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Patients identified with reduced ejection fraction using Eko Health AI were twice as likely to experience heart attacks, heart failure, hospitalization, and all-cause mortality over two years. SAN FRANCISCO, Oct. 2, 2024 /PRNewswire/ -- Eko Health, a pioneer in applying artificial intelligence (AI) for early detection of heart and lung diseases, today announced a new independent study from researchers at Imperial College London (Imperial) that demonstrated how AI can identify patients with significantly higher risk of experiencing major adverse cardiac events (MACE), including heart attacks and heart failure. Researchers used Eko Health's FDA-cleared and UKCA-marked Low Ejection Fraction AI to conduct the study, which reinforced the power of Eko's AI for early detection while also showing its potential to improve cardiovascular care in both clinical and remote settings. Continue Reading Patients identified with reduced ejection fraction using Eko Health AI were twice as likely to experience heart attacks, heart failure, hospitalization, and all-cause mortality over two years. Imperial researchers unveiled three significant studies at the European Society of Cardiology (ESC) Congress 2024, demonstrating: Eko AI Predictive of Major Adverse Cardiac Events and Mortality In a pivotal study involving over 1,000 patients, Eko's AI was shown to predict MACE—including heart attacks, heart failure, and hospitalization—as well as all-cause mortality. Patients flagged by the AI for low ejection fraction were twice as likely to experience MACE compared to those without a positive AI result. These patients also faced a 65% higher mortality rate, even after adjusting for traditional risk factors. "These findings underscore the power of AI-ECG in identifying patients at a significantly higher risk of MACE and mortality, even when traditional markers like left ventricular ejection fraction appear normal. In our study, patients with a positive AI-ECG result had more than double the risk of MACE and a 65% higher risk of mortality. This technology represents a critical advancement in early cardiac risk stratification, offering the potential for more targeted interventions through the simple addition of a single-lead ECG," said Dr. Patrik Bächtiger, one of the co-leads of this research at Imperial. "Notably, the AI identified at-risk patients who had unremarkable results from traditional diagnostic tools, such as echocardiograms. This highlights the technology's ability to detect hidden risk factors, offering healthcare providers a powerful tool for early intervention and improved patient outcomes," said Prof. Nicholas S. Peters, Director of the Health Impact Lab at Imperial. Eko AI Expands Remote Care Capabilities for Heart Failure Patients In another Imperial study presented at ESC 2024, Eko's AI technology demonstrated its potential for remote patient monitoring, particularly for individuals with heart failure. The study found that Eko's AI could accurately predict changes in left ventricular ejection fraction (LVEF), which is a critical indicator of heart function in heart failure patients. By being able to monitor changes in LVEF from home, patients could benefit from earlier interventions and personalized adjustments to their treatment plans, reducing the need for frequent hospital visits and providing peace of mind. Eko AI Demonstrates Scalability for Widespread Clinical Integration Over a 12-week period, the Imperial team successfully integrated Eko's AI across 71 primary care sites in the UK. The study highlighted both the consistent and seamless adoption of the technology by healthcare providers, in addition to its ability to enhance patient care without straining existing healthcare systems. "This demonstrates the technology's practicality and scalability for widespread clinical use, paving the way for broader implementation in routine medical practice," said Dr. Mihir Kelshiker, one of the co-leads of this program at Imperial. Together, these findings further solidify Eko's Low EF AI technology as an important innovation for early detection and management of cardiovascular disease, reinforcing its role as an essential tool in advancing patient care. "This important research from Imperial College London highlights the transformative potential of Eko's AI technology in the fight against heart disease," said Connor Landgraf, co-founder and CEO of Eko Health. "By identifying patients at elevated risk for major cardiac events with a simple, non-invasive test, we are empowering clinicians worldwide to take action earlier, ultimately saving lives and improving care outcomes on a global scale." About Eko Health Eko Health is a leading digital health company advancing how healthcare professionals detect and monitor heart and lung disease with its portfolio of digital stethoscopes, patient and provider software, and AI-powered analysis. Its FDA-cleared platform, used by over 500,000 healthcare professionals worldwide, allows them to detect earlier and with higher accuracy, diagnose with more confidence, manage treatment effectively, and ultimately give their patients the best care possible. Eko Health is headquartered in Emeryville, California, with over $165 million in funding from ARTIS Ventures, DigiTx Partners, Double Point Ventures, EDBI, Highland Capital Partners, LG Technology Ventures, Mayo Clinic, Morningside Technology Ventures Limited, NTTVC, Questa Capital, and others. Media Contact Sam Moore [email protected] SOURCE Eko Health WANT YOUR COMPANY'S NEWS FEATURED ON PRNEWSWIRE.COM? 440k+ Newsrooms & Influencers 9k+ Digital Media Outlets 270k+ Journalists Opted In GET STARTED

