Beating COVID with Big Data Using his proprietary algorithm, Assistant Professor Josh Lambert is mining a massive data set for FDA-approved drugs that could protect against COVID-19. Josh Lambert knows the power of big data and he is using it to uncover drugs or drug combinations with the potential to protect against COVID-19. Mining a research database that includes up-to-date health insurance claims data for about one-third of Americans, Lambert, PhD, assistant professor and biostatistician for the UC College of Nursing, is looking for COVID-positive patients whose regular medication regimen could have unintentionally protected them from the virus. Results will offer researchers a foundation for future clinical trials. Lambert has completed an analysis on single drugs and looks to publish findings by early 2022. In the second phase of his project, backed by a $250,000 National Institutes of Health grant, Lambert will use a proprietary algorithm and complex statistical models to identify drug combinations with similar protective effects against COVID. It is no small task and this is where Lambert’s expertise and innovation shine.
Winter 2022 | 11
