Accelerating Medicines Partnership Welcomes Anumana to its Heart Failure Program

Anumana has joined the Accelerating Medicines Partnership (AMP) Heart Failure program. The initiative—managed by the Foundation of the National Institutes of Health (FNIH)—brings together leaders in academia, industry, and government to advance critical research and improve patient outcomes.

“We are honored to join experts in the AMP Heart Failure program to help advance the next generation of treatments,” Anumana CEO Maulik Nanavaty said. “While heart disease treatments have seen remarkable progress, heart failure deaths continue to rise. The AMP Heart Failure collaboration is poised to shift that trend. Anumana will bring our expertise in developing and validating AI-enabled software as medical device (SaMD) that identifies diseases from electrocardiograms to advance the goals of the AMP Heart Failure program. By enabling earlier diagnoses, we aim to help improve patient care by starting treatment sooner, and ultimately improving quality of life.”

Launched in 2022 in collaboration with the National Heart, Lung, and Blood Institute at the National Institutes of Health (NIH), AMP Heart Failure is a multi-year, multi-center initiative focused on understanding heart failure with preserved ejection fraction (HFpEF), a complex condition in cardiovascular health, through two parallel and interconnected components. The first component is to aggregate clinical data from over 30 existing cohorts and trials to identify HFpEF subtypes. The second component builds upon the knowledge generated from component one by creating an extensively phenotyped new HFpEF patient cohort. Using advanced technologies, including digital measurements and AI-driven analytic methods, AMP HF aims to transform care with more precise treatment options, ultimately improving the outlook for millions of patients worldwide.

“AMP Heart Failure provides the opportunity to collaborate with partners that are using cutting-edge technologies to lower the risk of mortality in HFpEF patients and improve the quality of life,” said Tania Kamphaus, Ph.D., associate vice president, Science Partnerships, and director of Patient Engagement at the FNIH. “Anumana will contribute key analytical tools to help deepen our understanding of HFpEF and advance our ultimate goal of developing new treatments.”

Heart failure remains a leading cause of death and hospitalization globally, affecting nearly 6.7 million U.S. adults.¹ As an AMP Heart Failure partner, Anumana will support the program’s goals, including unifying large existing real-world datasets and developing new data solutions focused on HFpEF. This expanded dataset also provides Anumana with an opportunity to evaluate its ECG-AI algorithms across a broader patient population. By applying its technology to this real-world data, Anumana will facilitate earlier detection of complex heart conditions and drive more personalized treatment strategies.

ECG-AI LEF, Anumana’s AI algorithm using routine 12-lead ECG data to detect Low Ejection Fraction (LEF)—a commonly underdiagnosed indicator of heart failure²—received U.S. Food and Drug Administration (FDA) clearance in 2023 and is currently under review in Europe. Anumana has received FDA Breakthrough Device Designation for three additional algorithms: pulmonary hypertension, cardiac amyloidosis, and hyperkalemia. The company’s algorithms have been studied in more than 75 published clinical studies, effectively identifying conditions such as low ejection fraction and other hidden heart diseases.

Anumana is an AI-driven health technology company leveraging cutting-edge AI and translational science to unlock the heart’s electrical language. 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.

References
¹ Joynt Maddox et al. Circulation. 2024; v150:n4: https://doi.org/10.1161/CIR.0000000000001256
² Sara et al. European Cardiology Review. 2020 Feb:e13: 10.15420/ecr.2019.14