Medical Product Safety Evaluation: Biological Models and Statistical Methods

ISBN-13: 9780367571177 / Angielski / Miękka / 2020 / 354 str.

Jie Chen; Joseph Heyse; Tze Leung Lai

Opis

Medical Product Safety Evaluation: Biological Models and Statistical Methods presents cutting-edge biological models and statistical methods that are tailored to specific objectives and data types for safety analysis and benefit-risk assessment. Issues and challenges in the design and analysis of safety studies are covered.

Recenzje

"This book provides comprehensive coverage of the statistical methods for evaluating medical product safety in different stages of development life-cycle: from pre-clinical to clinical, and to post marketing studies. As the evaluation of safety of medical products including drugs, vaccines, devices are becoming increasingly important, more and more novel and complex statistical methods have recently been proposed and used. This book gives a very detailed account of the framework for safety evaluation as well as in-depth descriptions of many advanced statistical methods. As far as I am aware, it is the only book that covers such a broad arrays of topics in safety evaluation. Therefore, this book should be appealing to a very large audience, including graduate students and professional statisticians in industry, government, and academia. I think it can be used as a textbook (as many parts of the materials have been used for short courses or part of graduate degree course) or a reference book for practicing statisticians... Overall, I found the book to be a very important contribution to the scientific community."
~Ivan Chan, AbbVie

Spis treści

Introduction. Safety Databases. Safety Analysis Strategy. Summarizing Safety Data. Preclinical Safety. QT Interval Correction and Prolongation. Safety Boundaries. Sequential Sampling and Hypothesis Testing. Reporting Disproportionality. Bayes and Empirical Bayes Methods. Survival Methods. Safety Meta-Analysis. Methods for Observational Studies. Design of Safety Studies. Confounding and bias. Issues and Challenges in Safety Evaluation

O autorze

Jie Chen is a distinguished scientist at Merck Research Laboratories. He has more than 20 years of experience in biopharmaceutical R&D with research interest in the areas of innovative trial design, data analysis, Bayesian methods, multiregional clinical trials, data mining and machining learning methods, and medical product safety evaluation.

Joseph F. Heyse is a Scientific Assistant Vice President at Merck Research Laboratories, Fellow of the ASA and AAAS, and founding editor of Statistics in Biopharmaceutical Research. He has more than 40 years of experience in pharmaceutical R&D with research interest in safety evaluation and health economics and has more than 70 publications in peer reviewed journals. He is an editor of Statistical Methods in Medical Research.

Tze Leung Lai is the Ray Lyman Wilbur Professor of Statistics, and by courtesy, of Biomedical Data Science and Computational & Mathematical Engineering, and Co-director of the Center for Innovative Study Design at Stanford University. He is a Fellow of the IMS and ASA. His research interest includes sequential experimentation, adaptive design and control, change-point detection, survival analysis, time series and forecasting, multivariate analysis and machine learning, safety evaluation and monitoring. He has published 12 books and 300 articles in peer reviewed journals, and has supervised over 70 PhD theses at Columbia and Stanford Universities.