Characterizing the evolving landscape of COVID-19 therapeutics research with natural language processing

About this Class

Speaker: Tonia Korves, Ph.D. Lead Data Scientist Data and Human-Centered Solutions Innovation Center MITRE Corporation Abstract As COVID-19 research rapidly escalated last year, we quickly built a platform to help biomedical experts track published research about potential therapeutics and vaccines. The platform includes a natural language processing pipeline that identifies scientific documents about SARS-CoV-2 and other viruses, particular drugs, and vaccine types, sorted by stages of research, and a dashboard called the COVID-19 Therapeutic Information Browser, available at covidtib.c19hcc.org. The comprehensive data from this platform enables us to characterize COVID-19 drug research over time and at scale, and potentially draw lessons that can inform future decisions. In this talk, we will present our natural language processing methods, the dashboard, and an analysis of trends in published COVID-19 drug research and clinical trials over the past year. We will also discuss other uses for this data, outstanding challenges, and other potential applications of this approach. Join ZoomGov Meeting https://nih.zoomgov.com/j/1617561452?pwd=bE5YOVgrL2tHbFZidUJQOWZzdGlpZz09 Meeting ID: 161 756 1452 Passcode: 586729 One tap mobile +16692545252,,1617561452#,,,,*586729# US (San Jose) +16468287666,,1617561452#,,,,*586729# US (New York)