Anumana Appoints Kevin Ballinger and Jean-Luc Butel to Board of Directors

News

Company to present four studies, including a late-breaking featured science presentation, and host interactive experiences demonstrating AI’s role in cardiovascular care

CAMBRIDGE, Mass.--(BUSINESS WIRE)--Anumana, a leader in AI-powered cardiovascular diagnostics, will present groundbreaking clinical studies demonstrating how AI applied to electrocardiograms (ECG) can uncover early signs of heart disease and inform clinical care. The company’s late-breaking featured science study, along with three additional accepted abstracts, will be presented at the American Heart Association (AHA) Scientific Sessions 2025, taking place November 7–10 in New Orleans, LA. Anumana will also host several interactive experiences for attendees to explore how AI can be seamlessly integrated into cardiovascular care.

“Together, the studies being presented at AHA continue to expand our growing body of evidence supporting the use of ECG-AI as an everyday clinical procedure,” said Simos Kedikoglou, MD, President and COO of Anumana. “Anumana’s software-as-a-medical-device is grounded in extensive training, retrospective validation, and prospective confirmation in more than 135,000 patients cumulatively. This robust foundation ensures that our AI platform is designed to deliver actionable insights for clinicians and improve patient outcomes.”

Improved Identification of Near-Term Heart Failure Risk in Pooled Cohort Studies Using ECG-AI and PREVENT-HF (Late-Breaking Abstract)  - November 8 at 3:15 p.m. CT (211-213)

Is Parity an Independent Risk Factor for Takotsubo Cardiomyopathy (TTCM)? Using a Novel Research Platform with Large De-identified Electronic Health Record Data to Quantify Parity and its Association with TTCM  - November 9 at 11:30 a.m. CT (Population Science Zone)

Evaluation of a Novel Artificial Intelligence Electrocardiogram Tool for Early Identification of Pulmonary Arterial Hypertension and Chronic Thromboembolic Pulmonary Hypertension  - November 10 at 9:22 a.m. CT (Clinical Science Zone 2‚ Moderated Digital Poster 22)

A Multicenter Study of Detection of Pulmonary Hypertension Based on Point-of-Care 12-Lead ECG Data - November 10 at 9:36 a.m. CT (Clinical Science Zone 2‚ Moderated Digital Poster 22)

Engage with Anumana at AHA 2025—Booth #4719

Attendees are invited to connect with Anumana and experience the company’s AI-powered solutions firsthand:

Interactive Booth Experience: Bring a photo of your 12-lead ECG to discover your “ECG AiGE™”—an informative, data-driven look at how old your ECG says your heart is.

Evening Cocktail Event: AHA attendees can register to join Anumana for a networking reception on Saturday, November 8, at 6 p.m. local time, featuring brief presentations from Anumana’s leaders and nationally recognized experts in cardiac AI (click here for details).

Visit aha2025.anumana.ai for more information about Anumana at AHA.

Anumana is an AI-driven health technology company committed to transforming cardiovascular care. Co-founded by nference and Mayo Clinic, Anumana develops software-as-a-medical-device (SaMD) solutions that apply multimodal AI to support early detection, clinical decision-making, and intraoperative guidance across the continuum of care. The company’s portfolio includes ECG-based algorithms, generative imaging applications, and real-time procedural support tools designed to improve outcomes in both diagnostic and perioperative settings. The company’s FDA-cleared ECG-AI™ LEF algorithm is currently available in the U.S. and eligible for reimbursement as of January 2025. To learn more or schedule a demo, visit ECG-AI LEF. Please visit www.anumana.ai for more information and follow Anumana on LinkedIn and X for company updates.

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Anumana will present groundbreaking clinical studies showing how AI-enhanced ECGs can uncover early signs of heart disease and inform clinical care.

Anumana to Share Latest Advances in ECG-AI at AHA Scientific Sessions 2025

CAMBRIDGE, Mass.--(BUSINESS WIRE)--Anumana Inc., a leader in AI-powered cardiovascular detection algorithms, today announced the appointment of Kevin Ballinger and Jean-Luc Butel to its Board of Directors. In their roles, Ballinger and Butel will provide strategic guidance to Anumana’s leadership team as the company advances its AI-driven capabilities, expands clinical adoption, and scales operations.


“Kevin and Jean-Luc bring a depth of experience that will be an asset to Anumana,” said Maulik Nanavaty, CEO of Anumana. “Their decades of diverse and extensive understanding of healthcare organizations will help guide us as we move into our next phase of growth and expand the commercialization of cardiovascular deep learning AI solutions and product offerings.”


Ballinger is a seasoned healthcare executive with deep experience across the medtech and life sciences sectors. He has been a member of CVRx’s board since September 2024 and most recently served as Chief Executive Officer of Aldevron, LLC, a privately held genomics company acquired by Danaher Corporation in 2021. Prior to Aldevron, Ballinger spent 25 years at Boston Scientific Corporation, including nine years as Executive Vice President and Global President of the Interventional Cardiology division. Ballinger has also served on the boards of Silk Road Medical, Inc. and Shockwave Medical, Inc. He holds a B.S. in mechanical engineering from Michigan Technological University and an M.B.A. from the University of Minnesota’s Carlson School of Management.


Butel is a global healthcare advisor with decades of experience across public institutions and private industry. He currently serves on the boards of Takeda Pharmaceutical Company, Novo Holdings Advisory Group Asia, ICON, JanaCare, Rani Therapeutics, and Diagnostics Development Hub. Previously, Butel was Corporate Vice President and President at Baxter International and Executive Vice President and Group President, International, at Medtronic. He held senior leadership roles at Becton Dickinson and Johnson & Johnson and served as a senior advisor to McKinsey’s Healthcare Practice. He has also served on the boards of Varian Medical Systems, SGInnovate, and Singapore’s Economic Development Board. He was awarded the Singapore Public Service Medal in 2013 and holds a BA in international affairs from The George Washington University and an MBA in international management.

Anumana appoints Kevin Ballinger and Jean-Luc Butel to its Board of Directors.

Simultaneous publication in Journal of the American College of Cardiology demonstrates impact of ECG-AI on heart failure risk assessment

CAMBRIDGE, Mass.--(BUSINESS WIRE)--Anumana, a leader in AI-powered cardiovascular diagnostics, today announced new groundbreaking clinical data presented at the American Heart Association (AHA) Scientific Sessions 2025. Among the studies highlighted was a late-breaking featured science presentation, published simultaneously in the Journal of the American College of Cardiology, showing that AI applied to the electrocardiogram (ECG-AI) can enhance near-term prediction of incident heart failure beyond established clinical risk models. Anumana also has three additional abstracts being presented at the meeting.

