报告时间：2021年11月9日

               上午10:00-11:00

报告地点：腾讯会议

（会议ID：915 571 927）

报告嘉宾：Ying Ding（丁颖）

报告主题：New Statistical Insights in Precision Medicine: From Targeted Treatment Development to Individualized Treatment Recommendation

报告摘要

New Statistical Insights in Precision Medicine: From Targeted Treatment Development to Individualized Treatment Recommendation

There has been growing interest in discovering precision medicine in modern drug development and biomedical research. One aspect of precision medicine is to develop new therapies that target a subgroup of patients who exhibit enhanced treatment efficacy (as compared to the complement of the subgroup) through randomized controlled trials (RCTs). Another aspect is to tailor existing therapies to individual patients so that each patient can get the most suitable treatment. Motivated by analyzing the Age-Related Eye Disease Study (AREDS) data, a large RCT to study the efficacy of nutritional supplements in delaying the progression of an eye disease, age-related macular degeneration (AMD), this talk will present two recently developed statistical methods to address key issues in both aspects with survival type of outcomes: (1) a novel multiple-testing-based approach to simultaneously identify and infer subgroups with enhanced treatment efficacy in RCTs, and (2) a meta-learner framework to estimate heterogeneous treatment effects so that individualized treatment recommendation can be provided.

个人简介

Dr. Ying Ding is an Associate Professor (tenured) at the Department of Biostatistics, University of Pittsburgh. She received her Ph.D. in Biostatistics from University of Michigan in 2010. Before joining University of Pittsburgh, Dr. Ding worked as a Senior Research Scientist at Eli Lilly and Company for three years, and her responsibilities at Lilly focused on Type II diabetes trials and tailored therapeutics. Dr. Ding’s current research interests include survival analysis, large-scale multi-omics data analysis, multiple comparisons, and precision medicine. Her collaborative research includes cancer clinical trials, disease progression modeling and prediction for aging-related disorders. Dr. Ding has published over 60 manuscripts, one book (as a co-Editor), and four book chapters. Currently, Dr. Ding serves as ASA (American Statistical Association) Pittsburgh Chapter President, ASA Lifetime Data Science (LiDS) Section 2022 Program Chair-Elect, and ASA Statistical Partnership Across Academe, Industry & Government (SPAIG) Committee Vice Chair. She also serves as an Associate Editor for the journal Statistics in Medicine.