31st May 2018 11:30
LONDON (Alliance News) - EKF Diagnostics Holdings PLC on Thursday said its subsidiary Renalytix AI PLC has secured an exclusive license and collaboration contract with the Icahn School of Medicine at Mount Sinai in New York.
Under the deal, the healthcare system at Mount Sinai will be able to use EKF Diagnostics' biomarkers alongside artificial intelligence technology to research patient data and identify which candidates are at the highest risk of progressive diabetic kidney disease.
This disease costs the US healthcare system nearly USD100.0 billion per year, EKF said.
In turn, EKF Diagnostics will get access to Mount Sinai's data warehouse containing over 3.0 million patient health records. This data is expected to help the company to create an advanced learning system to monitor and flag patients at risk for kidney disease.
Point-of-care business EKF said it is currently in the process of spinning out its biomarker technology into separate US entity Renalytix AI Inc. EKF believes this technology has the potential to deliver "significant" upside value for its shareholders.
The company also said it is exploring funding options for its US arm, including equity funding.
Upon completion of the contract later this year, EKF said Mount Sinai has agreed to participate in testing several thousand at-risk patients in a clinical utility study in 2019, at an estimated cost of USD6.0 million.
EKF will then develop and launch the product for early identification and management of kidney disease. The project is subject to funding, the company said. In case of success, the product is expected to appear in the second half of 2019.
"This is a significant partnership for Renalytix AI with one of the largest hospital groups in the United States," said EKF Executive Chairman Julian Baines.
"I believe that this partnership will result in Renalytix AI being leaders in the field of kidney care, alongside Mount Sinai," Baines added.
Shares in EKF Diagnostics were trading 10% higher at 34.70 pence each on Thursday.
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