The featured study, “Enhanced Prediction of Incident Heart Failure Using Artificial Intelligence-Driven Analysis of 12-Lead Electrocardiogram Waveforms: A HeartShare/AMP-HF Pooled Cohort Analysis,” analyzed data from more than 14,000 participants across three major longitudinal cohorts—the Framingham Heart Study, Multi-Ethnic Study of Atherosclerosis, and Cardiovascular Health Study. Investigators found that integrating Anumana’s ECG-AI with the PREVENT-HF clinical risk equation significantly improved short-term heart failure risk prediction, reclassifying up to 12.5% of individuals into higher-risk categories not identified by clinical factors alone. Participants with positive ECG-AI results were more than 20 times as likely to develop heart failure within three years as those with negative results.

“AI analysis of standard 12-lead electrocardiograms (ECG-AI) allows detection of subtle electrical changes that signal early cardiac dysfunction. The findings from this analysis suggest that ECG-AI can enhance detection of patients at risk for development of HF when added to standard clinical risk assessment with the PREVENT-HF score,” said Akshay S. Desai, MD, MPH, Director of the Heart Failure Disease Management Program, Brigham and Women’s Hospital, and lead study investigator. “The implication is that ECG-AI may help clinicians to identify at-risk patients years before symptoms of HF appear, creating opportunities to start preventive therapy sooner and improve long-term outcomes.”

The study was conducted with the National Heart, Lung, and Blood Institute’s HeartShare/AMP Heart Failure Program using the BioData Catalyst platform, which accelerates reproducible biomedical research to drive scientific advances. The collaboration enabled access to deeply phenotyped, longitudinal cohorts and robust analytic capabilities, supporting a rigorous evaluation of ECG-AI for predicting early heart failure risk.

“This publication marks meaningful progress toward a future where AI helps prevent disease rather than just detecting it,” said Simos Kedikoglou, MD, President and COO of Anumana. “It demonstrates how our ECG-AI LEF algorithm can uncover early signs of heart failure, supporting clinicians in identifying at-risk patients sooner and enabling more proactive care.”

Anumana’s ECG-AI™ LEF algorithm analyzes standard 12-lead ECGs to identify patients with LEF, a key indicator of heart failure. The algorithm achieved an AUC of 0.944, with a sensitivity of 90.2% and specificity of 85.1%, reflecting its strong ability to detect patients at risk for heart failure.

In addition to the featured science, Anumana presented three abstracts highlighting the versatility of AI across cardiovascular conditions:

Multicenter Study of ECG-AI for Pulmonary Hypertension: Across five U.S. health systems, ECG-AI detected pulmonary hypertension with 84% sensitivity and 72% specificity, supporting earlier disease identification.

AI ECG for Early Identification of Pulmonary Arterial and Chronic Thromboembolic Pulmonary Hypertension: This retrospective real-world data analysis found that between initial symptom presentation and diagnosis, more than 74% of patients evaluated had at least one ECG, which was flagged as positive by ECG-AI PH, suggesting potential to reduce diagnostic delays.

Parity and Takotsubo Cardiomyopathy: Researchers developed a novel methodology to determine the lifetime number of pregnancies from electronic health record data to evaluate whether there is an association between parity and risk of Takotsubo cardiomyopathy.

Together, these studies reinforce Anumana’s leadership in translating advanced AI models into clinically meaningful solutions that support earlier detection, targeted intervention, and improved cardiovascular outcomes.

Anumana presents new clinical data at AHA 2025, including a late-breaking study and three additional abstracts.

Anumana Advances AI-Driven Cardiovascular Science with Late-Breaking Heart Failure Study and Multiple Abstracts at AHA 2025

Bioworld: Anumana Inc. has garnered a U.S. FDA breakthrough device designation for its artificial intelligence (AI)-powered electrocardiogram-based algorithm for early identification of cardiac amyloidosis. The ECG-AI detection algorithm is the fourth from the company and its partners to notch breakthrough status.

Anumana’s AI algorithm for cardiac amyloidosis gets FDA breakthrough nod

Based on pioneering research from Mayo Clinic, ECG-AI LEF aims to aid physicians in identifying low ejection fraction in patients at risk of heart failure

CAMBRIDGE, Mass. – Oct. 2, 2023 – Anumana, Inc., a leading AI-driven health technology and nference portfolio company working in collaboration with Mayo Clinic, today announced U.S. Food and Drug Administration (FDA) 510(k) clearance for ECG-AI LEF, a breakthrough artificial intelligence (AI)-powered medical device to detect low ejection fraction (LEF) in patients at risk of heart failure.

LEF, or a weak heart pump, is a significant, at times asymptomatic, and commonly undiagnosed indicator of heart failure.1 The increasing prevalence of heart failure and its associated morbidity, mortality, rehospitalizations, and societal costs2,3 underscores the need to identify and manage patients with LEF.

“Anumana’s ECG-AI LEF fills an important unmet need – the lack of an easily accessible point-of-care, noninvasive, and inexpensive tool to screen for a weak heart pump,” said Paul Friedman, M.D., chair of the Department of Cardiovascular Medicine at Mayo Clinic in Rochester, Minn. and chair of Anumana’s Board of Advisors. “It allows identification of otherwise hidden disease, for which many effective, lifesaving treatments are available – once the presence of the disease is known.”

Developed in partnership with Mayo Clinic, Anumana’s ECG-AI LEF is an innovative software-as-a-medical device (SaMD) designed to screen for LEF in adults at risk for heart failure using data from a routine 12-lead electrocardiogram (ECG), a rapid and common test used in both primary and specialty care. Based on pioneering research from Mayo Clinic,4 the algorithm has been developed utilizing over 100,000 ECG and echocardiogram data pairs from unique patients and has been clinically tested in more than 25 studies involving more than 40,000 patients in the U.S. and internationally.5

Anumana’s ECG-AI LEF was clinically validated in a multi-site, retrospective clinical study of 16,000 racially diverse patients, achieving its primary endpoint with an 84.5% sensitivity and 83.6% specificity.6 ECG-AI LEF achieved an AUROC7 of 0.932, demonstrating an ability to differentiate between LEF and ejection fraction (EF) >40% extremely well (a score ≥0.90 is considered excellent8) and better than most tests currently used in heart failure standard of care.9

Additionally, the EAGLE study, a groundbreaking prospective, randomized, controlled clinical trial by Mayo Clinic evaluated the use of an investigational version of the algorithm in routine clinical care of 22,641 adults by 120 primary care teams from 45 clinics or hospitals, demonstrating that ECG-AI LEF implementation improved clinician’s ability to diagnosis of LEF by 31% versus standard of care without increasing the overall rate of echocardiogram usage.10

ECG-AI LEF is one of Anumana’s broad pipeline of algorithms, including three additional FDA breakthrough device designation algorithms (pulmonary hypertension, cardiac amyloidosis, and hyperkalemia), and is founded on more than six years of pioneering ECG-AI research and development at Mayo Clinic, including nearly 100 peer-reviewed publications to date.

“Anumana was established in 2021 by nference in partnership with Mayo Clinic to unlock the electrical language of the heart through deep learning and improve disease diagnosis and patient care,” said Murali Aravamudan, co-founder and CEO of Anumana and nference. “In the short time of two years we have secured multiple FDA breakthrough device designations, entered multi-year agreements with three pharma partners, successfully established two new medical procedure codes for ECG AI technology, and now achieved our first FDA breakthrough medical device clearance. This is a significant milestone, and we are excited about the next phase of the journey, deploying our technology in the U.S. and globally to empower clinicians and enhance real-world clinical care.”

