RenalytixAI Begins Clinical Validation Of KidneyIntelX™ Built From The Mount Sinai BioMe™ BioBank

Creative Commons License Sinai Desert. Source:  laidianaguevara , no changes made.
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RenalytixAI plc., has announced the start of its clinical validation study for its lead diagnostic, 𝘒𝘪𝘥𝘯𝘦𝘺𝘐𝘯𝘵𝘦𝘭𝘟™. It is designed to diagnose and improve the clinical management of patients with Type II diabetes and those of African ancestry with fast-progressing kidney disease. RenalytixAI expects to commercially launch 𝘒𝘪𝘥𝘯𝘦𝘺𝘐𝘯𝘵𝘦𝘭𝘟™, developed in CLIA compliant RenalytixAI laboratories, to health systems and drug developers in the second half of 2019.

RenalytixAI, founded in 2018, leveraging the Mount Sinai Health System BioMe™ BioBank repository, in New York City, is a developer of artificial intelligence-enabled clinical diagnostic solutions for kidney disease, one of the most common and costly chronic medical conditions globally, with an estimated $114 billion cost of chronic and end-stage kidney disease to the United States healthcare system alone. 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.

𝘒𝘪𝘥𝘯𝘦𝘺𝘐𝘯𝘵𝘦𝘭𝘟™ will use machine learning algorithms to assess the combination of predictive blood-based biomarkers, including sTNFR1, sTNFR2, and KIM1, in combination with electronic health record information. The clinical validation will assess approximately 5,000 patient blood samples and electronic health records sourced from a multi-center collaboration including Emory University and Mount Sinai, and others.

Identification of patients with chronic kidney disease (CKD) who are at risk of, or are experiencing, rapid kidney function decline is challenging. However, the 𝘒𝘪𝘥𝘯𝘦𝘺𝘐𝘯𝘵𝘦𝘭𝘟™ test will significantly improve the identification of these patients in the early stages of CKD. This will improve care and could improve outcomes for these patients through early initiation or escalation of treatment strategies.

“The scale and clinical breadth of this validation provides a rare opportunity to evaluate how AI can aid our ability to detect fast-progressing kidney disease. 𝘒𝘪𝘥𝘯𝘦𝘺𝘐𝘯𝘵𝘦𝘭𝘟™ will give doctors a powerful tool to identify which individuals with kidney disease are likely to progress to end-stage disease and should be treated more aggressively,” … Dr. Michael J. Donovan, Professor of Pathology, Icahn School of Medicine at Mount Sinai, and Chief Medical Officer of RenalytixAI

“𝘒𝘪𝘥𝘯𝘦𝘺𝘐𝘯𝘵𝘦𝘭𝘟™ leverages three proven blood biomarkers validated in dozens of previous studies algorithmically combined with features from large electronic health record databases to identify progressive kidney disease. This approach can greatly improve the identification of patients at highest need of aggressive clinical intervention at any stage to slow or prevent progression to kidney failure.” – Dr. Barbara Murphy, 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, and Chair of the Scientific Advisory Board of RenalytixAI

“I’m pleased that Mount Sinai innovators and critical infrastructure such as BioMe™ BioBank significantly contribute to the advancement of diagnostics and prognostics for treating kidney disease.” … “Through this partnership with Renalytix AI and the combined resources of major medical centers to enhance the study, 𝘒𝘪𝘥𝘯𝘦𝘺𝘐𝘯𝘵𝘦𝘭𝘟™ will address the needs of patients with impaired kidney function that may lead to renal failure.” – Dr. Erik Lium, Executive Vice President of Mount Sinai Innovation Partners

Sources:

  1. https://www.prnewswire.com/news-releases/renalytixai-initiates-clinical-validation-study-of-ai-enabled-kidneyintelx-for-diagnosing-fast-progressing-kidney-disease-300782532.html
  2. https://www.linkedin.com/company/renalytixai/about/
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David is a consultant/medical writer for a number of ongoing healthcare initiatives including for Athla LLC/ HealthLabs, a discovery automation company for Big Data leveraging Big Compute. He has a number of years experience in academic R&D and healthcare related projects including the fields of oncology and immunotherapy.