A Handbook Of Applied Statistics In Pharmacology

Statistics plays an important role in pharmacology and related subjects such as toxicology and drug discovery and development. Improper statistical tool selection for analyzing the data obtained from studies may result in wrongful interpretation of the performance or safety of drugs. This book communicates statistical tools in simple language. The

This book will serve as an excellent field guide to applied toxicology and pharmacology investigators. It is an easy-to-read compilation of topics in applied statistics that might be considered a FAQ or perhaps more properly, a compilation of answers to questions that should be frequently asked, but often are not.

An English translation now joins the Russian and Spanish versions. It is based on the newly revised fifth edition of the German version of the book. The original edition has become very popular as a learning and reference source with easy to follow recipes and cross references for scientists in fields such as engineering, chemistry and the life sciences. Little mathematical background is required of the reader and some important topics, like the logarithm, are dealt with in the preliminaries preceding chapter one. The usefulness of the book as a reference is enhanced by a number of convenient tables and by references to other tables and methods, both in the text and in the bibliography. The English edition contains more material than the German original. I am most grateful to all who have in conversations, letters or reviews suggested improvements in or criticized earlier editions. Comments and suggestions will continue to be welcome. We are especially grateful to Mrs. Dorothy Aeppli of St. Paul, Minnesota, for providing numerous valuable comments during the preparation of the English manuscript. The author and the translator are responsible for any remaining faults and imperfections. I welcome any suggestions for improvement. My greatest personal gratitude goes to the translator, Mr. Zenon Reynaro wych, whose skills have done much to clarify the text, and to Springer-Verlag.

Providing a general guide to statistical methods used in the pharmaceutical industry, and illustrating how to use S-PLUS to implement these methods, the book explains why S-PLUS is a useful software package and discusses the results and implications of each particular application. It is targeted at graduates in biostatistics, statisticians involved in the industry as research scientists, regulators, academics, and/or consultants who want to know more about how to use S-PLUS and learn about other sub-fields within the industry, as well as statisticians in other fields who want to know more about statistical applications in the pharmaceutical industry.

Maintaining a practical perspective, Bioequivalence and Statistics in Clinical Pharmacology, Second Edition explores statistics used in day-to-day clinical pharmacology work. The book is a starting point for those involved in such research and covers the methods needed to design, analyze, and interpret bioequivalence trials; explores when, how, and why these studies are performed as part of drug development; and demonstrates the methods using real world examples. Drawing on knowledge gained directly from working in the pharmaceutical industry, the authors set the stage by describing the general role of statistics. Once the foundation of clinical pharmacology drug development, regulatory applications, and the design and analysis of bioequivalence trials are established, including recent regulatory changes in design and analysis and in particular sample-size adaptation, they move on to related topics in clinical pharmacology involving the use of cross-over designs. These include, but are not limited to, safety studies in Phase I, dose-response trials, drug interaction trials, food-effect and combination trials, QTc and other pharmacodynamic equivalence trials, proof-of-concept trials, dose-proportionality trials, and vaccines trials. This second edition addresses several recent developments in the field, including new chapters on adaptive bioequivalence studies, scaled average bioequivalence testing, and vaccine trials. Purposefully designed to be instantly applicable, Bioequivalence and Statistics in Clinical Pharmacology, Second Edition provides examples of SAS and R code so that the analyses described can be immediately implemented. The authors have made extensive use of the proc mixed procedures available in SAS.