Synthetic Data Engine to Support NIH's COVID-19 Research-Driving Effort

An artificial intelligence-enabled synthetic data generator that converts clinical data of any kind into equivalent, mock versions that don't expose sensitive patient-identifying details is being put to use as a component of the National Institutes of Health-steered National COVID Cohort Collaborative, or N3C effort. "The NIH's N3C initiative is a result of the urgent need for understanding of COVID both to develop better patient care and understand the impacts on individuals and the health system as a whole," Dr. Michael D. Lesh told Nextgov this week. Lesh--the co-founder and CEO of Syntegra, the company behind the synthetic data engine--shed light on how the tool works, and a new partnership between the business, NIH and the Bill and Melinda Gates Foundation that underpins this fresh endeavor. In June 2020, not long after the novel coronavirus pandemic disrupted nearly every aspect of American life, NIH launched N3C to accelerate COVID-19 research and new medical breakthroughs. The collaborative pursuit, according to a June press release, intends to systematically capture relevant data from participating health care providers across the country, aggregate that data into accessible formats, and in-turn help approved users harness research insights from that harmonized information, via the NCATS N3C Data Enclave.