EMERYVILLE, Calif., Sept. 12, 2024 /PRNewswire/ -- Eko Health, a pioneer in applying artificial intelligence (AI) for early detection of heart and lung diseases, today announced the appointment of Brent D. Lang, former Chairman and CEO of Vocera Communications, to its Board of Directors. Continue Reading Brent Lang, Former CEO of Vocera, joins Eko Health's Board of Directors Lang brings over three decades of healthcare and technology experience, having led Vocera through rapid growth, a successful IPO, and its $3 billion acquisition by Stryker (NYSE: SYK). His strategic vision and proven leadership will guide Eko as it continues to innovate and expand its platform for early detection of heart and lung diseases for patients worldwide. "Brent's wealth of experience in healthcare technology and company building, combined with a deep commitment to improving patient outcomes, makes him the perfect partner for Eko as we continue to help clinicians diagnose cardiopulmonary diseases earlier and with greater accuracy," said Connor Landgraf, CEO of Eko Health. "We are thrilled to welcome him to our Board." Lang's appointment follows significant milestones for Eko, including surpassing 500,000 healthcare providers on the platform, completing a $41 million Series D, and receiving FDA clearance for the first AI algorithm to aid heart failure detection during routine exams. "It's an honor to join Eko's Board at such a growth inflection point for the company," said Lang. "Eko's technology is revolutionizing the way clinicians detect and manage heart and lung diseases, and I look forward to working with the team to ensure the life-saving platform reaches millions of patients and providers around the world in the coming years." Beyond his distinguished career in healthcare, Lang is also an Olympic gold medalist, having competed with the 1988 USA Men's Swimming team. He continues to support athletes as an independent director and treasurer for the USA Gymnastics Board of Directors. Lang holds an MBA from the Stanford Graduate School of Business and a bachelor's degree in industrial and operations engineering from the University of Michigan. About Eko Health Eko Health is a leading digital health company advancing how healthcare professionals detect and monitor heart and lung disease with its portfolio of digital stethoscopes, patient and provider software, and AI-powered analysis. Its FDA-cleared platform, used by over 500,000 healthcare professionals worldwide, allows them to detect earlier and with higher accuracy, diagnose with more confidence, manage treatment effectively, and ultimately give their patients the best care possible. Eko Health is headquartered in Emeryville, California, with over $165 million in funding from ARTIS Ventures, DigiTx Partners, Double Point Ventures, EDBI, Highland Capital Partners, LG Technology Ventures, Mayo Clinic, Morningside Technology Ventures Limited, NTTVC, Questa Capital, and others. Media Contact Sam Moore [email protected] SOURCE Eko Health WANT YOUR COMPANY'S NEWS FEATURED ON PRNEWSWIRE.COM? 440k+ Newsrooms & Influencers 9k+ Digital Media Outlets 270k+ Journalists Opted In GET STARTED

After years of talking up artificial intelligence’s potential to help make drugs, Recursion will finally bring data to the table — and lots of it. Sometime next month, the Salt Lake City-based biotech will share its first Phase 2 readout, starting a planned stretch of 10 trial readouts in 18 months. The barrage of data will determine if Recursion can avoid the fate of peers that have struggled after falling short with their own lead programs. “It feels like we’re at that moment, people launching things,” Gibson said in an interview earlier this year, comparing the coming data readouts to SpaceX’s early rocket attempts, which included spectacular successes — and plenty of explosions. “There are going to be failures, but ultimately we’re all figuring out how to put the pieces together. And when it starts working in 12 months or 36 months or a few years, it’s going to be an entirely different industry.” Blowups can be expensive, however, and Gibson has savvily padded the company’s balance sheet by raising $216 million in a June secondary offering. And earlier this month, Recursion made an even more dramatic move, reaching an all-stock deal to acquire longtime rival Exscientia, bringing in more drugs, technology and nearly $400 million in cash and equivalents. “They’re one of the most rational actors in the space,” said Joshua Elkington, the founder of Axial, an early-stage biotech venture capitalist firm through which Gibson has invested money. “He knows how to navigate the ups and downs of the market. Ride the waves up, and then consolidate his winnings and not get overextended and blow up.” Despite Gibson’s financial moves, the clinic is a risk he has yet to tangle with. Failure could not just imperil its lead drug programs, but tarnish the company’s (and the AI industry’s) narrative. Even though Recursion’s stock has fallen by about 75% since its 2021 initial public offering, the biotech is still worth $2.2 billion, commanding $1.7 billion in enterprise value. Much of that value could hinge on success in the clinic, investors say. “The company would be trading at cash, period, if it weren’t for AI,” said Shahram Seyedin-Noor, the founder and general partner of Civilization Ventures, a small biotech VC firm. “Even though they’re down 77%, they’re not down 97%. If this data fails, they’ll be down 