Anumana and Pfizer Partner to Enable Early Detection of Underdiagnosed Cardiovascular Disease
Companies initiate research agreement supporting development of new AI-ECG algorithm to help identify patients who may be at risk of cardiac amyloidosis
Anumana, an AI-driven health technology company and portfolio company of nference, has entered into a multi-year agreement with Pfizer, 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.
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“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.”
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
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“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.”
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