RenalytixAI Announces Podium Presentation and Publication on “Evaluation of Payer Budget Impact Associated with the Use of Artificial Intelligence in vitro Diagnostic, KidneyIntelX™, to Modify DKD Progression”

NEW YORK, March 24, 2020 /PRNewswire/ -- Renalytix AI plc (LSE: RENX), the AIM-traded developer of clinical grade artificial intelligence in vitro diagnostics for kidney disease, announces that data from a study highlighting the health economic benefits associated with KidneyIntelX™ testing in diabetic kidney disease populations (DKD) will be presented at the National Kidney Foundation Spring Clinical Meeting. An abstract summarizing key results will be published in the peer reviewed journal, the American Journal of Kidney Disease.

National Kidney Foundation Spring Clinical Meeting (March 26, 2020)
Thomas Goss, PharmD, Senior Vice President, Boston Healthcare Associates, will deliver a presentation titled Evaluation of Payer Budget Impact Associated with the Use of Artificial Intelligence in vitro Diagnostic, KidneyIntelX™, to Modify DKD Progression during the Late Breaking Abstract session at the National Kidney Foundation’s Spring Clinical Meeting. The presentation will highlight the significant cost savings associated with the implementation of KidneyIntelX™ in large health care system patient populations in the United States. The presentation is based on a comprehensive economic model developed by Boston Healthcare Associates utilizing peer reviewed clinical data to estimate the costs associated with chronic kidney disease progression in the U.S. The presentation session will be held on Thursday, March 26, 2020 at 4:15 PM ET. A summary of the presentation results will be made available on the Company’s website.

“The results suggest substantial cost savings can be achieved using KidneyIntelX™ to assess CKD patient populations at risk of rapid kidney function decline and/or kidney failure under a number of different scenarios tested,” said Thomas Goss, Senior Vice President at Boston Healthcare Associates Inc.

An abstract summarizing the results will also be published in the May 2020 issue of the American Journal of Kidney Disease (www.ajkd.org), the official journal of the National Kidney Foundation, which is recognized worldwide as a leading source of information devoted to clinical nephrology practice and clinical research.

NKF’s Spring Clinical Meeting gathers more than 3,000 nephrology healthcare professionals from across the United States to learn about the newest developments related to all aspects of nephrology practice. Due to the coronavirus and coronavirus disease (COVID-19) outbreak in the United States the meeting is being held as a live virtual event in 2020. Sessions can be accessed through the conference website.

About Kidney Disease
Kidney disease is now recognized as a public health epidemic affecting over 850 million people globally. The Centers for Disease Control and Prevention (CDC) estimates that 15% of US adults, or 37 million people, currently have chronic kidney disease (CKD). Further, the CDC reports that 9 out of 10 adults with CKD do not know they have it and 1 out of 2 people with very low kidney function who are not on dialysis do not know they have CKD*. Kidney disease is referred to as a “silent killer” because it often has no symptoms and can go undetected until a very advanced stage. Each year kidney disease kills more people than breast and prostate cancer. Every day, 13 patients in the United States die while waiting for a kidney transplant.

About RenalytixAI
RenalytixAI is a developer of clinical grade, artificial intelligence-enabled in vitro diagnostic solutions for kidney disease, one of the most common and costly chronic medical conditions globally. The Company’s products are being designed to make significant improvements in kidney disease diagnosis, transplant management, clinical care, and patient stratification for drug clinical trials. For more information, visit renalytixai.com.

* https://www.cdc.gov/kidneydisease/publications-resources/2019-national-facts.html

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SOURCE RenalytixAI