Accurkardia has announced that it has been granted US patent number 12,620,488 for the company’s proprietary machine learning-based system for identifying cardiac amyloidosis from a standard, routinely performed 12-lead electrocardiogram (ECG).
In a press release, Accurkardia notes that most cardiac amyloidosis patients are only identified after permanent damage to the heart has already occurred, adding that the stakes of earlier detection are “high, and concrete”, impacting which treatments patients receive and how long they live.
According to the company, catching cardiac amyloidosis sooner steers patients away from standard heart failure treatments that may be ineffective or even harmful for this condition, and toward therapies proven to improve survival.
“Cardiac amyloidosis hides in plain sight—and, because the symptoms are quite similar to other causes of heart failure, we have historically relied on expensive, late-stage imaging to diagnose what is already advanced disease, often after conventional medical therapy has failed to improve symptoms,” said Jason Lazar (State University of New York [SUNY] Downstate, New York, USA). “A reliable ECG-based screening signal, leveraging information the human eye simply cannot extract, has the potential to redefine when and how we intervene, particularly as therapeutic options continue to expand. Simply put, earlier diagnosis leads to much better outcomes.”
Accurkardia’s patent establishes its intellectual property foundation across all major amyloidosis subtypes, including amyloid light-chain (AL) amyloidosis, and wild-type and hereditary transthyretin amyloidosis (ATTR). It joins a growing pipeline of Accurkardia artificial intelligence (AI)-ECG biomarkers that includes US Food and Drug Administration (FDA) Breakthrough Device-designated algorithms for aortic stenosis—AK-AVS—and hyperkalaemia—AK+ Guard—alongside the company’s US FDA-cleared automated ECG interpretation platform, AccurECG 2.0.
“Disease-modifying amyloidosis therapies are among the most important advances in cardiology in a generation, but their impact is gated by our ability to find the right patients in time,” said Juan Jimenez, co-founder and chief executive officer (CEO) of Accurkardia. “This patent establishes the foundation for closing that gap. We are turning a test that is already performed millions of times per year globally into a screening biomarker, deployable without new hardware or procedures, seamlessly integrating our capabilities into existing workflows.”
Accurkardia states that a distinguishing feature of this approach is its use of explainable, feature-based machine learning built on annotated ECG parameters rather than a ‘black box’ model. The design supports interpretability for clinicians, transparency for regulators, and adaptability for downstream deployment at scale, the company adds.
