RenalytixAI, an NYC-based developer of artificial intelligence-enabled clinical diagnostics for kidney disease, today announced it raised $29 million in funding to support the development and commercialization of two product categories for the early detection of kidney disease and accurate management of kidney transplant rejection. Following the successful completion of its fundraising on November 6, 2018, RenalytixAI started trading publicly on AIM, a market of the London Stock Exchange.
Kidney Disease is a Public Health Crisis
Kidney disease is a public health epidemic and one of the largest healthcare markets globally affecting over 850 million people globally, 40 million people in the U.S.Nearly 50% of individuals with advanced (Stage IV) disease are unaware of the severity of their reduced kidney function. As a result, many patients progress to kidney failure in an unplanned manner, ending up having dialysis in the ER without ever seeing a clinical specialist. In addition, every day 13 patients die in the U.S. while waiting for a kidney transplant.
To identify patients at risk for kidney disease progression and dialysis, RenalytixAI AI-driven platform will draw from distinct sources of health data, including systems containing extensive electronic health records, predictive blood-based biomarkers and other genomic information for analysis by high-performance, learning computer algorithms (machine learning).
In combining these different inputs to develop its products, RenalytixAI has the potential to create novel and powerful models for the prediction of disease progression and drug/therapy response in individual patients.
RenalytixAI Commercialization Collaboration with Mount Sinai
The Company intends to launch its first diagnostic product, KidneyIntelX™, in 2019 in collaboration with the Icahn School of Medicine at Mount Sinai, the medical school of the Mount Sinai Health System (“Mount Sinai”). The partnership announced in June 2018 will leverage MSHS’s massive data warehouse containing over 3,000,000 patient health records and 43,000 patient records in the BioMeTMBioBank 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.
The Company intends to submit KidneyIntelX™ for regulatory review by the U.S. Food and Drug Administration.
“Kidney disease is a major challenge for healthcare systems around the globe,” said Barbara Murphy, MD, dean for Clinical Integration and Population Health, and Murray M. Rosenberg Professor and Chair, Samuel Bronfman Department of Medicine, Icahn School of Medicine at Mount Sinai, board member and chair of the Scientific Advisory Board of RenalytixAI. “We’re responding to this critical unmet need by developing two products that will identify patients at risk for kidney disease progression and dialysis, and categorize the type of risk that will be experienced by kidney transplant patients.”