Benchmark genome study demonstrates accuracy of artificial intelligence in rapidly diagnosing rare diseases

Fabric Genomics and Rady Children's Institute for Genomic Medicine today announced the publication of a retrospective study in Genome Medicine showing that across six leading genomic centers and hospitals, researchers were able to detect more than 90% of disease-causing variants in infants with rare diseases using the Fabric GEM AI algorithm and whole-genome and whole-exome data from previously diagnosed newborns and rare disease patients at Rady Children's Hospital – San Diego and other clinical sites. Despite differences in case collection, sequencing methods, and bioinformatics pipelines across all sites, Fabric GEM's performance demonstrated a new standard of accuracy, ranking the causative variant first or second more than 90% of the time. In addition, Fabric GEM ranked specific diseases and conditions associated with these genes to assist clinicians in the ultimate diagnosis of each case. These findings demonstrate how artificial intelligence (AI) can successfully reduce the burden of gene variant review by clinical geneticists. "Fast and definitive genetic diagnosis is essential to providing the right treatment in a timely manner for critically ill newborns," said Stephen Kingsmore, MD, DSc, a co-author of the study and the President and CEO of Rady Children's Institute for Genomic Medicine.