Fabric Genomics Technology Supports Global Scientific Study of Whole Genome Sequencing in Rare Disease Diagnosis

OAKLAND, Calif.--(BUSINESS WIRE)-- The New England Journal of Medicine has published findings from a pilot study that has shown how whole genome sequencing (WGS) uncovered new diagnoses for patients across the broadest range of rare diseases. The identification and prioritization of candidate genetic variants were performed with Fabric Genomics’ artificial intelligence (AI)-driven decision-support system and the company’s clinical genetics teams, who analyzed a large portion of the genomes of the 4,660 people in the study, a part of the 100,000 Genomes Project, led by Genomics England, England’s National Health Service (NHS) and Queen Mary University of London.

The pilot study found that using WGS led to a new diagnosis for 25% of the participants. Of these new diagnoses, 14% were found in regions of the genome that would be missed by other conventional methods, including other types of non-whole genomic tests. The groundbreaking 100,000 Genomes Project which produced this study was established in 2013 to sequence whole genomes from NHS patients and their families in the United Kingdom.

“Congratulations to Genomics England and Queen Mary University of London for the incredible progress they have made in the 100,000 Genomes Project bringing the power of whole genome sequencing to rare disease diagnostics,” said Martin Reese, PhD, Founder and CEO of Fabric Genomics. “Large public projects like this have created technologies, data and solutions including Fabric GEM that demonstrate benefits for individuals and the health care system as a whole. The Fabric team is happy to have participated in this important study showing how whole genome sequencing can guide patient care in the clinic at scale.”

“Rare disorders and uncommon forms of common conditions are significant health burdens and are costly worldwide,” said clinical geneticist and Fabric Genomics co-founder Dr. Paul Billings. “This pilot study underscores the importance of WGS in significantly improving the speed, diagnostic yield and value of testing for rare disorders. The inclusion of new AI and review from Fabric Genomics appears essential for those outcomes.”

This publication follows on the heels of another demonstration of the potential of whole genome sequencing to impact patient treatment involving the Fabric GEM AI algorithm. In October, Fabric Genomics published in Genome Medicine performance results of its Fabric GEM AI algorithm in a benchmark retrospective study together with its partner Rady Children’s Institute for Genomic Medicine in previously diagnosed newborns and rare disease patients at Rady Children’s Hospital – San Diego and other clinical sites demonstrating improved and rapid identification of genetic diseases.

Fabric GEM is a clinical decision support software applying advanced AI, and leveraging genomic, phenotypic, and clinical data to identify a short list of causal candidates. Fabric GEM prioritizes variants, reducing the typical number of candidates for clinical review to fewer than five.

The full publication can be found online at: https://www.nejm.org/doi/full/10.1056/NEJMoa2035790.

The Genomics England news release can be found at: https://www.genomicsengland.co.uk/news.

About Fabric Genomics

Fabric Genomics is making genomics-driven precision medicine a reality. The company provides clinical decision-support software that enables clinical labs, hospital systems, and country-sequencing programs to gain actionable genomic insights, improved diagnostic yields, and reduced turnaround time. Fabric’s Enterprise Platform for end-to-end genomic analysis incorporates proven AI-algorithms and natural language processing and has applications in both hereditary disease and oncology. Headquartered in Oakland, California, Fabric Genomics was founded by industry veterans and innovators with a deep understanding of bioinformatics, large-scale genomics, and clinical diagnostics. To learn more, visit fabricgenomics.com and follow us on Twitter and LinkedIn.

View source version on businesswire.com: https://www.businesswire.com/news/home/20211111005494/en/