Real-world evidence (RWE) has been at the forefront of pharmaceutical innovations. It plays an important role in transforming drug development from a process aimed at meeting regulatory expectations to an operating model that leverages data from disparate sources to aid business, regulatory, and healthcare decision making. Despite its many benefits, there is no single book systematically covering the latest development in the field.

Written specifically for pharmaceutical practitioners, Real-World Evidence in Drug Development and Evaluation, presents a wide range of RWE applications throughout the lifecycle of drug product development. With contributions from experienced researchers in the pharmaceutical industry, the book discusses at length RWE opportunities, challenges, and solutions.

Features

• Provides the first book and a single source of information on RWE in drug development
• Covers a broad array of topics on outcomes- and value-based RWE assessments
• Demonstrates proper Bayesian application and causal inference for real-world data (RWD)
• Presents real-world use cases to illustrate the use of advanced analytics and statistical methods to generate insights
• Offers a balanced discussion of practical RWE issues at hand and technical solutions suitable for practitioners with limited data science expertise

Harry Yang, Ph.D., is Vice President and Head of Biometrics at Fate Therapeutics. He has 25 years of experience across all aspects of drug research and development, from early target discovery, through pre-clinical, clinical, and CMC programs to regulatory approval and post-approval lifecycle management. He has published 7 statistical books, 15 book chapters, and over 90 peer-reviewed papers on diverse scientific and statistical subjects. He is a frequent invited speaker at national and international conferences. He also developed statistical courses and conducted training at the FDA and USP.

Binbing Yu, Ph.D., is Associate Director in the Oncology Statistical Innovation group at AstraZeneca. He serves as the statistical expert across the whole spectrum of drug R&D, including drug discovery, clinical trials, operation and manufacturing, clinical pharmacology, oncology medical affairs and post-marketing surveillance. He obtained his PhD in Statistics from the George Washington University. His primary research interests are clinical trial design and analysis, cancer epidemiology, causal inference in observation studies, PKPD modeling and Bayesian analysis.