In response to the US FDA’s Critical Path Initiative, innovative adaptive designs are being used more and more in clinical trials due to their flexibility and efficiency, especially during early phase development. Handbook of Adaptive Designs in Pharmaceutical and Clinical Development provides a comprehensive and unified presentation of the principles and latest statistical methodologies used when modifying trial procedures based on accrued data of ongoing clinical trials. The book also gives a well-balanced summary of current regulatory perspectives.
The first several chapters focus on the fundamental theory behind adaptive trial design, the application of the Bayesian approach to adaptive designs, and the impact of potential population shift due to protocol amendments. The book then presents a variety of statistical methods for group sequential design, classical design, dose-finding trials, Phase I/II and Phase II/III seamless adaptive designs, multiple stage seamless adaptive trial design, adaptive randomization trials, hypotheses-adaptive design, and treatment-adaptive design. It also covers predictive biomarker diagnostics for new drug development, clinical strategies for endpoint selection in translational research, the role of independent data monitoring committees in adaptive clinical trials, the enrichment process in targeted clinical trials for personalized medicine, applications of adaptive designs that use genomic or genetic information, adaptive trial simulation, and the efficiency of adaptive design. The final chapters discuss case studies as well as standard operating procedures for good adaptive practices.
With contributions from leading clinical researchers in the pharmaceutical industry, academia, and regulatory agencies, this handbook offers an up-to-date, complete treatment of the principles and methods of adaptive design and analysis. Along with reviewing recent developments, it examines issues commonly encountered when applying adaptive design methods in clinical trials.
Overview of Adaptive Design Methods in Clinical Trials, Annpey Pong and Shein-Chung Chow
Fundamental Theory of Adaptive Designs with Unplanned Design Change in Clinical Trials with Blinded Data, Qing Liu and George Y.H. Chi
Bayesian Approach for Adaptive Design, Guosheng Yin and Ying Yuan
The Impact of Protocol Amendments in Adaptive Trial Designs, Shein-Chung Chow and Annpey Pong
From Group Sequential to Adaptive Designs, Christopher Jennison and Bruce W. Turnbull
Determining Sample Size for Classical Designs, Simon Kirby and Christy Chuang-Stein
Sample Size Reestimation Design with Applications in Clinical Trials, Lu Cui and Xiaoru Wu
Adaptive Interim Analyses in Clinical Trials, Gernot Wassmer
Classical Dose-Finding Trial, Naitee Ting
Improving Dose-Finding: A Philosophic View, Carl-Fredrik Burman, Frank Miller, and Kiat Wee Wong
Adaptive Dose-Ranging Studies, Marc Vandemeulebroecke, Frank Bretz, José Pinheiro, and Björn Bornkamp
Seamless Phase I/II Designs, Vladimir Dragalin
Phase II/III Seamless Designs, Jeff Maca
Sample Size Estimation/Allocation for Two-Stage Seamless Adaptive Trial Designs, Shein-Chung Chow and Annpey Pong
Optimal Response-Adaptive Randomization for Clinical Trials, Lanju Zhang and William Rosenberger
Hypothesis-Adaptive Design, Gerhard Hommel
Treatment Adaptive Allocations in Randomized Clinical Trials: An Overview, Atanu Biswas and Rahul Bhattacharya
Integration of Predictive Biomarker Diagnostics into Clinical Trials for New Drug Development, Richard Simon
Clinical Strategy for Study Endpoint Selection, Siu Keung Tse, Shein-Chung Chow, and Qingshu Lu
Adaptive Infrastructure, Bill Byrom, Damian McEntegart, and Graham Nicholls
Independent Data Monitoring Committees, Steven Snapinn and Qi Jiang
Targeted Clinical Trials, Jen-Pei Liu
Functional Genome-Wide Association Studies of Longitudinal Traits, Jiangtao Luo, Arthur Berg, Kwangmi Ahn, Kiranmoy Das, Jiahan Li, Zhong Wang, Yao Li, and Rongling Wu
Adaptive Trial Simulation, Mark Chang
Efficiency of Adaptive Designs, Nigel Stallard and Tim Friede
Cases Studies in Adaptive Design, Ning Li, Yonghong Gao, and Shiowjen Lee
Good Practices for Adaptive Clinical Trials, Paul Gallo
Annpey Pong is a manager in the Department of Biostatistics and Research Decision Sciences at Merck Research Laboratories. Dr. Pong is also the associate editor of the Journal of Biopharmaceutical Statistics. She earned her Ph.D. in statistics from Temple University.
Shein-Chung Chow is a professor in the Department of Biostatistics and Bioinformatics at Duke University School of Medicine. Dr. Chow is also a professor of clinical sciences at Duke–National University of Singapore Graduate Medical School and the editor of the Journal of Biopharmaceutical Statistics. He earned his Ph.D. in statistics from the University of Wisconsin–Madison.