Anumana is focused on driving fast-paced adoption of the new ECG-AI category, clinically developing and commercializing its novel technologies in healthcare. The newly FDA-cleared ECG-AI LEF can be easily integrated with various ECG information management systems or directly with a patient’s electronic health record via Anumana’s web-based ECG Viewer to support clinical decision-making.

Anumana spearheaded the effort to bring reimbursement to ECG-AI, receiving approval for two Category III CPT® codes from the American Medical Association in 2022. These codes are now available and designed to facilitate the use, adoption, and potential reimbursement of emerging technologies in clinical workflows.

To learn more about ECG-AI LEF and schedule a demo, visit us at ECG-AI LEF.

Anumana is a leading AI-driven health technology company leveraging cutting-edge AI and industry-leading translational science to unlock the electrical language of the heart as never before. The company was founded by nference in partnership with Mayo Clinic to leverage the clinical and technical expertise of both organizations to develop innovative ECG-AI technology from an investigational resource to a clinically meaningful tool for clinicians to advance patient care. Anumana’s software-as-a-medical device (SaMD) solutions aim to detect hidden diseases using ECG-AI algorithms to enhance and improve interventional procedures through real-time AI insights.

Anumana was named one of Fierce MedTech’s Fierce 15 companies for 2022. Follow Anumana at anumana.ai and on LinkedIn and Twitter.

Dr. Friedman and Mayo Clinic have a financial interest in the technology referenced in this press release. Mayo Clinic will use any revenue it receives to support its not-for-profit mission in patient care, education, and research.

1.     Jaskanwal D Sara, Takumi Toya, Riad Taher, Amir Lerman, Bernard J Gersh, Nandan S Anavekar. Asymptomatic Left Ventricle Systolic Dysfunction. European Cardiology Review 2020, 15:e13; https://doi.org/10.15420/ecr.2019.14.

2.     Tsao, C.W., Aday, A.W., Almarzooq Z.I., et al. Heart Disease and Stroke Statistics—2023 Update: A Report From the American Heart Association. Circulation Vol. 147, No. 8; https://www.ahajournals.org/doi/10.1161/CIR.0000000000001123#d330256e1.

3.     Khazanie P, Allen LA. Systematizing Heart Failure Population Health. Heart Fail Clin. 2020 Oct;16(4):457-466. Doi: 10.1016/j.hfc.2020.06.006. Epub 2020 Jul 21. PMID: 32888640; PMCID: PMC7737815; https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7737815/.

4.     Attia, Z.I., Kapa, S., Lopez-Jimenez, F. et al. Screening for cardiac contractile dysfunction using an artificial intelligence–enabled electrocardiogram. Nat Med 25, 70–74 (2019); https://doi.org/10.1038/s41591-018-0240-2.

5.     Anumana data on file and published studies.

6.     Anumana data on file (NCT04963218).

7.     Area Under the Receiving Operating Characteristic curve (AUROC) is a performance metric commonly used to evaluate the ability of a model to distinguish between two classes. An AUROC of 0.5 suggests that the model is no better than random and an AUROC of 1.0 indicates a perfect classifier; https://en.wikipedia.org/wiki/Receiver_operating_characteristic.

8.     Muller MP, Tomlinson G, Marrie TJ, Tang P, McGeer A, Low DE, et al. Can routine laboratory tests discriminate between severe acute respiratory syndrome and other causes of community-acquired pneumonia? Clin Infect Dis. 40:1079–86 (2005); https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8831439/.

9.     Such as NT-proBNP, a common blood test used to help identify LEF today with an AUROC of 0.83; Koschack, J., Scherer, M., Lüers, C. et al. Natriuretic peptide vs. clinical information for diagnosis of left ventricular systolic dysfunction in primary care. BMC Fam Pract 9, 14 (2008); https://doi.org/10.1186/1471-2296-9-14h.

10.   Yao, X., Rushlow, D.R., Inselman, J.W. et al. Artificial intelligence–enabled electrocardiograms for identification of patients with low ejection fraction: a pragmatic, randomized clinical trial. Nat Med 27, 815–819 (2021); https://doi.org/10.1038/s41591-021-01335-4.

Pazanga Health Communications for Anumana

Anumana Receives U.S. FDA 510(k) Clearance for ECG-AI Algorithm to Detect Low Ejection Fraction

CAMBRIDGE, Mass, June 27, 2024 Anumana, a leading AI-driven health technology company and portfolio company of nference, announced a new study that revealed promising results in support of further development of its investigational pulmonary hypertension (PH) algorithm. The study, “An electrocardiogram-based AI algorithm for early detection of pulmonary hypertension,” which was published in the European Respiratory Journal, determined that the algorithm used in the study can detect PH using routine 12-lead electrocardiogram (ECG) data.

PH is a severe, progressive disease where delayed diagnosis is associated with a higher risk of morbidity and mortality.1-5 Despite an increasing number of available treatments for the disease, diagnostic delays – often of more than two years from symptom onset - are common, due to the non-specific symptoms at presentation.6-9  To address this challenge, Anumana, in collaboration with Mayo Clinic, Vanderbilt University Medical Center (VUMC), and Janssen Research & Development, LLC, a Johnson & Johnson company, has developed an Al algorithm designed to detect PH using routinely collected 12-lead ECG data. 

In the newly published study, a convolutional neural network developed for detecting PH was trained and validated using retrospective ECG and either right heart catheterization or echocardiogram data from 39,823 PH-likely patients and 219,404 control patients from Mayo Clinic. The algorithm used in the study was further validated on an additional 6,045 PH-likely patients and 24,256 control patients from VUMC. The algorithm demonstrated promising performance in identifying PH, achieving an area under the receiver operating characteristic curve (AUC) of 0.92 in the diagnostic test set at Mayo Clinic and 0.88 at VUMC, where AUC values range from 0 to 1.10


The PH algorithm received Breakthrough Device designation from the FDA in 2022, and Anumana is continuing to develop the PH algorithm in pursuit of FDA clearance and CE marking. Anumana has previously received FDA 510(k) clearance for its ECG-AI™ LEF algorithm, which helps clinicians detect low ejection fraction in patients at risk of heart failure.

“The promising data from our study suggest that an AI algorithm has the potential to non-invasively detect PH at an early stage using standard ECGs. This finding marks a significant step forward in the care and management of PH patients who often have a long diagnostic journey,” said Dr. Hilary DuBrock, a Mayo Clinic pulmonologist and lead author of the study. 

“These new data underscore the potential of AI algorithms to empower clinicians to uncover diseases earlier, improve patient outcomes and bring us one step closer to our mission to transform cardiac care,” said Maulik Nanavaty, CEO of Anumana. “We’re continuing to work closely with our partners to further clinically validate this much-needed algorithm, which can help clinicians worldwide get PH patients into treatment sooner to address symptoms and prolong life.” 

