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Start-Up Cleerly Sees Path Using AI to Prevent Cardiovascular Disease

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New York-based Cleerly has raised $43 million in a series B round and brought in $54 million to date. Cleerly is also one of a growing number of companies at the intersection of artificial intelligence and the cardiovascular sector.

A company standing at the intersection of artificial intelligence, cardiology, and digital health is emerging to help prevent heart attacks. New York-based Cleerly is launching after having raised about $43 million in a series B round.

The company’s technology was born out of research from the Dalio Institute for Cardiovascular Imaging at the New York-Presbyterian Hospital and Weill Cornell Medicine and uses non-invasive coronary (CT) angiography to perform comprehensive coronary artery phenotyping through AI-enabled and FDA-cleared solutions. This technology is based on millions of annotated lab images used to build more than two dozen algorithms capable of quantifying and characterizing the presence, extent, severity, and type of coronary artery disease and other cardiovascular disorders.

“We’re trying to address this fundamental change that we’ve needed in the field of cardiology,” James Min, MD FACC, and founder and CEO of Cleerly, told MD+DI. “For 50 to 70 years, [cardiologists] have been focused on risk factors of disease like cholesterol [etc]… in the asymptomatic population. In the symptomatic population, we’ve been geared toward trying to find blockages in arteries and finding out whether or not that reduces blood flow.”

He added that the problem with focusing on risk factors in the asymptomatic population is because it misses about 70% of the people that are going to have a heart attack.

This is because the risk factors don’t have enough precision to identify and pinpoint individuals who are at risk for a heart attack. In the symptomatic patients who present the chest pain and shortness of breath the way that we’ve been doing it – looking at downstream sequela of the disease rather than the disease itself – the atherosclerosis or the plaque buildup.

Min said, “We wanted to develop a tool that would allow us to homogenize this gap between trying to identify surrogate markers of disease to bridge the measuring of the actual disease itself and then characterize the type of disease that’s present in order to help doctors guide their therapy selections for medications and lifestyle interventions.”

The financing was led by Vensana Capital with participation from LRVHealth, New Leaf Venture Partners, DigiTx Partners, the American College of Cardiology, Cigna Ventures, and existing investors.

“We see Cleerly as the future of how coronary artery disease will be evaluated, and we support the company’s mission to tailor a personalized approach to diagnosis, management and treatment, and to validate all of this with world-class clinical evidence of utility and cost-effectiveness,” said Justin Klein, MD, JD, Managing Partner at Vensana Capital. “With Cleerly’s industry-leading technology platform and inherent value propositions, we believe Cleerly is ideally positioned to inform a new standard of care for how we manage coronary artery disease at scale.”

Proceeds from the series B round will be used scale commercially and for R&D.

“We have developed an architecture within our company that allows us to then really try to do huge quantum changes at scale,” Min said. “I think we’re ready to do that. That’s why we came out from under the radar; raised the round; and will use the majority of that round for commercial scale.”

The company has clearances for two FDA products that are out on the market. Plans call for Cleerly to submit additional applications for products to FDA later this year.

To date, Cleerly has raised about $54 million.

“It’s one thing to extract all of the robustness of the imaging science and the data of the disease genotype – it’s another thing to be able to use that,” Min said. “One of our major focus areas is how do we translate all of this advanced imaging science around disease genotype and then present it to clinicians and patients in a way they can ingest that information and find it to be clinically actionable.”

He added, “If I told you that there was something wrong with your car and just gave you a blueprint of your car and circled it, it doesn’t really help you. You need to somehow understand how that influences the function of your car in the way a non-mechanic can understand. We tried to do the same thing with heart disease for all of the stakeholders in the pathway with a very heavy emphasis on improving patient literacy.”

AI's Expanding Role in Cardiology

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Artificial intelligence has been blossoming in healthcare for quite some time now – especially in the cardiovascular sector. Here are some examples of how AI has been beneficial in the cardiovascular realm.  

FDA recently doled out a pair of clearances for iRhythm Technologies’ wearable cardiac monitor. The firm’s newly cleared AI component allows for expanded training of the algorithm across a larger database, resulting in enhanced diagnostic accuracy and better-quality assurance. With AI, the average rhythm detection sensitivity of iRhythm’s detection algorithm has improved by 21% since its creation in 2010.

Eko also uses AI and machine learning to aid in the fight against heart disease. The Berkley, CA-based company unveiled its Aortic Stenosis (AS) detection algorithm at the American Society of Echocardiography (ASE) 2019 Scientific Sessions. The algorithm was developed and tested in partnership with the Northwestern Medicine Bluhm Cardiovascular Institute.

HeartVista is working to increase the use of CardiacMRI’s. To achieve this goal, the Los Altos, CA-based company has developed the One Click Cardiac Package MRI software, which received FDA clearance. HeartVista’s FDA-cleared Cardiac Package uses AI-assisted software to prescribe the standard cardiac views with just one click, and in as few as 10 seconds. 

Last year, GE Healthcare won FDA clearance for the Vivid Ultra Edition an AI-powered cardiovascular ultrasound system designed to shorten diagnostic exam time and improve measurement consistency.

 

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