Mount Sinai Health System in New York is collaborating with startup RenalytixAI Plc, to use artificial intelligence solutions to improve kidney disease detection, management and treatment for patients with diabetes and other at-risk patient populations.
The partnership will leverage Mount Sinai’s data warehouse containing over 3 million patient health records and 43,000 patient records in the biobank repository, and using de-identified clinical data, will create an advanced learning system to monitor and flag patients at risk for kidney disease and costly unplanned “crashes” into dialysis.
Approximately 1 million patients cared for in the Mount Sinai Health System are either diagnosed with Type II diabetes or are of African ancestry, two of the major at-risk population segments for kidney disease.
The first product launch is anticipated in the second quarter of 2019 targeting preventable dialysis and chronic kidney disease costs. Additional U.S. based healthcare systems are expected to participate in clinical utility data development and product launch.
“Our ability to apply the power of artificial intelligence against such a deep repository of clinical data in combination with prognostic biomarkers has the potential to change the game for all of our patients with diabetes and other populations at risk for kidney disease,” said Barbara Murphy, M.D., Dean for Clinical Integration and Population Health Management and Chair for the Department of Internal Medicine at the Icahn School of Medicine at Mount Sinai, in a prepared statement. She also chairs the RenalytixAI Scientific Advisory Board.
Established in 2018, RenalytixAI expects to pursue expanded clinical utility trials through collaborations with leading academic medical centers, pharmaceutical and patient advocacy organizations in the United States and Europe this year, followed by submission of product applications for review by the U.S. Food and Drug Administration.
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