Mayo Clinic has a financial interest in the technology referenced in this press release. Mayo Clinic will use any revenue it receives to support its not-for-profit mission in patient care, education and research.


Anumana is a leading AI-driven health technology company leveraging cutting-edge AI and industry-leading translational science to unlock the electrical language of the heart as never before. The company was founded by nference in collaboration with Mayo Clinic to leverage the clinical and technical expertise of both organizations to develop innovative ECG-AI technology into a clinically meaningful, medical-grade, and easy to use tool for clinicians to advance patient care. Anumana’s software-as-a-medical device (SaMD) ECG-AI™ solutions aim to detect diseases earlier using standard-of-care ECG readings, enabling clinicians to enhance and improve care with real-time AI insights.   

Anumana’s lead algorithm, ECG-AI™ LEF is now available in the U.S. To learn more about how the algorithm can help clinicians identify low ejection fraction earlier and schedule a demo, visit us at ECG-AI LEF.  

schoinski@pazangahealth.com                                    

(860) 301-5058                              


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Vachiéry JL et al. Eur Respir Rev 2012; 21(123):40–47.

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Didden EM, Lee E, Wyckmans J, et al. Time to diagnosis of pulmonary hypertension and diagnostic burden: A retrospective analysis of nationwide US healthcare data. Pulm Circ 2023: 13(1): e12188.

Armstrong I, Billings C, Kiely DG, et al. The patient experience of pulmonary hypertension: a large cross-sectional study of UK patients. BMC Pulm Med 2019: 19(1): 67.

Maron BA, Humbert M. Finding pulmonary arterial hypertension-switching to offense to mitigate disease burden. JAMA cardiology 2022: 7(4): 369-370.

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Data from Anumana’s New Study Show AI Algorithm Has the Potential to Detect Pulmonary Hypertension Early Using ECG Data

CAMBRIDGE, Mass. – June 25, 2024 – Anumana, a leading AI-driven health technology company and portfolio company of nference, and InfoBionic.Ai, a digital health company specializing in remote cardiac monitoring and diagnostic solutions, today announced a joint research collaboration agreement to develop and commercialize the next generation of remote cardiac care solutions, combining Anumana’s breakthrough ECG-AI™ technology and InfoBionic.Ai’s MoMe ARC® platform. 

By leveraging Anumana's ECG-AI algorithms, developed and validated in collaboration with Mayo Clinic, this initiative aims to enhance InfoBionic.Ai’s MoMe ARC Platform’s ability to detect and intervene in cardiac diseases earlier in the remote patient monitoring setting, with the potential to improve patient outcomes. Anumana and InfoBionic.Ai, both Mayo Clinic portfolio companies,1,2 will continue to work closely with Mayo Clinic under this research agreement.

“It is exciting to see the convergence of our pioneering work in artificial intelligence and remote patient monitoring through this new partnership between Anumana and InfoBionic.Ai,” said Peter Noseworthy, MD, chair of the Heart Rhythm Services Division of Cardiovascular Medicine at Mayo and a board director at InfoBionic.Ai. “By combining InfoBionic.Ai’s remote monitoring solutions with Anumana’s innovative ECG-AI algorithms, including the FDA-cleared algorithm for detecting low ejection fraction (LEF), we aim to equip healthcare providers with the latest cutting-edge tools to detect underlying cardiac conditions earlier, enabling timely intervention and personalized care. It’s a thrilling time for cardiology."

“This collaboration marks an important step in Anumana’s mission to revolutionize cardiac care by enhancing the power of ECG with AI,” said Maulik Nanavaty, CEO of Anumana. “Since the founding of Anumana, our vision has been to elevate the utility of ECG with AI across all the settings in which ECGs are used. By joining forces with InfoBionic.Ai, we are expanding our capabilities from 12 leads in clinical settings to wearable lower-lead ECGs in patients’ homes. We look forward to bringing our AI technology to meet patients and physicians where they are, ultimately benefiting both worldwide.” 

Under the agreement, InfoBionic.Ai and Anumana will develop and integrate Anumana's ECG-AI algorithms, starting with the FDA cleared ECG-AI LEF algorithm, into InfoBionic.Ai's continuous and remote cardiac monitoring platform, allowing the ability to detect LEF and other conditions through the remote monitoring of cardiac activity. The companies will also work together to validate the clinical utility of the integrated solution and seek regulatory clearance to bring this technology to market.

Anumana has received FDA Breakthrough Device Designation for four of its algorithms: low ejection fraction, pulmonary hypertension, cardiac amyloidosis, and hyperkalemia. Its ECG-AI platform won the 2024 MedTech Breakthrough Award for “Best New Technology Solution- Cardiology.” ECG-AI LEF, the company’s FDA-cleared AI algorithm using routine 12-lead ECG data to detect low ejection fraction (LEF), a commonly undiagnosed indicator of heart failure,3 received U.S. FDA clearance in September 2023 and is currently under review in Europe. Anumana has demonstrated that its ECG-AI technology can be adapted to lower-lead ECG devices while maintaining a high degree of performance. A version of the neural network used in Anumana’s FDA cleared ECG-AI LEF algorithm has shown the algorithm to be effective in detecting low ejection fraction using single-lead wearable ECG devices.4 

InfoBionic.Ai’s MoMe ARC is the first and only continuous 6-lead FDA-cleared platform leveraging leading-edge AI analysis and native business intelligence. MoMeARC is a solution that includes a 4-in-1 Gateway device that seamlessly transitions between 2-day in addition to extended Holter tests, Event and MCT modes remotely, streamlining patient monitoring time and minimizing delays.


InfoBionic.Ai’s digital technology has transformed the efficiency and economics of cardiac remote patient monitoring. The company’s vision for its FDA-cleared third-generation platform, the MoMe ARC®, is to remove the roadblocks hindering virtual and remote diagnosis and decision-making. The Massachusetts-based team of seasoned entrepreneurs has had successful careers in healthcare, IT, medical devices, and mobile technology, and brings specific expertise in remote monitoring and cardiology.

Anumana is a leading AI-driven health technology company leveraging cutting-edge AI and industry-leading translational science to unlock the electrical language of the heart as never before. The company was founded by nference in collaboration with Mayo Clinic to leverage the clinical and technical expertise of both organizations to develop innovative ECG-AI technology into a clinically meaningful, medical-grade, and easy to use tool for clinicians to advance patient care. Anumana’s software-as-a-medical device (SaMD) ECG-AI™ solutions aim to detect diseases earlier using standard-of-care ECG readings, enabling clinicians to enhance and improve care with real-time AI insights.  

 Anumana’s lead algorithm, ECG-AI™ LEF is now available in the U.S. To learn more about how the algorithm can help clinicians identify low ejection fraction (LEF) earlier and schedule a demo, visit us at ECG-AI LEF. 

https://newsnetwork.mayoclinic.org/discussion/mayo-clinic-launches-new-technology-platform-ventures-to-revolutionize-diagnostic-medicine/

https://infobionic.ai/press/infobionic-enters-know-how-agreement-mayo-clinic/

Jaskanwal D Sara, Takumi Toya, Riad Taher, Amir Lerman, Bernard J Gersh, Nandan S Anavekar. Asymptomatic Left Ventricle Systolic Dysfunction. European Cardiology Review 2020, 15:e13; https://doi.org/10.15420/ecr.2019.14.

