safety Assessment
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Nonparametric Methods in Pharmaceutical Statistics
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Optimal Design of Experiments in Pharmaceutical Applications
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Analysis of Human Pharmacokinetic Data
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Allocation in Randomized Clinical Trials
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Sample-Size Analysis for Traditional Hypothesis Testing: Concepts and Issues
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Design and Analysis of Dose-Ranging Clinical Studies
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Analysis of Incomplete Data
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Reliability and Validity: Assessing the Psychometric Properties of Rating Scales
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Decision Analysis in Drug Development
