This is the first book entirely devoted to the design and analysis of TCM development from a Western perspective, i.e., evidence-based clinical research and development. The book provides not only a comprehensive summary of innovative quantitative methods for developing TCMs but also a useful desk reference for principal investigators involved in personalized medicine. Written by one of the world's most prominent biostatistics researchers, it covers all of the statistical issues encountered at various stages of pharmaceutical/clinical development of a TCM.

Shein-Chung Chow, PhD, is a professor in the Department of Biostatistics and Bioinformatics at Duke University School of Medicine. Dr. Chow is also an adjunct professor at Duke-National University of Singapore Graduate Medical School, an adjunct professor at North Carolina State University, and founding director of the Global Clinical Trial and Research Center in Tianjin, China. He is editor-in-chief of the Journal of Biopharmaceutical Statistics and editor-in-chief of the Chapman & Hall/CRC Biostatistics Series. He is the author or co-author of more than 250 papers and 24 books, including Adaptive Design Methods in Clinical Trials, Second Edition, Handbook of Adaptive Designs in Pharmaceutical and Clinical Development, and Controversial Statistical Issues in Clinical Trials. A fellow of the ASA and member of the ISI, Dr. Chow has received the ASA Chapter Service Recognition Award, the DIA Outstanding Service Award, and the ICSA Extraordinary Achievement Award.

Introduction. Global Pharmaceutical Development. Regulations on Traditional Chinese Medicine. Reference Standards and Product Specifications. QOL-Like Instrument for Evaluation of TCM. Factor Analysis and Principal Component Analysis. Statistical Validation of Chinese Diagnostic Procedures. Statistical Test for Consistency. Statistical Process for Quality Control/Assurance. Bioavailability and Bioequivalence. Population Pharmacokinetics. Experience of Generic Drug Products with Multiple Components. Stability Analysis for Drug Products with Multiple Components. Case Studies. Current Issues and Recent Developments.