NEW YORK, May 7, 2019 /PRNewswire/ -- Renalytix AI plc (LON: RENX), a developer of artificial intelligence-enabled clinical diagnostics for kidney disease, announced today a collaboration with University Medical Center Groningen (UMCG), Netherlands, to evaluate KidneyIntelX™ across over 3,500 patients with Type II Diabetes. The study will assess how effectively KidneyIntelX identifies patients with fast-progressing kidney disease who would be most likely to benefit from new drug therapies to prevent or slow down their progression to end-stage renal disease and dialysis.
As part of the planned evaluation, the KidneyIntelX test will be performed at multiple time points on over 9,000 patient samples from completed clinical trial biobanks, providing valuable insight into the potential utility of KidneyIntelX as a predictor of response to breakthrough therapies for the treatment of diabetic kidney disease.
Hiddo J.L. Heerspink, Pharm.D., Department of Clinical Pharmacy and Pharmacology, UMCG and lead investigator in the planned evaluation said, "The ability of KidneyIntelX to discriminate fast-progressing kidney disease offers pharma the potential to enrich clinical trials with patients most likely to benefit most from novel drug therapies. Additionally, the potential to predict drug response in these patients is critically important to directing clinical use of new therapies."
KidneyIntelX is designed to diagnose and improve clinical management of patients with Type II diabetes and those of African ancestry with fast-progressing kidney disease, in an effort to curtail the high global costs of Chronic Kidney Disease and end-stage renal disease. In the United States healthcare system alone, these costs are estimated at $114 billion per annum. RenalytixAI expects to commercially launch KidneyIntelX as a laboratory developed test in its CLIA laboratory facilities in the United States in H2 2019.
It is anticipated that initial data from this collaboration will be published in early 2020 and is expected to support prospective revenue-generating clinical trial and clinical diagnostic applications of KidneyIntelX. Better identification and characterization1 of enrolled patients has the potential to reduce the cost and duration of clinical trials and increases the likelihood of reaching successful outcomes.
Expense associated with this project, which is attributable to RenalytixAI, has already been accounted for in existing projections.
