报告题目：Adaptive Trial Supply Optimization
报告摘要：As adaptive clinical trials receive growing attention in the past decade, optimal clinical drug supply management is required to address the adaptiveness. In this research, we develop a stochastic inventory control optimization model under participant enrollment uncertainty. The developed model addresses several important aspects in trial supply chains, including drug wastage, resupply policy, trial span, and overall cost. Through numerical studies, we show our model is capable of delivering promising responses to the adaptiveness of size re-estimation and dosage dropping. We also report reasonable cost variation when changing the number of clinical sites and tested dosages.
报告人简介：Professor Nan Kong is Associate Professor in the Weldon School of Biomedical Engineering at Purdue University. He received his PhD in industrial engineering from the University of Pittsburgh in 2006. His research interest lies in population health management and policy, hospital and healthcare systems operations, and big-data driven smart connected health operations research. He has published more than 40 peer-reviewed journal articles. He has received grants from NSF, NIH, AHRQ, and Air Force. He has organized tasks/clusters for several INFORMS meetings, including INFORMS 2016, 2017, INFORMS International 2012, 2015, and INFORMS Healthcare 2013, 2017.