Through a new partnership unveiled Tuesday, the National Institutes of Health will harness Israeli startup MDClone’s platform to generate computationally-derived synthetic data directly from clinical health data aggregated across the U.S., to underpin and advance research in the fight against COVID-19.
The work is a notable piece of the NIH’s new National COVID Cohort Collaborative, or N3C, effort, through which the federal agency is offering approved users an opportunity to access “different levels” of COVID-19 patients’ clinical data—including a limited data set, a de-identified data set from that LDS and a synthetic data set—to quickly transform captured medical information into insights that can bolster research supporting the nation’s pandemic response.
MDClone confirmed it’s providing the enabling technology for the synthetic workstream in N3C.
“Patient privacy is always a concern when managing healthcare data,” MDClone’s Chief Commercial Officer Josh Rubel told Nextgov via email Wednesday. “In the context of COVID-19, preserving privacy and allowing for research is of value to the NIH and its academic partners. MDClone has the unique ability to securely manage original patient data and convert it to synthetic data, which has the shape and structure of the original data but contains NO actual patient data.”
Information contained in COVID-19 patients’ electronic health records—when securely anonymized and combined in colossal volumes representing many individuals—could inform new and necessary insights needed to combat the ongoing health crisis. To ..
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