Geneial Secures Major Contract with RENCI and NHLBI to Partner with ARPA-H to Transform Biomedical Data Standardization with Advanced AI

HOUSTON, Oct. 31, 2024 /PRNewswire/ -- Geneial, a company advancing private, community-led genetic medicine, has been awarded a one-year pilot project through National Heart, Lung, and Blood Institute's BioData Catalyst® (BDC) program and the Renaissance Computing Institute (RENCI) to advance AI tools to streamline the complex process of transforming biomedical data into analysis-ready formats. Geneial will collaborate with RENCI, NHLBI BioData Catalyst (BDC), and performers from the Advanced Research Projects Agency for Health (ARPA-H) Biomedical Data Fabric (BDF) Toolbox program to unlock new possibilities for precision medicine research and implementation on a broad scale.

As healthcare research relies increasingly on mapping fragmented datasets to standardized and interoperable data models, Geneial's new AI tools will optimize and automate this process, which currently requires extensive manual effort and significant financial investment. Geneial's technology will offer flexible, efficient conversion to current standards—such as the Global Alliance for Genomics and Health (GA4GH) Phenopackets format—while anticipating future data needs and supporting adaptable, evolving standards.

"Data standardization remains a significant challenge in precision medicine," said Dr. Adam Hansen, CEO of Geneial. "Our collaboration with ARPA-H, NHLBI, and RENCI directly addresses this critical bottleneck, enabling researchers to focus on groundbreaking discoveries rather than laborious data management. By advancing tools that meet today's needs and adapt to tomorrow's, we're substantially reduce data wrangling costs as we enhance the utility of biomedical data."

This work aligns with Geneial's broader vision of a global, privacy-preserving data exchange, one that allows individuals and data custodians to maintain control while connecting researchers, drug developers, and healthcare systems with harmonized, high-quality data. It marks a significant expansion of the business into AI-driven data standardization, while reinforcing Geneial's commitment to accelerating progress in genomic medicine, making it easier for researchers to derive insights that can lead to better, more inclusive healthcare.

Expanding Expertise in AI and Healthcare Innovation
In alignment with its growth strategy, Geneial has recently expanded its team with notable experts in AI and healthcare data. Joshua Proulx, formerly Chief Data Scientist at Safe & Reliable Healthcare (acquired by Vizient) and previously its Chief Technology Officer, brings extensive experience in healthcare data reliability and safety. Bryce Daines, Ph.D., formerly Chief Technology Officer at Modulus Therapeutics, brings deep expertise in high-throughput AI applications for biomedical research. Together, Proulx, Daines and other new team members strengthen Geneial's position as a forward-thinking partner in healthcare data innovation.

Disclaimer: The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

About RENCI
RENCI (Renaissance Computing Institute) develops and deploys advanced technologies to enable research discoveries and practical innovations. RENCI partners with researchers, government, and industry to engage and solve the problems that affect North Carolina, our nation, and the world. An institute of the University of North Carolina at Chapel Hill, RENCI was launched in 2004 as a collaboration involving UNC Chapel Hill, Duke University, and North Carolina State University.

About Geneial
Geneial is committed to creating equitable health futures by building secure, human-centered solutions for biomedical data. As Geneial expands into AI-driven data standardization, it empowers data owners and researchers with tools that unlock the value of harmonized data, driving forward precision medicine and improving access to transformative insights.

SOURCE Geneial

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