Speaker: Krystal Tsosie, Ph.D., M.P.H., Assistant Professor in the School of Life Sciences and Associate Director of the Biodiversity Knowledge Integration Center at at Arizona State University

Abstract: The next discoveries in genomic medicine are likely to be rare or uncovered variation from populations absent in current datasets. Indigenous peoples--who are concerned with data sharing, privacy, broad consent, and group risks of re-identification that are unlikely to be resolved by open data--encounter many dilemmas. How can Indigenous peoples benefit from precision health though they derive lower clinical utitlity and have servere structural barriers to care? How can they contribute to genomic datasets, if the wanted to, and not be subject to data co-optation and commercialization in innovation pathways that are inaccessible to Indigenous peoples? Merely increasing inclusion of Indigenous peoples in genomic datasets is not going to solve the health inequity problem without drastic shifts in benefit- and data equity via Indigenous-led biobanking and machine learning approaches. The era of community-based participatory research has transitiond to Tribally based research in genomics and health.