Alnylam Advances Future of ATTR-CM Care Through Strategic Collaboration with Viz.ai and Support for the American Heart Association

Key Takeaways

• Alnylam partners with Viz.ai for AI-driven ATTR‑CM detection.
• AWARE study pilots AI workflow in five health systems.
• Collaboration supports AHA’s three‑year ATTR‑CM learning network.
• Goal: shift diagnosis earlier, improve care coordination.
• Underdiagnosis affects ~80% of 350,000 global ATTR patients.

Summary

Alnylam Pharmaceuticals announced a strategic partnership with Viz.ai to develop an AI‑enabled care pathway for earlier detection of transthyretin amyloid cardiomyopathy (ATTR‑CM), launching the AWARE study in five health systems. The company also pledged support for the American Heart Association’s three‑year ATTR‑CM Discovery Initiative, creating a 10‑site learning collaborative to improve care coordination. Both efforts aim to shift diagnosis upstream, generate real‑world evidence, and standardize treatment pathways for a disease that remains underdiagnosed. Alnylam will discuss these initiatives in a TTR investor webinar at 9:30 am ET.

Pulse Analysis

Transthyretin amyloid cardiomyopathy (ATTR‑CM) is a rapidly progressive form of heart failure that remains dramatically underdiagnosed; estimates suggest 80 % of the roughly 350,000 global patients never receive a formal diagnosis. Late identification limits access to disease‑modifying therapies, including Alnylam’s RNAi‑based treatments, and drives higher mortality and costly hospitalizations. As the leading RNA interference company, Alnylam has a strategic incentive to close the diagnostic gap, not only to improve patient outcomes but also to expand the market for its approved and pipeline products.

To accelerate detection, Alnylam has teamed with Viz.ai, a pioneer in AI‑powered imaging analysis, to embed an FDA‑cleared echocardiography algorithm (Us2.ai) into electronic health‑record workflows. The joint AWARE (AI‑Enhanced Echocardiography Workflow to Advance Recognition and Diagnosis of Cardiac Amyloidosis) study will launch in five diverse health systems, generating real‑world evidence on how automated alerts influence referral timing and treatment initiation. By tackling the practical barriers of integration—data interoperability, clinician trust, and workflow disruption—the partnership aims to prove that AI can move from pilot projects to scalable, reimbursable tools across the Viz.ai network.

Complementing the technology push, Alnylam is backing the American Heart Association’s three‑year ATTR‑CM Discovery Initiative, which will convene a 10‑site learning collaborative to map gaps, share best‑practice pathways, and standardize referral criteria. By aggregating data from both AI‑driven pilots and multidisciplinary clinics, the initiative can produce actionable benchmarks for insurers and policymakers, potentially reshaping reimbursement models for early‑stage therapy. If successful, the combined effort could set a new industry standard for rare‑disease diagnostics, accelerate adoption of RNAi therapeutics, and generate a measurable reduction in heart‑failure‑related costs for the U.S. healthcare system.