descendantsDNA, Inc. Engages Broad Clinical Labs and Fabric Genomics for Genomic Services to Support Human Longevity
descendantsDNA, Inc. Engages Broad Clinical Labs and Fabric Genomics for Genomic Services to Support Human Longevity
descendantsDNA, Inc. Engages Broad Clinical Labs and Fabric Genomics for Genomic Services to Support Human Longevity
Fabric Genomics, the leader in artificial intelligence (AI)-powered next generation sequencing interpretation, is announcing a new partnership with Intermountain Children’s Health to analyze the whole genomes of children sequenced by the Broad Clinical Labs to help speed diagnosis of kids who may have genetic diseases.
Fabric AI technology for interpretation of the human genome, powered by the Fabric GEM AI algorithm, will be adapted into the FirstSteps clinical support tool, empowering clinicians to provide timely medical intervention for patients with rare genetic diseases in Greece.
The newly formed partnership will enable clinical genomics laboratories to move from sample to evidence-backed analysis to actionable clinical reports using a push-button solution.
The partners will offer an integrated sample-to-report rapid nanopore sequencing analysis platform for neonatal/paediatric intensive care units to support clinicians in acute settings.
Fabric’s AI platform will help identify and prioritize new genome variants associated with neuroimmune axis disorders and accelerate clinical diagnostics for these conditions.
Priced at $1,000 per sample, the new test promises to be competitive with other offerings in the market
while offering better cost transparency.
Hofher, Former Chief Scientific Officer of GeneDx, is the latest addition to Fabric Genomics’ expanding leadership team
A new study in Nature Communications describes and examines the performance of Rady Children’s Institute for Genomic Medicine’s Genome-to-Treatment (GTRx™), a clinical decision support tool on which Fabric is a research collaborator.
Fabric’s PHEVOR WGS algorithm used in recent University of Utah School of Medicine study featured in npj Genomic Medicine: “A dominant negative ADIPOQ mutation in a diabetic family with renal disease, hypoadiponectinemia, and hyperceramidemia”
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