Attia, Z.I., Harmon, D.M., Dugan, J. et al. Prospective evaluation of smartwatch-enabled detection of left ventricular dysfunction. Nat Med 28, 2497–2503 (2022). https://doi.org/10.1038/s41591-022-02053-1


schoinski@pazangahealth.com                                  

Anumana and InfoBionic.Ai Announce Collaboration to Advance AI-powered Remote Cardiac Telemetry Technology for Early Detection of Cardiac Diseases

Coherent Market Insights: The global electrophysiology devices market is expected to exhibit a CAGR of 12.6% during the forecast period due to the increasing organic strategies such as acquisition by the key market players. For instance, in November 2022, anumana, Inc., a health technology company, announced that they had acquired NeuTrace, a medical technology company. This acquisition will help anumana, Inc., for the development of electrophysiology platform.

Global Electrophysiology Devices Market to Surpass US$ 20,069.2 Million by 2030, Says Coherent Market Insights (CMI)

Pharma Times: Artificial intelligence (AI) health technology company, Anumana, will collaborate with Pfizer to develop an artificial intelligence electrocardiogram algorithm (AI-ECG), which enables the early detection of cardiac amyloidosis.

Pfizer and Anumana boost detection of cardiovascular disease

Mobi Health News: Anumana, a joint venture between EHR data company nference and the Mayo Clinic, entered into a multiyear partnership with Pfizer to develop an AI-based tool for the early detection of cardiac amyloidosis. Under the agreement, Anumana will research and pursue FDA De Novo classification for an algorithm that could find signals within electrocardiograms (ECGs) that hint at the condition. The partners also aim to gain regulatory clearance in Europe and Japan.

Pfizer, Anumana team up to develop AI algorithm for cardiac amyloidosis detection

BioSpace: Anumana, Inc., an AI-driven health technology company and portfolio company of nference, has entered into a multi-year agreement with Pfizer Inc. for Anumana to develop an artificial intelligence electrocardiogram algorithm (AI-ECG) designed to enable the early suspicion of cardiac amyloidosis. Anumana will conduct a clinical validation trial and pursue De Novo classification for the algorithm as a Software-as-a-Medical-Device (SaMD) and aims to gain regulatory approval for the algorithm as an SaMD for the detection of cardiac amyloidosis in the U.S., Europe, and Japan.

Anumana and Pfizer Partner to Enable Early Detection of Underdiagnosed Cardiovascular Disease

Developed in collaboration with Janssen and Mayo Clinic, this technology has the potential to aid physicians in earlier detection of pulmonary hypertension, a progressive, life-threatening disease

CAMBRIDGE, Mass., May 24, 2022 – Anumana, Inc., an AI-driven health technology company from nference, Inc., today announced that the U.S. Food & Drug Administration (FDA) has granted Breakthrough Device Designation to its AI-enhanced, ECG-based Pulmonary Hypertension (PH) Early Detection Algorithm. The algorithm is a precise, non-invasive screening tool that addresses an unmet need for earlier diagnosis of patients with pulmonary hypertension, which may otherwise go unnoticed until the disease has advanced, delaying treatment initiation, thereby limiting treatment efficacy and adversely impacting patient outcomes.

FDA Breakthrough Device Designation recognizes novel innovations that demonstrate the potential to provide more effective treatment or diagnosis for life-threatening or irreversibly debilitating diseases and helps to accelerate the regulatory process.

“Electrophysiology waveforms hold immense untapped potential for detecting diseases earlier in their natural history, particularly for conditions in which earlier diagnosis and therapeutic intervention can prolong survival and improve quality of life,” said Venky Soundararajan, PhD, co-founder and Chief Scientific Officer of Anumana and nference. “The FDA's Breakthrough Device Designation for Anumana's PH Early Detection Algorithm is one step forward for the field of ECG AI overall, and more saliently, a giant leap forward for PH patients.”

PH is a progressive, life-threatening disease estimated to affect up to 0.1-1% of the global population.1,2 Due to the non-specific symptoms of the disease, such as shortness of breath, diagnostic delays are common3,4,5, often longer than a year, and have been linked with a higher mortality risk in certain patient subgroups.6,7

Anumana’s AI-enhanced ECG algorithm is designed to easily and safely detect PH at an earlier stage, by leveraging the widespread availability of 12-lead ECGs in primary care, urgent care, and emergency room settings. The AI-enhanced ECG PH Algorithm is enabled by the nference platform, which provides insight from more than 6 million de-identified patient records, including over 8 million ECGs. It was developed through a collaboration between data scientists and physicians at Anumana, Janssen Research & Development, LLC, and Mayo Clinic. Supported by Mayo Clinic Platform, nference launched Anumana in 2021 to develop and commercialize AI-enabled algorithms.

If approved, the early detection algorithm will be offered as Software as a Medical Device (SaMD) that can be downloaded on a physician’s smartphone, tablet, or computer, or accessed via the Cloud through an Electronic Health Record or ECG Information Management System interface. Using a standard 12-lead ECG, the algorithm analyzes the voltage-time data and within seconds provides a prediction of likelihood of PH, reducing the time between initial symptoms and the first evaluation for PH via targeted cardiac imaging. This early detection algorithm is still in development and not yet approved for clinical use.
 
“While therapeutic options for patients with pulmonary hypertension have evolved in recent years, we have not seen significant advancement in reducing the time from symptom onset to diagnosis – and our hypothesis was that data science could help change this,” said Najat Khan, PhD, Chief Data Science Officer and Global Head, Strategy and Operations, Janssen Research & Development, LLC. “We leveraged the power of artificial intelligence, the ingenuity of our data scientists and researchers, and deep collaboration to co-develop this AI-based innovation, with the ultimate goal of helping to improve patient outcomes and transform the trajectory of this devastating disease.”
 
“Early diagnosis of pulmonary hypertension is paramount due to its progression and potential severity,” said Paul Friedman, M.D., chair of the Department of Cardiovascular Medicine at Mayo Clinic. “The addition of AI to a standard ECG – a painless, inexpensive, widely used test that is routinely performed – transforms the ECG into a screening tool for PH, with the opportunity to improve outcomes via early detection by guiding appropriate testing.”

The Pulmonary Hypertension Early Detection Algorithm is the company’s second technology to receive FDA Breakthrough Device Designation. Its low ejection fraction algorithm, developed by Mayo Clinic and licensed by Anumana, received Breakthrough Device Designation in 2019 and Emergency Use Authorization for COVID-19 in 2020. Anumana has a large pipeline of novel algorithms that have been validated by over 30 peer-reviewed publications, including a first of its kind prospective clinical impact study on low ejection fraction that was published in Nature Medicine in 2021. These software solutions are currently in development with each algorithm as a candidate for FDA medical device approval.

