Statistics in Drug Research: Methodologies and Recent Developments
Shein-Chung Chow, Jun Shao, Chow ChowBooks.org participates in affiliate programs including Bookshop.org and the Amazon Services LLC Associates Program. We may earn a commission from qualifying purchases made through links on this page, at no additional cost to you.
Overview
Emphasizing the role of good statistical practices (GSP) in drug research and formulation, this book outlines important statistics applications for each stage of pharmaceutical development to ensure the valid design, analysis, and assessment of drug products under investigation and establish the safety and efficacy of pharmaceutical compounds. Coverage include statistical techniques for assay validation and evaluation of drug performance characteristics, testing population/individual bioequivalence and in vitro bioequivalence according to the most recent FDA guidelines, basic considerations for the design and analysis of therapeutic equivalence and noninferiority trials.
Synopsis
Emphasizing the role of good statistical practices (GSP) in drug research and formulation, this book outlines important statistics applications for each stage of pharmaceutical development to ensure the valid design, analysis, and assessment of drug products under investigation and establish the safety and efficacy of pharmaceutical compounds. Coverage include statistical techniques for assay validation and evaluation of drug performance characteristics, testing population/individual bioequivalence and in vitro bioequivalence according to the most recent FDA guidelines, basic considerations for the design and analysis of therapeutic equivalence and noninferiority trials.
Booknews
Chow (Temple U.) and Shao (U. of Wisconsin-Madison) explain the application of statistics used during the various stages of pharmaceutical research and development to demonstrate quality, safety, and efficacy in research and development. Among the contexts they consider are assay and process validation, dissolution testing and profile comparison, stability analysis, and bioavailability and bioequivalence. They draw on such principles as randomization, blinding, substantive evidence, bridging studies, therapeutic equivalence, noninferiority trials, analyzing incomplete data, meta- analysis, quality of life, and medical imaging. Annotation c. Book News, Inc., Portland, OR (booknews.com)