The cost for bringing new medicine from discovery to market has nearly doubled in the last decade and has now reached $2.6 billion. There is an urgent need to make drug development less time-consuming and less costly. Innovative trial designs/ analyses such as the Bayesian approach are essential to meet this need. This book will be the first to provide comprehensive coverage of Bayesian applications across the span of drug development, from discovery, to clinical trial, to manufacturing with practical examples.
This book will have a wide appeal to statisticians, scientists, and physicians working in drug development who are motivated to accelerate and streamline the drug development process, as well as students who aspire to work in this field. The advantages of this book are:
Provides motivating, worked, practical case examples with easy to grasp models, technical details, and computational codes to run the analyses
Balances practical examples with best practices on trial simulation and reporting, as well as regulatory perspectives
Chapters written by authors who are individual contributors in their respective topics
Dr. Mani Lakshminarayanan is a researcher and statistical consultant with more than 30 years of experience in the pharmaceutical industry. He has published over 50 articles, technical reports, and book chapters besides serving as a referee for several journals. He has a PhD in Statistics from Southern Methodist University, Dallas, Texas and is a Fellow of the American Statistical Association.
Dr. Fanni Natanegara has over 15 years of pharmaceutical experience and is currently Principal Research Scientist and Group Leader for the Early Phase Neuroscience Statistics team at Eli Lilly and Company. She played a key role in the Advanced Analytics team to provide Bayesian education and statistical consultation at Eli Lilly. Dr. Natanegara is the chair of the cross industry-regulatory-academic DIA BSWG to ensure that Bayesian methods are appropriately utilized for design and analysis throughout the drug-development process.
Rezensionen / Stimmen
'This is not a book that you should breeze through. Sure, you can. However, the reader should read at a pace that is appropriate to extract all the juice out of it. It will not be an exaggeration to say that you can explore the book like a treasure trove. I highly recommended it for those who want to challenge their minds and wouldn't mind rethinking and relearning.'
- Enayet Raheem, International Society for Clinical Biostatistics, 71, June 2021
Reihe
Sprache
Verlagsort
Verlagsgruppe
Zielgruppe
Für höhere Schule und Studium
Maße
Höhe: 234 mm
Breite: 156 mm
Dicke: 29 mm
Gewicht
ISBN-13
978-1-032-17702-1 (9781032177021)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Dr. Mani Lakshminarayanan is a researcher and statistical consultant with more than 30 years of experience in the pharmaceutical industry. He has published over 50 articles, technical reports, and book chapters besides serving as a referee for several journals. He has a Ph.D. in Statistics from Southern Methodist University, Dallas, Texas and is a Fellow of the American Statistical Association.
Dr. Fanni Natanegara has over 15 years of pharmaceutical experience and is currently Principal Research Scientist and Group Leader for the Early Phase Neuroscience Statistics team at Eli Lilly and Company. She played a key role in the Advanced Analytics team to provide Bayesian education and statistical consultation at Eli Lilly. Dr. Natanegara is the chair of the cross industry-regulatory-academic DIA BSWG to ensure that Bayesian methods are appropriately utilized for design and analysis throughout the drug-development process.
Introduction. Building prior. Discover/preclinical phase. Clinical phase. Product development. Regulatory overview of Bayesian application. Computational tools. Special topics.
