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Editorial Advisory Board

  • Professor Andrea M. Armani, University of Southern California
  • Ruti Ben-Shlomi, Ph.D., LightSolver
  • James Butler, Ph.D., Hamamatsu
  • Natalie Fardian-Melamed, Ph.D., Columbia University
  • Justin Sigley, Ph.D., AmeriCOM
  • Professor Birgit Stiller, Max Planck Institute for the Science of Light, and Leibniz University of Hannover
  • Professor Stephen Sweeney, University of Glasgow
  • Mohan Wang, Ph.D., University of Oxford
  • Professor Xuchen Wang, Harbin Engineering University
  • Professor Stefan Witte, Delft University of Technology

GeneDx Enhances the Power of its Interpretation Platform with Artificial Intelligence (AI) Powered Gene Ranker to Enable Faster and More Efficient Clinical Analysis

GeneDx's Multiscore tool to be showcased at the American College of Medical Genetics and Genomics (ACMG) Annual Meeting

GeneDx (Nasdaq: WGS), a leader in delivering improved health outcomes through genomic insights, today announced Multiscore, an advanced AI-powered decision support tool designed to revolutionize genetic analysis by improving diagnostic efficiency, streamlining workflows, and enhancing clinical insights. Multiscore is embedded into GeneDx’s interpretation platform as a decision support tool to help clinical geneticists focus on the most relevant genes during their clinical analysis. GeneDx will present the AI-powered decision support tool at ACMG, in a session: Multiscore, a Gene Ranker Powered by Artificial Intelligence and Real-World Clinical Data, Shows High Sensitivity in 10,000 Exomes and Genomes which received one of the limited spots in an industry-specific platform session.

Through the combination of GeneDx’s industry leading proprietary dataset, publicly available data, and the power of AI, Multiscore prioritizes genes in exome and genome sequences by ranking them based on alignment with a patient’s clinical presentation. Incorporating phenotypic similarities into gene ranking criteria, GeneDx can better serve patients whose symptoms may not fit textbook descriptions and enables the identification of pathogenic or likely pathogenic diagnoses even in complex cases. This approach enables faster, more accurate identification of genetic conditions, providing a scalable solution for clinical interpretation embedded directly within GeneDx’s platform, and reducing the time required for manual review by analysts, ultimately shortening the overall turnaround time for delivering results.

“GeneDx recognizes the impact of AI to unlock even more potential and opportunity from our genomic data, and its ability to drive efficiencies in workflows, ultimately accelerating the time to diagnosis and enabling genetic diagnoses at scale. Multiscore is just one of the many ways we're leveraging the power of AI in our workflows,” said Bryan Dechairo, PhD, Chief Operating Officer at GeneDx. “By equipping our clinical geneticists with AI-driven solutions during analysis, we're not only improving operational performance and scale, we're also enriching our database even more rapidly. With each test we gain a deeper understanding of disease-gene relationships which also serve as a powerful tool to accelerate the path to treatment for patients.”

By leveraging the accumulated insights within GeneDx’s database of 750,000 clinical exome and genome sequences and over six million phenotypic datapoints, Multiscore offers a continuously updated knowledge base and ensures the most current gene-disease associations are incorporated into the interpretation process regularly.

About GeneDx:

At GeneDx (Nasdaq: WGS), we believe that everyone deserves personalized, targeted medical care—and that it all begins with a genetic diagnosis. Fueled by one of the world’s largest, rare disease data sets, our industry-leading exome and genome tests translate complex genomic data into clinical answers that unlock personalized health plans, accelerate drug discovery, and improve health system efficiencies. For more information, please visit genedx.com and connect with us on LinkedIn, Facebook, and Instagram.

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