Description
Book SynopsisThe growing interest in using combination drugs to treat various complex diseases has spawned the development of many novel statistical methodologies. The theoretical development, coupled with advances in statistical computing, makes it possible to apply these emerging statistical methods in in vitro and in vivo drug combination assessments. However, despite these advances, no book has served as a single source of information for statistical methods in drug combination research, nor has there been any guidance for experimental strategies.
Statistical Methods in Drug Combination Studies fills that gap, covering all aspects of drug combination research, from designing in vitro drug combination studies to analyzing clinical trial data. Featuring contributions from researchers in industry, academia, and regulatory agencies, this comprehensive reference:
- Describes statistical models used to characterize doseâresponse patterns of monotherapies and ev
Trade Review
"This book is a welcome addition to the literature and fills a needed niche since last book written on drug synergism was over 15 years ago . . . each chapter presents a different technique for solving common challenges in the development of drug combinations. . . Overall, this book serves as a good reference for both researchers in the field of statistics and drug combination development."
~ Jessica L. Jaynes, California State University, Fullerton
"Investigating drug combinations is a steadily growing area in preclinical and clinical research.As usual, specific statistical methodology is needed to handle these kinds of trials. . . .the book is generallywell structured and the majority of sections actually builds up on and refers to each other. This book provides a good overview on and a good introduction to the topic of statistical methods for drug combination studies, especially regarding the preclinical part."
~ Tim Holland-Letz, German Cancer Research Center Heidelberg
Table of Contents
Drug Combination: Much Promise and Many Hurdles. Drug Combination Synergy. Drug Combination Design Strategies. Confidence Interval for Interaction Index. Two-Stage Response Surface Approaches to Modeling Drug Interaction. A Bayesian Industry Approach to Phase I Combination Trials in Oncology. Statistical Methodology for Evaluating Combination Therapy in Clinical Trials. Challenges and Opportunities in Analysis of Drug Combination Clinical Trial Data. Software and Tools to Analyze Drug Combination Data.