97%. It’ll be very damaging to them, because the aura will be off.” Seyedin-Noor said he remembers Gibson pitched him before closing Recursion’s Series A in 2016. He didn’t invest in Recursion then, and said he sees limits today in its technology and ability to stay at the fast-moving AI frontier. But he singled out Gibson, a founder with strong execution chops, as a key advantage headed into these readouts — even if results are negative. “I’ve always been impressed by their ability to stay ahead of this tsunami, and to ride the waves as opposed to getting buried under it,” he added. “A moment of truth is coming up for them, but because I believe fundamentally in founder-led companies, I think they will survive even bad data.” Recursion declined to make Gibson or recently-hired R&D head Najat Khan available for an interview. Ironically, the Phase 2 data coming next month — the first proof-of-concept test of Recursion’s platform — is for a drug that wasn’t actually designed with any AI technology. Instead, it dates back more than a decade to Recursion’s founding and Gibson’s PhD research . In the University of Utah lab of Dean Li, now the R&D head of Merck, Gibson used publicly available machine learning tools to search 2,100 compounds. That PhD project found Recursion’s most clinically advanced drug, a decades-old compound called tempol, also called REC-994, which is now being tested by the company in patients with a brain condition called cerebral cavernous malformation, or CCM. CCM is a rare neurological disorder with a wide variety of symptoms. According to the NIH, it’s caused when capillaries in the brain form lesions that can displace brain, brainstem and spinal cord tissue, altering blood flow. The lesions can create clots that cause stroke, seizures, hearing and vision changes, and partial paralysis. Tempol itself hasn’t been FDA-approved, though a handful of companies are researching its use as an antiviral treatment for Covid-19 and ataxia-telangiectasia, for which it’s received orphan designation . In a paper published in Pharmacology Research & Perspectives , Recursion researchers said tempol could potentially treat CCM by reducing oxidative stress in the brain, which contributes to the lesions. Drug development is challenging for CCM because the disease’s symptoms can vary depending on the location of a patient’s lesions. Recursion’s study, which enrolled 62 patients and included a placebo group, will primarily test for the drug’s safety and tolerability. The study is also measuring secondary endpoints to gauge potential signs of efficacy, including three patient-reported scores and two MRI-based metrics looking at brain lesions and brain-bleeding events. Researchers may face a dilemma in defining meaningful improvements, particularly given the disease’s variability. Jefferies analyst Dennis Ding noted any data will be “challenging” to interpret, referencing a natural history study showing 70% of patients reporting no change over a year. “Nobody, including the FDA, understands what’s ‘good’ or a clinically meaningful improvement and on what endpoints,” Ding wrote in a research note earlier this month. Like next month’s Phase 2 data, Recursion’s next two Phase 2 readouts are also testing in-licensed molecules, previously developed by The Ohio State University and Takeda. Results of those rare disease trials are expected in the fourth quarter of 2024 and the first half of 2025. In fact, Recursion’s first internally designed drug, called REC-3964, is only expected to start a Phase 2 study in treating C. diff infections by year’s end. The company hasn’t provided timing for a readout. That’s not to dismiss the company’s work. “When you’re using screening tools and looking at images, I think you’re AI-assisted,” ARTIS Ventures general partner Vasudev Bailey said. “But is it an AI-derived molecule? I don’t know. I think it’s AI-assisted, and that is also awesome. Huge value in it, but let’s be careful in what we call it.” It will likely be some time before there are substantial clinical readouts to test out Recursion’s chops at designing molecules from scratch. But first, it has to survive a much more traditional test of whether its nearer-term pipeline will keep its momentum going. Gibson routinely compares Recursion’s research philosophy to the tech world, naming giants like Netflix, Tesla and Amazon. Extending that analogy, these readouts could determine if the biotech is tech giant Facebook, or tech castoff Friendster. Nearly all agree Recursion correctly bet on an emerging trend in building automated labs and incorporating algorithms into drug R&D. But the question remains if Recursion was too early. On the other hand, positive data could suggest its first-mover advantage is real, and fuel the big bets it’s made partnering with chip giant Nvidia and large language model-based software that can, it hopes, help discover and design drugs. If the earliest version of its platform succeeds, investors can only imagine what the latest iterations may be able to accomplish. The startup landscape has changed dramatically over the past decade, only adding more pressure on imminent clinical results. Shinier, newer objects exist in abundance. Many are starting with transformers and diffusion models — AI architectures that didn’t exist when Recursion started — to develop drugs. Altogether, investors want to see not just a strong platform, but ultimately, a technology that produces promising drugs. “Without that, you’re in trouble,” Bailey said. “What the market has exposed is that you can’t hide behind an AI story alone.”