About Anumana
Anumana, an AI-driven health technology company and a portfolio company of nference and Mayo Clinic Platform, is harnessing industry-leading AI and translational science to decode the electrocardiogram as never before – as a deep predictive tool and biomarker of disease – empowering care providers to help patients early. Anumana algorithms have been developed, trained, and validated using clinical data from Mayo Clinic, and are undergoing rigorous clinical trial validation. Anumana is developing AI-enabled ECG algorithms for real-world physician use, integrating point-of-care applications into existing workflows, thereby reducing costs, improving outcomes, and enhancing quality of life. Anumana’s AI-enabled tools can diagnose hidden conditions earlier than ever before. Anumana’s algorithms are investigational medical devices and have not yet received regulatory approval or clearance. For more information, visit anumana.ai and follow Anumana on LinkedIn & Twitter.

About nference
Through its powerful technology platform and software, nference is transforming health care by making biomedical knowledge computable. Its partnership with Mayo Clinic has given nference an opportunity to synthesize more than 100 years of institutional knowledge, producing real-world evidence in real time by converting large amounts of data into deep insights to advance discovery and development of diagnostics and therapeutics. nference is headquartered in Cambridge, Mass. Follow nference on LinkedIn and Twitter. Visit us at nference.com.

Andrea Sampson, Sampson Public Relations Group

Wijeratne DT, Lajkosz K, Brogly SB, et al. Increasing Incidence and Prevalence of World Health Organization Groups 1 to 4 Pulmonary Hypertension. Circ Cardiovasc Qual Outcomes. 2018;11(2):e003973. doi:10.1161/CIRCOUTCOMES.117.003973

Hoeper MM, Humbert M, Souza R, et al. A global view of pulmonary hypertension. Lancet Respir Med. 2016;4(4):306-322. doi:10.1016/S2213-2600(15)00543-3

Armstrong I, Billings C, Kiely DG, et al. The patient experience of pulmonary hypertension: a large cross-sectional study of UK patients. BMC Pulm Med 2019: 19: 67.

Brown LM, Chen H, Halpern S, et al. Delay in recognition of pulmonary arterial hypertension: factors identified from the REVEAL Registry. Chest 2011: 140: 19-26.

Rich S, Dantzker DR, Ayres SM, et al. Primary pulmonary hypertension. A national prospective study. Ann Intern Med 1987: 107: 216-223.

Khou V, Anderson JJ, Strange G, et al. Diagnostic delay in pulmonary arterial hypertension: Insights from the Australian and New Zealand pulmonary hypertension registry. Respirol Carlton Vic. 2020;25(8):863-871. doi:10.1111/resp.13768

Klok FA, Barco S, Konstantinides SV, et al. Determinants of diagnostic delay in chronic thromboembolic pulmonary hypertension: results from the European CTEPH Registry. Eur Respir J. 2018;52(6):1801687. doi:10.1183/13993003.01687-2018

FDA Grants Breakthrough Device Designation to Anumana’s ECG Pulmonary Hypertension Early Detection AI Algorithm

Health Evolution: Researchers in Future Healthcare Journal say that while there are claims from organizations that they’ve developed an AI solution that can “diagnose and treat a disease with equal or greater accuracy than human clinicians,” most of them are based on radiological image analysis. A survey of health care leaders found that while 58 percent are using AI in clinical practice, the most common applications are all related to imaging.

Promising AI clinical use cases beyond imaging

Health Evolution: Researchers in Future Healthcare Journal say that while there are claims from organizations that they’ve developed an AI solution that can “diagnose and treat a disease with equal or greater accuracy than human clinicians,” most of them are based on radiological image analysis. A survey of health care leaders found that while 58 percent are using AI in clinical practice, the most common applications are all related to imaging. 

Cardiovascular Business: Anumana, a Massachusetts-based healthcare technology company focused on artificial intelligence (AI), has announced a new multi-year deal with Pfizer focused on improving the identification and diagnosis of cardiac amyloidosis. The groups will work to develop a new AI algorithm capable of identifying signs of cardiac amyloidosis—a significant heart issue that can lead to heart failure—in electrocardiogram (ECG) results.

AI specialists ink deal with Pfizer to target cardiac amyloidosis

IMC Newsdesk: Mayo Clinic has developed health technology to deliver clinical decision support tools, diagnostic insights and care recommendations so clinicians can make faster and more accurate diagnoses and provide continuous care to patients.

Mayo Clinic platform aids clinical decisions

Medtech Dive: Anumana, a health technology startup spun out of Mayo Clinic, entered a multi-year agreement with Pfizer to develop an algorithm to detect cardiac amyloidosis, a serious heart condition. Anumana plans to conduct a clinical trial validating the algorithm and seek de novo clearance in the U.S. It also will seek regulatory approval in Europe and Japan.

Pfizer to partner with Mayo Clinic spinoff on early cardiac amyloidosis detection

AI-driven startup from nference and Mayo Clinic Platform positioned to transform cardiac care

CAMBRIDGE, Mass., March 20, 2023 – Anumana, an AI-driven health technology company and portfolio company of nference, has been named one of Fierce Medtech’s 2022 Fierce 15. This prestigious honor indicates that the two-year-old company is well-positioned to transform cardiac care by leveraging cutting-edge AI and industry-leading translational science to unlock the electrical language of the heart.

“We are honored to be recognized as one of the Medtech Fierce 15 companies for 2022,” said David McMullin, Chief Business Officer of Anumana. “Anumana’s goal is to decode electrical signals from the heart as never before, empowering healthcare providers to improve patient care throughout the cardiac clinical pathway. We are excited to continue developing innovative solutions to the most pressing challenges facing cardiovascular disease diagnosis, treatment, and management.” 

Powered by nference’s nSights data platform, Anumana leverages ECG waveforms from the heart with deep, longitudinal electronic medical records (EMR) data at the patient level, developing state-of-the-art algorithms aimed to help physicians diagnose and treat cardiac disease earlier and more efficiently. Nference, which partners with leading healthcare systems such as Mayo Clinic and Duke Health, makes real-world data available includes multiple data modalities (clinical, molecular, and imaging). 

Anumana’s algorithms for early detection of low ejection fraction, pulmonary hypertension, and hyperkalemia, have received Breakthrough Device Designation from the U.S. FDA. Its robust pipeline of FDA-ready algorithms has been validated with significant prospective clinical evidence in over 75 peer-reviewed publications - including two first-of-their-kind studies published in Nature Medicine and The Lancet. Anumana develops these algorithms in collaboration with the Mayo Clinic Platform and has received sponsorship from strategic pharmaceutical leaders such as Janssen,  Novartis, and Pfizer to further develop and commercialize ECG-AI algorithms.

Anumana’s AI platform utilizes widely accessible screening tools and is built to seamlessly integrate into existing clinical workflows, providing clinicians with real-time insights, accelerating the time to guideline-directed medical therapy, reducing costs, and improving patient outcomes. Anumana seeks regulatory clearances for the platform as software as a medical device (SaMD) and has early milestones for reimbursement in place with two Category III CPT® codes that became effective January 1st, 2023. 

