Overview

Adaptive design has become an important tool in modern pharmaceutical research and development. Compared to a classic trial design with static features, an adaptive design allows for the modification of the characteristics of ongoing trials based on cumulative information. Adaptive designs increase the probability of success, reduce costs and the time to market, and promote accurate drug delivery to patients. Reflecting the state of the art in adaptive design approaches, Adaptive Design Theory and Implementation Using SAS and R provides a concise, unified presentation of adaptive design theories, uses SAS and R for the design and simulation of adaptive trials, and illustrates how to master different adaptive designs through real-world examples. The book focuses on simple two-stage adaptive designs with sample size re-estimation before moving on to explore more challenging designs and issues that include drop-loser, adaptive dose-funding, biomarker-adaptive, multiple-endpoint adaptive, response-adaptive randomization, and Bayesian adaptive designs. In many of the chapters, the author compares methods and provides practical examples of the designs, including those used in oncology, cardiovascular, and inflammation trials. Equipped with the knowledge of adaptive design presented in this book, you will be able to improve the efficiency of your trial design, thereby reducing the time and cost of drug development.

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9781584889625

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!this book covers many of the different forms of adaptive design. ! The book also provides both SAS and R code to implement the theory, making the implementation of the theory much more accessible to readers. ! Its strength is that it provides an overview on many different types of adaptive designs, with an excellent source of references. ! a useful resource in this relatively new and quickly developing field. ! --Patrick Kelly, Statistics in Medicine, Vol. 29, 2010 This book provides a thorough overview of adaptive designs in clinical trials similar to another book on adaptive designs coauthored by Dr. Chang (Chow and Chang, 2006), but using a more theoretical framework. ! this book is an excellent addition to the biostatistics book series ! . It provides a comprehensive summary of adaptive designs that have been developed, and includes about 400 references in the bibliography. The general theory behind most of the adaptive designs is helpful in understanding their advantages over fixed designs, as well as their potential pitfalls. The SAS and R programs associated with each adaptive design make the book practical as well. --Journal of the American Statistical Association, Vol. 104, No. 487, September 2009 ! this book provides a systematic introduction to adaptive design theory. It also gives trial examples and computing code to help readers construct a comprehensive understanding of adaptive designs. It is certainly a useful guide and reference for academic and industry statisticians alike. --Feifang Hu, Biometrics, June 2009 This easy-to-read book provides the reader with a unified and concise presentation of adaptive design theories, together with computer programs written in SAS and R for the design and simulation of adaptive trials. ! The text, computer programs, and data sets will be of value to both practitioners and students alike. --International Statistical Review, 2008

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Millennium Pharmaceuticals, Cambridge, Massachusetts, USA

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