TITLE: Innovative Designs for Early Phase Dose-Finding Studies
SPEAKER: Sue Jane Wang, FDA, and Yuan Ji University of Chicago
Abstract:
The goal of a first-in-human clinical trial aims at exploring the safety and tolerability of an experimental treatment. Traditionally, fixed rule approaches, such as 3+3, 4+4, are commonly proposed for early phase clinical trials. Statistical literature has shown improved performance characteristics in almost all scenarios explored in the simulation studies when flexibility is built-in prospectively in a fixed rule or when model-based approaches are used. As a result, we are seeing a growing adoption of newer methodologies in early phase trial implementations.
In this tutorial, we plan for three sessions, a methodology and application session, a regulatory consideration and rationale session, and software demo session. At the conclusion of the short course, the participants will learn and apply dose finding methods suitable for their consideration. We note that proper dose selection in early-phase clinical trials will be further experimented in later phase clinical trials aiming for successful pharmaceutical development.
Outline:
- Opening and Overview
- Methodologies and Applications
– Phase 1a dose escalation
– Phase 1b cohort expansion
– Drug combination dose finding
– Immune oncology dose finding with delayed outcomes
– Designs and methods for basket screening trials - Regulatory considerations and rationales
– Brief Overviews on Regulatory Guidance for Early Phase Dose Finding, Cohort Expansion, Adaptive Design, Master Protocol, New Drug Combinations
– Some recent case studies utilizing innovative design strategies in early-phase dose finding studies - Software demo with Q&A
Speaker Bio
Dr. Sue-Jane Wang is Associate Director for Adaptive Design and Pharmacogenomics and the Biostatistics Leader for the Biomarker Qualification Program from Office of Biostatistics, Office of Translational Sciences in Center for Drug Evaluation and Research, U.S. Food and Drug Administration. Other than her current role representing the Office providing services to all 18 medical divisions in CDER/FDA on adaptive designed clinical trials, biomarker associated pharmacogenomics clinical trials and biomarker qualification, Dr. Wang has published over 80 peer-reviewed collaborative research papers in clinical trials, medical genetics, bioinformatics and pharmacogenomics journals and has given more than 200 invited presentations domestic and internationally. Recently, she received Thomas Teal Award for Excellence in Publishing awarded by Drug Information Association and was recognized by the statistical profession and elected a fellow in the American Statistical Association. In the past year, she received the FDA level individual scientific achievement award on Excellence in Analytical Science. She has served as an Editor-in-Chief for Pharmaceutical Statistics. Currently, she is an elected member of International Statistics Institute, an associate editor for Statistics in Medicine and for Statistical Biosciences Journal.
Dr. Yuan Ji is Professor of Biostatistics at The University of Chicago. He is an NIH-funded PI focusing on innovative computational and statistical methods for translational cancer research. Dr. Ji is author of over 140 publications in peer- reviewed journals, conference papers, book chapters, and abstracts, including Nature, Nature Methods, JCO, JNCI, JASA, and Biometrics, across medical and statistical journals. He is the inventor of many innovative Bayesian adaptive designs such as the mTPI and i3+3 designs, which have been widely applied in dose-finding clinical trials worldwide, including trials published on Lancet Oncology, JAMA oncology and JCO. His work on cancer genomics has been reported by a large number of media outlets in 2015. In particular, he led a publication in Nature Methods and invention of a tool called TCGA-Assembler which has been downloaded over 10,000 times worldwide. His recent work on precision medicine was elected as one of the top 10 ideas of the Precision Trials Challenge hosted by The Harvard Business School in 2015. He received Mitchell Prize in 2015 by the International Society for Bayesian Analysis. He is an elected fellow of the American Statistical Association.