Fierce Medtech’s Fierce 15, launched in 2012, is an annual special report that spotlights the most exciting startups in medtech. This year’s report features the 15 medtech startups that made the biggest splashes in 2022 and aimed to pick the players they think are “the most capable of delivering on their promises to advance the art and science of healthcare.”

Anumana, an AI-driven health technology company and portfolio company of nference, is leveraging cutting-edge AI and industry-leading translational science to unlock the electrical language of the heart as never before. Anumana algorithms have been developed, trained, and validated using clinical data from Mayo Clinic and other leading institutions to detect hidden diseases using AI-ECG algorithms and to enhance and improve interventional procedures through real-time AI insights. Multiple Anumana algorithms have received FDA Breakthrough Device Designation and are currently undergoing rigorous clinical validation. Anumana software devices are designed for real-world physician use, integrating into existing workflows at the point of care to reduce costs and enhance quality of life. Anumana algorithms are investigational medical devices and have not yet received regulatory approval or clearance. For more information, visit anumana.ai and follow Anumana on LinkedIn and Twitter.

Anumana Named to Fierce Medtech’s 2022 Fierce 15

Mayo Clinic News Network: Mayo Clinic announced a new technology platform initiative to deliver the next generation of clinical decision support tools, diagnostic insights and care recommendations to help clinicians make faster and more accurate diagnoses and provide truly continuous care to patients. The Remote Diagnostics and Management Platform (RDMP) connects data with innovative new artificial intelligence (AI) algorithms and augments human decision-making within existing clinical workflows. RDMP enables "event-driven medicine," providing insights in the right context, at the right time.

Mayo Clinic launches new technology platform ventures to revolutionize diagnostic medicine

Mayo Clinic News Network: Two health tech advances are at the heart of a study published in Nature Medicine: an app and backend infrastructure to let patients remotely share smartwatch ECG data with their clinicians in an easy and secure way, and the modification of a proven 12-lead ECG artificial intelligence (AI) algorithm to enable it to run on a single-lead watch ECG recording.

AI transforms smartwatch ECG signals into a diagnostic tool for heart failure

AZO Robotics: The EAGLE—short for ECG AI-Guided Screening for Low Ejection Fraction—trial attempted to establish whether an artificial intelligence (AI) screening tool designed to spot low ejection fraction through EKG data could enhance the diagnosis of this medical disorder in regular practice. The results of the study have been published in the Nature Medicine journal.

New Study Demonstrates Value of AI-Enabled EKG Algorithm in Routine Practice

EurekAlert: Heart disease can take a number of forms, but some types of heart disease, such as asymptomatic low ejection fraction, can be hard to recognize, especially in the early stages when treatment would be most effective. The ECG AI-Guided Screening for Low Ejection Fraction, or EAGLE, trial set out to determine whether an artificial intelligence (AI) screening tool developed to detect low ejection fraction using data from an EKG could improve the diagnosis of this condition in routine practice. Study findings are published in Nature Medicine.

Trial demonstrates early AI-guided detection of heart disease in routine practice

HIT Consultant: Anumana, an AI-driven health technology company and portfolio company of nference, today announced a multi-year agreement with Pfizer for Anumana to develop an investigational artificial intelligence electrocardiogram algorithm (AI-ECG) designed to enable the early identification of patients who may be at risk of cardiac amyloidosis.

Anumana & Pfizer Partner on Amyloidosis AI-ECG Algorithm Development

Health Leaders: A start-up from the Mayo Clinic orbit is partnering with Pfizer to develop an AI-enhanced ECG that can detect cardiac amyloidosis, a progressive disease that's difficult to diagnose early.

New Project Trains AI on a Hard-to-Diagnose Cardiac Issue

JHC Online: Mayo Clinic has announced a new technology platform initiative to new clinical decision support tools, diagnostic insights, and care recommendations to help clinicians make faster and more accurate diagnoses and provide continuous care to patients.

Mayo Clinic launches two new tech companies

DotMed: Mayo Clinic has launched two new companies to support its new technology initiative, the Remote Diagnostics and Management Platform. The solution applies artificial intelligence to derive insights from data and uses these findings to support human decision-making within existing clinical workflows. It supports “event-driven medicine” by aiming to provide insights in the right context at the right time.

Mayo Clinic launches two new companies

Medtech Insight: The Minnesota-based health care system announced the formation of Anumana Inc. to commercialize artificial intelligence-enabled algorithms and Lucem Health to curate data collected from remote monitoring devices.

Mayo Clinic Launches Two Companies To Support New Remote Monitoring Initiative

Health Transformer: Anumana, a startup designing neural network algorithms to enable early detection and accelerate treatment of heart disease, raised $25.7M led by founders nference and Mayo Clinic, with participation from Matrix Capital Management, Matrix Partners, and NTTVC.

StartUp Health Insights: Virta & 1Doc3 Close Rounds, Over $1.4B Raised This Week

Health Transformer: Anumana, a startup designing neural network algorithms to enable early detection and accelerate treatment of heart disease, raised $25.7M led by founders nference and Mayo Clinic, with participation from Matrix Capital Management, Matrix Partners, and NTTVC. 

Pharma File: Anumana has announced the FDA had granted breakthrough Device Designation to its AI-enhanced ECG-based Pulmonary Hypertension (PH) Early Detection Algorithm. Breakthrough Device Designations recognise novel innovations demonstrating potential to provide more effective treatment, or diagnosis for life-threatening or irreversibly debilitating diseases. The designation helps to accelerate the regulatory process.

FDA grants Breakthrough Device Designation to pulmonary hypertension early detection AI

Med City News: Mayo Clinic shared results of a study showing that an AI tool developed by the system could be used to improve diagnosis of low ejection fraction, a type of heart disease. It's part of a broader push by Mayo Clinic to commercialize AI-based diagnostic tools, starting with spinout company Anumana.

Mayo Clinic finds algorithm helped clinicians detect heart disease, as part of broader AI diagnostics push

Medical Xpress: Patients with migraine with aura (MwA) have significantly higher artificial intelligence-enabled electrocardiogram (AI-ECG) atrial fibrillation (AF) prediction model output, according to a study from Mayo Clinic published online June 8 in Headache. The study used Mayo Clinic developed algorithm for detecting atrial fibrillation, which is now licensed to Anumana.

Migraine with aura identified as independent risk factor for A-fib

Medical Xpress: Patients with migraine with aura (MwA) have significantly higher artificial intelligence-enabled electrocardiogram (AI-ECG) atrial fibrillation (AF) prediction model output, according to a study from Mayo Clinic published online June 8 in Headache. The study used Mayo Clinic developed algorithm for detecting atrial fibrillation, which is now licensed to Anumana. 

Medical Product Outsourcing: Artificial intelligence (AI)-driven healthtech company, Anumana has received U.S. Food and Drug Administration (FDA) Breakthrough Device Designation for its AI-enhanced, ECG-based pulmonary hypertension (PH) early detection algorithm. The precise and non-invasive screening tool supports earlier PH diagnosis, which may otherwise not be noticed until the disease has advanced, delaying treatment and limiting efficacy while adversely impacting outcomes.

