NEW YORK, July 9, 2019 /PRNewswire/ -- Renalytix AI plc (AIM: RENX), a developer of artificial intelligence-enabled clinical diagnostics for kidney disease, announced today positive interim analysis of data from the KidneyIntelX™ expanded validation study. The results show that in a multi-center cohort of Type 2 diabetes patients, the KidneyIntelX algorithm has met or exceeded required performance targets for identifying those patients experiencing rapid kidney function decline (RKFD)1 and patients who eventually progressed to kidney failure and/or dialysis. The expanded validation program data will support the ongoing regulatory process with the Food and Drug Administration ("FDA") under Breakthrough Device designation, which was announced May 2, 2019.
"We have now completed the complex process of integrating electronic health record data and our proprietary blood biomarker measurements from over 3,000 patients with Type 2 diabetes from three independent, diverse population groups," said Fergus Fleming, Chief Technology Officer of RenalytixAI. "KidneyIntelX continues to demonstrate significant performance improvements over current diagnostic standards and now in a multi-center environment."
Initial performance targets, as outlined in a published study and publicly announced by RenalytixAI on April 1, 2019, illustrated that the KidneyIntelX machine learning algorithm significantly increased the ability to predict which patients went on to experience RKFD versus currently used diagnostic methods. Similarly, in the expanded validation study population, the positive predictive value ("PPV") of KidneyIntelX for RFKD in the Type 2 diabetes population exceeded 50 percent in those patients who were in the highest 15 percent of the risk distribution, and a negative predictive value of greater than 95 percent for patients unlikely to experience RKFD. This compares to a PPV of approximately 30 percent for standard of care methods. In addition, when the performance target was analyzed for the clinical end-point of kidney failure within five years, in the interim results from the expanded validation study the PPV improved further.
Identifying high-risk patients more accurately and earlier can enable optimized clinical management and therapeutic options to slow kidney disease progression and help reduce the overall risk of developing end-stage kidney disease and unplanned or "crash" dialysis. In the United States healthcare system alone, these costs are estimated at $114 billion per year.
The Company announced on January 23, 2019 the initiation of this validation study series to assess blood samples and electronic health records from patients with both Type 2 diabetes and patients of African ancestry. The Company intends to release further data updates in the near term including data relating to the multi-center, African ancestry patient cohort analyzed by KidneyIntelX with the addition of a high-risk inherited gene known as APOL1 into the algorithm.
The Company continues to work closely with FDA under Breakthrough Device designation to test KidneyIntelX in a final independent cohort of subjects that will form the basis for consideration in the ongoing regulatory approval process. RenalytixAI intends to provide further updates on this process in the near term as appropriate.
The KidneyIntelX artificial intelligence-enabled in vitro diagnostic uses a machine learning algorithm to assess results from proprietary blood biomarkers in combination with information from a patient's electronic health record, to generate an RKFD score. The expanded validation study program includes stored patient plasma samples and corresponding electronic health record features collected from three leading academic medical centers: Emory University, the Icahn School of Medicine at Mount Sinai and the University of Pennsylvania. RenalytixAI expects to commercially launch KidneyIntelX in the United States in H2 2019.
About Kidney Disease
Kidney disease is now recognized as a public health epidemic affecting over 850 million people globally. In the United States alone, over 40 million people are classified as having chronic kidney disease, with nearly 50 percent of individuals with advanced (Stage IV) disease 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 emergency room without ever seeing a clinical specialist, such as a nephrologist. Every day 13 patients die in the United States while waiting for a kidney transplant.
RenalytixAI is a developer of artificial intelligence-enabled clinical diagnostic solutions for kidney disease, one of the most common and costly chronic medical conditions globally. The Company's solutions are being designed to make significant improvements in kidney disease diagnosis and prognosis, clinical care, patient stratification for drug clinical trials, and drug target discovery. For more information, visit renalytixai.com.
1. Rapid kidney function decline or RKFD is defined as a change in kidney function (glomerular filtration rate) of at least 5ml/min/1.73m2/year