Nearly half of patients with advanced kidney disease are unaware of the severity of their illness, meaning that they often don’t receive treatment until their condition reaches critical levels.
Renalytix AI, which was spun out from British diagnostic and medical device maker EKF Diagnostics, is attempting to lower costs and improve outcomes for patients by using machine learning to pull together disparate data sets and highlight which patients are at most risk for kidney disease.
Early detection or warning signs can led to better treatment plans to head off the course of disease like specialist referrals or starting patients on medications like ACE and SGLT2 inhibitors.
The company recently raised $29 million through an initial public offering on the London Stock Exchange’s Alternative Investment Market in order to boost commercialization and clinical validation efforts for its products.
Renalytix AI CEO James McCullough said the company decided to raise capital through the public markets because of its parent company’s ties to institutions in the United Kingdom, along with the desire for funding within a flat capital structure.
The company’s first product, a diagnostic aid known as KidneyIntelX, is aiming to identify patients at risk for particularly fast progression of kidney disease using medical history data, blood-based bio-markers and other comorbidities like type 2 diabetes.
A Deep-dive Into Specialty Pharma
A specialty drug is a class of prescription medications used to treat complex, chronic or rare medical conditions. Although this classification was originally intended to define the treatment of rare, also termed “orphan” diseases, affecting fewer than 200,000 people in the US, more recently, specialty drugs have emerged as the cornerstone of treatment for chronic and complex diseases such as cancer, autoimmune conditions, diabetes, hepatitis C, and HIV/AIDS.
The technology was initially conceived at Mount Sinai and is being developed through a collaboration with the academic medical center. By working with Mount Sinai, Renalytix is able to access to the health system’s data warehouse, which houses 3 million de-identified patient records, as well as the BioMe Biobank, a 43,000-strong patient biorepository that includes blood samples, genetic information and linked EHR data.
That data set is key as Renalytix looks to validate its technology over a large diverse population set.
“It allows us to perform larger scale rapid validation across a diverse population, which you need because diagnostically you don’t want to overfit for one particular demographic or phenotype,” McCullough said in a phone interview.
The company’s new capital will initially be mainly directed at establishing a multi-center study during the first half of 2019 which can provide the clinical validation for eventual regulatory clearance with the FDA.
Renalytix is also planning on conducting a prospective utility impact study to understand best practices around the diagnostic’s use, how it affects patients and how it fits into existing clinical workflow.
McCullough said the company is hoping to start setting up collaborations with academic medical centers and integrated health systems as initial customers over the next year.
Besides being it’s first customer and research collaborator, Mt. Sinai is also an investor in Renalytix, making a $2 million equity investment when the company went public.
“We’re pleased to be collaborating with RenalytixAI, an emerging industry leader in healthcare AI, on the development of breakthrough prognostics and diagnostics for renal disease,” said Erik Lium, executive vice president of Mount Sinai Innovation Partners, in a statement.
“Renal disease represents an increasing healthcare crisis globally, and early detection and intervention can change the course of this disease.”
Mount Sinai Innovation Partners is a group dedicated to driving licensing and commercialization of scientific developments within the Mount Sinai healthcare system, a role that McCullough characterized as “essential” in the development of Renalytix’s technology.
The company’s second product offering, which is based on research from Mount Sinai professor Barbara Murphy, is directed toward kidney transplant rejection and is meant to help better guide clinical decisionmaking during the transplant process. This can include aspects like the correct use of immunosuppressant drugs and tracking the development of kidney fibrosis in transplant recipients.
Ultimately, McCullough said the company is looking to develop an “algorithmic platform” which can be developed into different use cases like clinical trial enrollment, tracking disease dynamics and helping doctors and pharmaceutical companies better engage in precision medicine around kidney disease.
Renalytix isn’t the only company looking at applying AI computing techniques to diagnostics, although the majority are in medical imaging space. A few examples include Iowa City-based IDx, which is developing a system to diagnose diabetic retinopathy and digital health company Arterys, which is looking to speed up and improve medical imaging.
Google’s DeepMind team is also working on an initiative to use machine learning to help clinicians detect and manage the development of acute kidney injuries in patients.
Photo: HYWARDS, Getty Images