Anumana's ECG Pulmonary Hypertension AI Algorithm Gains Breakthrough Status

Mass Device: Mayo Clinic announced that it is introducing a new technology platform to support two new companies it has launched. Rochester, Minn.–based Mayo Clinic’s Remote Diagnostics & Management Platform (RDMP) is designed to connect data with new AI algorithms and augment human decision-making within existing clinical workflows, according to a news release.

Mayo Clinic helps launch two new companies for improved diagnostics

Innovator News: Mayo Clinic announced a new technology platform and launched two new companies April 14 that promise to improve doctors’ ability to spot disease early by connecting data from remote medical devices with AI-enabled algorithms. The first target is the heart.

New Ventures To Use AI To Target Heart Disease

Modern Healthcare: Mayo Clinic announced a new technology platform initiative to deliver the next generation of clinical decision support tools, diagnostic insights and care recommendations to help clinicians make faster and more accurate diagnoses and provide truly continuous care to patients. The Remote Diagnostics and Management Platform (RDMP) connects data with innovative new artificial intelligence (AI) algorithms and augments human decision-making within existing clinical workflows. RDMP enables "event-driven medicine," providing insights in the right context, at the right time.

Midwest providers eye new financial opportunities

Companies initiate research agreement supporting development of new AI-ECG algorithm to help identify patients who may be at risk of cardiac amyloidosis

CAMBRIDGE, Mass. – Dec. 15, 2022 – Anumana, Inc., an AI-driven health technology company and portfolio company of nference, has entered into a multi-year agreement with Pfizer, Inc. for Anumana to develop an artificial intelligence electrocardiogram algorithm (AI-ECG) designed to enable the early suspicion of cardiac amyloidosis. Anumana will conduct a clinical validation trial and pursue De Novo classification for the algorithm as a Software-as-a-Medical-Device (SaMD) and aims to gain regulatory approval for the algorithm as an SaMD for the detection of cardiac amyloidosis in the U.S., Europe and Japan. 

Cardiac amyloidosis is a serious, progressive, and underdiagnosed rare disease that leads to heart failure.1 In patients with cardiac amyloidosis, the heart walls become stiff, making it difficult for the left ventricle to properly relax and fill with blood, while at the same time hampering its ability to squeeze and pump blood out of the heart. Symptoms and comorbidities associated with cardiac amyloidosis, such as shortness of breath, knee pain, bilateral carpal tunnel syndrome, kidney disease, and gastrointestinal issues, can vary and seem unrelated, making diagnosis difficult.2,3 

“The challenge in diagnosing cardiac amyloidosis can prevent patients from getting treatment while the disease continues to progress,” said David McMullin, chief business officer of Anumana. “We believe this collaboration will demonstrate the power of Anumana’s AI-ECG algorithms to help clinicians intervene earlier, giving them greater ability to improve patient outcomes and prolong lives.”

The research agreement with Pfizer will help deepen Anumana’s efforts to implement AI-enabled early detection software that can reveal signals from ECGs that humans cannot interpret. The ubiquitous nature of the painless, non-invasive 100-year-old ECG test gives AI-ECG algorithms the potential to reach a larger number of patients earlier. 

“AI-ECG solutions alert clinicians to humanly imperceptible patterns in ECG signals, providing an early warning for serious occult or impending disease,” said Paul Friedman, M.D., Chair of the Department of Cardiovascular Medicine at Mayo Clinic and Chair of Anumana’s Mayo Clinic Board of Advisors. “This stands to improve the lives of people with cardiac amyloidosis by improving the speed of triage and care of this group.”

Anumana was founded in 2021 in collaboration with the Mayo Clinic Platform. Anumana has licensed Mayo Clinic AI-ECG algorithms for low ejection fraction, pulmonary hypertension, and hyperkalemia, all of which have received Breakthrough Device Designation from the U.S. FDA. These algorithms have been validated by over 75 peer-reviewed publications, including a first of its kind prospective clinical impact study on low ventricular ejection fraction that was published in Nature Medicine in 2021, and another first of its kind batch enrolled prospective clinical impact study that demonstrated the effectiveness of AI-ECG to screen for undetected atrial fibrillation in normal sinus rhythm that was published in The Lancet in 2022.

Anumana, an AI-driven health technology company and portfolio company of nference, is harnessing industry-leading AI and translational science to unlock the electrical language of the heart as never before. Anumana algorithms have been developed, trained, and validated using clinical data from Mayo Clinic and other leading institutions to detect hidden diseases using AI-ECG algorithms and to enhance and improve interventional procedures through real-time AI techniques. Multiple Anumana algorithms have received FDA Breakthrough Device Designation and are currently undergoing rigorous clinical trial validation. Anumana software devices are designed for real-world physician use, integrating into existing workflows at the point of care to reduce costs and enhance quality of life. Anumana algorithms are investigational medical devices and have not yet received regulatory approval or clearance. For more information, visit anumana.ai and follow Anumana on LinkedIn and Twitter.

References
1.     Rapezzi C, Lorenzini M, Longhi S et al. Cardiac amyloidosis: the great pretender. Heart Fail Rev. 2015;20(2):117-124.
2.     Maurer MS, Elliott P, Comenzo R, Semigran M, Rapezzi C. Addressing Common Questions Encountered in the Diagnosis and Management of Cardiac Amyloidosis. Circulation. 2017;135(14):1357-1377.
3.     Ash S, Shorer E, Ramgobin D, Vo M, Gibbons J, Golamari R, Jain R, Jain R. Cardiac amyloidosis-A review of current literature for the practicing physician. Clin Cardiol. 2021 Mar;44(3):322-331.

Media Contact:
Sam Choinski
Pazanga Health Communications for Anumana
schoinski@pazangahealth.com
(860) 301-5058

NS Medical Devices: The research agreement with Pfizer will aid Anumana to develop an AI-enabled ECG algorithm to help detect patients who may be at risk of cardiac amyloidosis

Anumana, Pfizer collaborate on AI-based detection of cardiovascular disease

Medical Device Network: Health technology company Anumana and Pfizer have signed a multi-year agreement to develop an artificial intelligence electrocardiogram (AI-ECG) algorithm for the early detection of cardiac amyloidosis. Under the deal, Anumana will carry out a clinical validation trial and seek De Novo classification for the new AI-ECG algorithm as a Software-as-a-Medical-Device (SaMD).

Anumana and Pfizer partner for cardiovascular disease detection

FIERCE Biotech: The heart-focused artificial intelligence company Anumana is looking to break new ground for its algorithms through a partnership with Pfizer. They plan to develop programs that can help diagnose cases of cardiac amyloidosis, where misfolded proteins build up around the tissue.

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Philips Launches ECG AI Marketplace to Enhance Early Cardiac Diagnosis

Anumana expands AI cardiac care platform with support from Boston Scientific

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