Invited Session 2
May 7, 2021
10:00 AM – 11:30 PM Pacific Time
Zhenzhen Xu, PhD, is a Senior Mathematical Statistician in the Center for Biologics Evaluation and Research (CBER) at the FDA. Besides leading a team in conducting the statistical review on applications in the field of cell, gene and tissue therapy, she also served as the principal investigator of an awarded FDA Chief Scientist Challenge Grant. Dr. Xu is the FDA CBER representative in the ASA Oncology Working Group and has been actively involved in a number of FDA’s statistical policy and outreach projects.
Over the past ten years, Dr. Xu has authored or co-authored numerous articles in the area of innovative design and analysis of clinical trials, particularly cancer immunotherapy trials and cluster randomized trials. She is the recipient of the 2018 FDA Chief Scientist Publication Award.
Prior to joining the FDA, she spent two years working in the pharmaceutical industry. Dr. Xu holds a Ph.D. in Biostatistics from the University of Michigan and a Master degree in Statistics from Harvard University.
A typical challenge facing the design and analysis of immuno-oncology (IO) trials is the prevalence of nonproportional hazards (NPH) patterns manifested in Kaplan-Meier curves under time-to-event endpoints. The NPH patterns would violate the proportional hazards assumption, and yet conventional design and analysis strategies often ignore such a violation, resulting in underpowered or even falsely negative IO studies. In this article, we explore, both empirically and analytically, the fundamental causes for the occurrence of various NPH patterns and then present novel design and analysis strategies to properly address such issue. Empirical studies demonstrate that the proposed strategies can ensure adequate study power, whereas the conventional alternative leads to a severe power loss. More importantly, the proposed strategies pinpoint a solution to enhance the study efficiency, alleviate the NPH patterns and outline a path towards precision immunotherapy design.
Dr. Siu is a senior medical oncologist at Princess Margaret Cancer Centre since 1998, and has been a Professor of Medicine at the University of Toronto since 2009. She is the Director of the Phase I Program and Co-Director of the Bras and Family Drug Development Program at Princess Margaret Cancer Centre, and holds the BMO Chair in Precision Genomics (2016-2026). She is also the Clinical Lead for the Tumor Immunotherapy Program at Princess Margaret Cancer Centre. Dr. Siu served on the Board of Directors for the American Society of Clinical Oncology (ASCO) for a four-year term (2012-2016). She also served as a member of the Nomination Committee for the American Association for Cancer Research (AACR) (2014-2016) and on the AACR Board of Directors for a three-year term (2017-2020).
Dr. Siu’s major research focus is in the area of new anticancer drug development, particularly with respect to phase I trials and head and neck malignancies. She is the Principal Investigator of a phase I cooperative agreement UM1 award sponsored by the United States National Cancer Institute.
Internationally, Dr. Siu was the recipient of the US NCI Michaele C. Christian Award in Oncology Drug Development in 2010. She has been awarded the TAT 2020 Honorary Award for contributions in the development of anticancer drugs. Locally, she was awarded the University of Toronto Department of Medicine Eaton Scholar Researcher in 2016. She was the ASCO Conquer Cancer Foundation Grants Selection Committee Chair in 2009-10. She was Chairperson of the AACR Education Committee, Co-Chairperson of the Scientific Committee for the 2012 Annual Meeting and Co-Chairperson for the Clinical Trials Committee 2015-2017. Dr. Siu has published over 350 peer-reviewed manuscripts, and she is currently a scientific editor for Cancer Discovery and is on the editorial board for JAMA Oncology, Cell and Cancer Cell.
Phase I clinic trials have evolved over time in their objectives and endpoints that extend beyond safety, tolerability and determination of maximum tolerated dose and recommended phase II dose (RP2D). The design and methodology of phase I trials have also becoming more complex including new dose escalation schemes, the increasing use of dose expansion cohorts to make go-no-go decisions, and the application of pharmacological or biological parameters to determine RP2D especially when dose-limiting toxicity is not anticipated. In this presentation, a risk stratification approach in the phase I evaluation of immuno-oncology agents is discussed; as well as ways to optimize patient selection and dose determination in early phase clinical trials.
