Across Healthcare joins ARPA-H rare disease data initiative
Across Healthcare will support a UNC- and Emory-led ARPA-H program aimed at building the world’s largest rare disease data resource. The effort could help researchers identify patients sooner, improve diagnosis, and expand research and trial recruitment across roughly 2,700 rare diseases.
Why it matters: - The ARPA-H RAPID initiative is designed to speed up rare disease diagnosis and care by linking clinical, genetic, patient-reported and other longitudinal data. - The project could improve patient identification for research and clinical trials across about 2,700 rare diseases. - The effort also aims to strengthen decision support for clinicians and help accelerate treatment discovery.
What happened: - Across Healthcare said it will serve as a subcontractor to the University of North Carolina at Chapel Hill and a collaborator on the RAPID program. - UNC and Emory University are leading the four-and-a-half-year initiative. - ARPA-H is funding the project with an award of up to $35 million to UNC. - The initiative sits within RAPID, or Rare Disease AI/ML for Precision Integrated Diagnostics, an ARPA-H program inside the U.S. Department of Health and Human Services. - Across announced that its Matrix platform will support rare disease data collection and community engagement.
The details: - Matrix will help with acquisition and harmonization of longitudinal data from rare disease registries and other authorized sources. - The platform will also support participant consent and engagement, data quality, healthcare data connectivity and privacy-preserving linkage. - Matrix includes support for longitudinal registries, patient- and clinician-reported research data, electronic consent and electronic health record connectivity. - Across said it will be able to contribute rare disease community data throughout the program. - Patient advocacy groups can create a longitudinal registry on Matrix or use an existing Matrix registry. - Appropriately consented and governed data from those communities can contribute to the broader RAPID resource, subject to program privacy requirements. - The announcement said longitudinal registries can also support natural history research, patient identification, clinical trial recruitment, outcomes research and future research partnerships. - Rare disease advocacy groups interested in a Matrix registry or data contribution can contact Across Healthcare at info@acrossmatrix.com. - The company says Matrix is built for patient-centered research and real-world evidence generation.
Between the lines: - The project gives rare disease advocacy groups a path to connect local community registries to a national-scale research resource without losing control over consent and governance. - The model could make patient communities more visible to researchers while preserving trust, which is often a major barrier in rare disease research. - By focusing on longitudinal data, the initiative is betting that repeated, real-world observations will be more useful than one-time snapshots for diagnosis and research. - Jason Colquitt, CEO of Across Healthcare, said rare disease advocacy groups need better ways to find patients, understand communities and identify people for research and clinical trials. - Terry Jo Bichell, PhD, CEO of COMBINEDBrain, said RAPID creates a way to connect more rare disease communities to a broader research ecosystem while preserving engagement and trust.
What's next: - Across Healthcare said rare disease patient advocacy groups can contact the company to explore setting up a Matrix registry or contributing data through the RAPID effort. - The UNC- and Emory-led project will continue over the next four and a half years as it builds the data resource and expands community participation. - If successful, the program could become a major national infrastructure for rare disease research and diagnosis.
The bottom line: - Across Healthcare is positioning Matrix as a data bridge between rare disease communities and a large federal research push aimed at faster diagnosis and better care.
Disclaimer: This article was produced by AGP Wire with the assistance of artificial intelligence based on original source content and has been refined to improve clarity, structure, and readability. This content is provided on an “as is” basis. While care has been taken in its preparation, it may contain inaccuracies or omissions, and readers should consult the original source and independently verify key information where appropriate. This content is for informational purposes only and does not constitute legal, financial, investment, or other professional advice.
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