Fully and Dave talk national synthetic data repositories and what we've learned after collecting and analyzing a year's worth of Covid-19 data. Dr. Payne is the Janet and Bernard Becker Professor and Founding Director of the Institute for Informatics at Washington University in St. Louis. He is also the Associate Dean for the Office of Health Information and Data Science and the Chief Data Scientist for Washington University. He holds appointments as a Professor of General Medical Sciences and Computer Science and Engineering in the Schools of Medicine and Engineering and Applied Sciences, respectively. In this capacity, he is responsible for the creation and oversight of comprehensive biomedical informatics and data science research, training, and support programs aligned with the health and life science enterprise spanning Washington University, BJC Healthcare, and a variety of regional partners. Further, he serves as the director of the Biomedical Informatics components/programs that exist under the auspices of both the CTSA-funded Institute for Clinical and Translational Science (ICTS) and the NCI-funded Siteman Cancer Center at Washington University. He earned both masters and doctoral degrees in Biomedical Informatics at the Columbia University College of Physicians and Surgeons. He is an elected fellow of the American College of Medical Informatics (ACMI), the American Medical Informatics Association (AMIA), and the American Institute for Medical and Biological Engineering (AIMBE), and he also holds leadership appointments on numerous national steering, editorial, and advisory committees, including efforts associated with AMIA, Association for Computing Machinery (ACM), National Cancer Institute (NCI), National Library of Medicine (NLM), and the National Center for Advancing Translational Science (NCATS). His research portfolio broadly focuses upon the areas of translational bioinformatics (TBI) and clinical research informatics (CRI) and includes projects focusing on: 1) knowledge-based approaches to high-throughput hypothesis discovery and data-driven decision making; 2) distributed data management and analysis in support of clinical and translational research; and 3) human-factors and workflow analysis.