Peter F. Thall is the Anise J. Sorrell Professor in the Department of Biostatistics at M.D. Anderson Cancer Center, and an adjunct professor in the Department of Statistics at Rice University. He is a Fellow of the American Statistical Association and the Society for Clinical Trials, and received the Don Owen Award in 2014. Dr. Thall has published over 250 papers and book chapters in the statistical and medical literature, and co-authored the 2016 book Bayesian Designs for Phase I-II Clinical Trials. His latest book, Statistical Remedies for Medical Researchers, is in press and should become available in the summer of 2019. Dr. Thall’s research areas include clinical trial design, precision medicine, Bayesian nonparametric statistics, incorporating expert opinion into Bayesian inference, and dynamic treatment regimes. He has presented over 200 invited talks and 30 short courses, served as an associate editor for Journal of the National Cancer Institute, Statistics in Medicine, Statistics in Biosciences, Clinical Trials, and Biometrics, and is an ASA media expert.
A new design paradigm is presented that encompasses all phases of clinical evaluation of a new drug or biological agent. The design is motivated by the possibility that the dose selected as optimal in a phase I-II trial may not maximize mean survival time. The design hybridizes phase I-II and phase III by allowing the chosen phase I-II dose to be re-optimized based on survival time data from phase I-II patients and the first portion of phase III. The phase I-II/III design uses adaptive randomization in phase I-II, and relies on a mixture model for the survival time distribution as a function of efficacy, toxicity, and dose. A simulation study is presented to evaluate the phase I-II/III design and compare it to the usual approach that conducts phase III using the dose selected in phase I-II. The simulations show that the new design controls Type I error and has generalized power (GP), defined as the probability of correcting selecting a truly optimal dose and concluding that the new agent at that dose is superior to standard therapy, that may be .09 to .74 larger than the GP of the conventional approach. The new design also greatly increases the expected survival time of trial participants
Naitee Ting is a Fellow of American Statistical Association (ASA). He is currently a Director in the Department of Biostatistics and Data Sciences at Boehringer-Ingelheim Pharmaceuticals Inc. (BI). He joined BI in September of 2009, and before joining BI, he was at Pfizer Inc. for 22 years (1987-2009). Naitee received his Ph.D. in 1987 from Colorado State University (major in Statistics). He has an M.S. degree from Mississippi State University (1979, Statistics) and a B.S. degree from College of Chinese Culture (1976, Forestry) at Taipei, Taiwan.
Naitee published articles in Technometrics, Statistics in Medicine, Drug Information Journal, Journal of Statistical Planning and Inference, Journal of Biopharmaceutical Statistics, Biometrical Journal, Statistics and Probability Letters, and Journal of Statistical Computation and Simulation. His book “Dose Finding in Drug Development” was published in 2006 by Springer, and is considered as the leading reference in the field of dose response clinical trials. The book “Fundamental Concepts for New Clinical Trialists”, co-authored with Scott Evans, was published by CRC in 2015. Another book “Phase II Clinical Development of New Drugs”, co-authored with Chen, Ho, and Cappelleri was published in 2017 (Springer). Naitee is an adjunct professor of Columbia University and University of Connecticut. Naitee has been an active member of both the ASA and the International Chinese Statistical Association (ICSA).
Maoxia Zheng is a Senior Director of Biostatistics at Genentech/Roche. Since she joined the company in 2006, Maoxia has been the lead statistician/biostatistics manager for many oncology solid tumor programs, including Avastin in brain tumor, Kadcyla in early breast cancer, and most recently Tecentriq in the GI and GU indications, including the innovative immunotherapy combination platform Morpheus. Maoxia was the Global Development Team Leader for Genentech/Roche Pediatric Oncology programs, and she led the design and implementation of the pediatric oncology platform iMATRIX, which explores multiple pediatric tumor types and multiple molecules based on MOA. Maoxia holds a PhD in Statistics from the University of Chicago.