Lost in Translation
Presented by Lee-Jen Wei, Harvard University
Friday, April 14, 2023
12:00 PM ET
AUST 434
Webex Meeting Link
Over the years, the process of designing, monitoring, and analyzing clinical studies for evaluating new treatments has gradually fallen into a fixed pattern. Clinical trialists have sometimes been slow to utilize new methodologies–perhaps to avoid potential delays in the review process for drug approval or manuscript submission. The underlying attitude toward innovation in drug development is in sharp contrast to that in other technologically-driven fields. Scientific investigation is an evolving process. What we have learned from previous studies about methodological shortcomings should help us better plan and analyze future trials. Unfortunately, use of inefficient or inappropriate procedures persists even when better alternatives are available. In this talk, we will explore various methodological issues and potential solutions to them. A goal of the clinical study is to obtain robust, clinically interpretable treatment effect estimate with respect to risk-benefit perspectives at the patient’s level via efficient and reliable quantitative procedures. We will discuss how to achieve this goal via various real trial examples. This talk is related to the so-called “translational statistics and data science.”
Speaker Bio:
L.J. Wei is a professor of Biostatistics at Harvard University. Before joining Harvard, he was a professor at University of Wisconsin, University of Michigan, and George Washington University. His main research interest is in the clinical trial methodology, especially in design, monitoring and analysis of studies. He has developed numerous novel statistical methods which are utilized in practice. He received the prestigious Wald Medal in 2009 from the American Statistical Association for his contribution to clinical trial methodology. He is a fellow of American Statistical Associating and Institute of Mathematical Statistics. In 2014, to honor his mentorship, Harvard School of Public Health established a Wei-family scholarship to support students studying biostatistics. His recent research area is concentrated on translational statistics, the personalize medicine under the risk-benefit paradigm via biomarkers and revitalizing clinical trial methodology. He has more than 200 publications and served on numerous editorial and scientific advisory boards. L. J. Wei has extensive working experience in regulatory science for developing and evaluating new drugs/devices.