Bayesian Analysis with R for Drug Development Bayesian Analysis with R for Drug Development
Chapman & Hall/CRC Biostatistics Series

Bayesian Analysis with R for Drug Development

Concepts, Algorithms, and Case Studies

    • $54.99
    • $54.99

Publisher Description

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.

GENRE
Science & Nature
RELEASED
2019
June 26
LANGUAGE
EN
English
LENGTH
326
Pages
PUBLISHER
CRC Press
SELLER
Taylor & Francis Group
SIZE
6.8
MB
Real-World Evidence in Drug Development and Evaluation Real-World Evidence in Drug Development and Evaluation
2021
Biosimilars Biosimilars
2018
Clinical Trial Modernization Clinical Trial Modernization
2025
Emerging Non-Clinical Biostatistics in Biopharmaceutical Development and Manufacturing Emerging Non-Clinical Biostatistics in Biopharmaceutical Development and Manufacturing
2016
Statistics for Biotechnology Process Development Statistics for Biotechnology Process Development
2018
Real-World Evidence in Drug Development and Evaluation Real-World Evidence in Drug Development and Evaluation
2021
Medical Risk Prediction Models Medical Risk Prediction Models
2021
Biomarker Analysis in Clinical Trials with R Biomarker Analysis in Clinical Trials with R
2020
Biosimilar Clinical Development: Scientific Considerations and New Methodologies Biosimilar Clinical Development: Scientific Considerations and New Methodologies
2016
Innovative Methods for Rare Disease Drug Development Innovative Methods for Rare Disease Drug Development
2020
Statistical Design, Monitoring, and Analysis of Clinical Trials Statistical Design, Monitoring, and Analysis of Clinical Trials
2021