Bayesian Analysis with R for Drug Development
Chapman & Hall/CRC (Verlag)
978-1-032-17786-1 (ISBN)
Drug development is an iterative process. The recent publications of regulatory guidelines further entail a lifecycle approach. Blending data from disparate sources, the Bayesian approach provides a flexible framework for drug development. Despite its advantages, the uptake of Bayesian methodologies is lagging behind in the field of pharmaceutical development.
Written specifically for pharmaceutical practitioners, Bayesian Analysis with R for Drug Development: Concepts, Algorithms, and Case Studies, describes a wide range of Bayesian applications to problems throughout pre-clinical, clinical, and Chemistry, Manufacturing, and Control (CMC) development. Authored by two seasoned statisticians in the pharmaceutical industry, the book provides detailed Bayesian solutions to a broad array of pharmaceutical problems.
Features
Provides a single source of information on Bayesian statistics for drug development
Covers a wide spectrum of pre-clinical, clinical, and CMC topics
Demonstrates proper Bayesian applications using real-life examples
Includes easy-to-follow R code with Bayesian Markov Chain Monte Carlo performed in both JAGS and Stan Bayesian software platforms
Offers sufficient background for each problem and detailed description of solutions suitable for practitioners with limited Bayesian knowledge
Harry Yang, Ph.D., is Senior Director and Head of Statistical Sciences at AstraZeneca. He has 24 years of experience across all aspects of drug research and development and extensive global regulatory experiences. He has published 6 statistical books, 15 book chapters, and over 90 peer-reviewed papers on diverse scientific and statistical subjects, including 15 joint statistical works with Dr. Novick. He is a frequent invited speaker at national and international conferences. He also developed statistical courses and conducted training at the FDA and USP as well as Peking University.
Steven Novick, Ph.D., is Director of Statistical Sciences at AstraZeneca. He has extensively contributed statistical methods to the biopharmaceutical literature. Novick is a skilled Bayesian computer programmer and is frequently invited to speak at conferences, having developed and taught courses in several areas, including drug-combination analysis and Bayesian methods in clinical areas. Novick served on IPAC-RS and has chaired several national statistical conferences.
Harry Yang is Senior Director and Head of Statistical Sciences at MedImmune. He has 24 years of experience across all aspects of drug research and development and extensive global regulatory experiences. He has published six statistical books, 15 book chapters, and over 90 peer-reviewed papers on diverse scientific and statistical subjects, including 15 joint statistical works with Dr. Novick. Dr. Yang is a frequent invited speaker at national and international conferences. He also developed statistical courses and conducted training at the FDA and USP as well as Peking University. Steven Novick is Director of Statistical Sciences at MedImmune. He has extensively contributed statistical methods to the biopharmaceutical literature. Dr. Novick is a skilled Bayesian computer programmer and is frequently invited to speak at conferences, having developed and taught courses in several areas, including drug-combination analysis and Bayesian methods in clinical areas. He served on IPAC-RS and has chaired several national statistical conferences.
Background. Drug Research and Development. Basics of Bayesian analysis. Bayesian Estimation of Sample Size and Power. Pre-Clinical and Clinical Research. Pre-clinical efficacy study. Futility analysis. Phase 3 Clinical Trial. Chemistry, Manufacturing, and Control. Analytical method. Process Development. Bayesian Approach to Statistical Process Control.
| Erscheinungsdatum | 01.10.2021 |
|---|---|
| Reihe/Serie | Chapman & Hall/CRC Biostatistics Series |
| Zusatzinfo | 36 Tables, black and white |
| Sprache | englisch |
| Maße | 156 x 234 mm |
| Gewicht | 453 g |
| Themenwelt | Mathematik / Informatik ► Mathematik |
| Studium ► Querschnittsbereiche ► Epidemiologie / Med. Biometrie | |
| Naturwissenschaften ► Biologie | |
| Technik | |
| ISBN-10 | 1-032-17786-1 / 1032177861 |
| ISBN-13 | 978-1-032-17786-1 / 9781032177861 |
| Zustand | Neuware |
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