Case Studies in Bayesian Methods for Biopharmaceutical CMC

This book provides applied Bayesian methods for chemistry, manufacturing, and control (CMC) studies in the biopharmaceutical industry, featuring case studies with code and reproducible output. It is written for practicing nonclinical biostatisticians with graduate degrees in statistics and aims to address real-life industry applications.

Format: Hardback
Length: 340 pages
Publication date: 15 December 2022
Publisher: Taylor & Francis Ltd

This comprehensive book delves into the realm of applied Bayesian methods for chemistry, manufacturing, and control (CMC) studies within the biopharmaceutical industry. With a collective effort from industry and academic experts, the book presents a collection of captivating case studies, each serving as a chapter. Spanning a wide range of CMC topics, these case studies encompass stability analysis, analytical method development, specification setting, process development and optimization, process control, experimental design, dissolution testing, and comparability studies.

Each case study is accompanied by detailed code and reproducible output, allowing readers to delve into the analytical processes and obtain tangible results. Written with an academic perspective, this book is specifically tailored to practicing nonclinical biostatisticians, many of whom possess graduate degrees in statistics.

What sets this book apart is its exclusive focus on CMC Bayesian case studies, making it a valuable resource for those seeking to expand their knowledge and expertise in this field. The case studies, drawn from a diverse range of companies across the industry, provide real-world insights and practical applications of Bayesian methods. The authors, who are renowned Bayesian statisticians in the CMC domain, bring their extensive knowledge and experience to the forefront, ensuring a thorough and authoritative exploration of the subject matter.

In addition to the case studies, the book offers an accompanying website featuring code for reproducibility, enabling readers to replicate and validate the analyses presented. This added feature enhances the book's practicality and allows for a deeper understanding of the methodologies employed.

Overall, this book serves as a groundbreaking contribution to the field of applied Bayesian methods in the biopharmaceutical industry. It offers a wealth of knowledge, practical insights, and case studies that will be invaluable to researchers, practitioners, and students alike. By providing a comprehensive and accessible approach to CMC Bayesian analysis, this book empowers individuals to make informed decisions and drive innovation in the pharmaceutical industry.

Weight: 811g
Dimension: 254 x 178 (mm)
ISBN-13: 9781032185484