RARE Daily

Emedgene to Donate AI Assessments to Help Undiagnosed Rare Disease Patients

March 2, 2020

Rare Daily Staff

Emedgene, an AI-based genomic analysis company, is launching an initiative to help patients with undiagnosed rare diseases by using its platform and new algorithm to re-run patient cases and identify whether they can be solved with newly available information.

Emedgene says its Pathorolo algorithm is the first machine-learning algorithm developed to assess the likelihood of solving a genomic clinical case with currently available evidence. The model is based on the Isreali biotech’s proprietary automatic-interpretation algorithms, which include information continuously curated from the literature and databases. In a test cohort of 553 patients 93 percent of cases that were identified as solved, were indeed solved, says the company.

 

Emedgene will continuously run its algorithms on the data and alert patients once cases are recognized as solvable. The recommended follow-up will be through a certified medical geneticist, who will be provided with the new evidence for the case. Emedgene will collaborate with patient advocacy groups, research institutes, and non-profit organizations to make the program available for their patients.

 

“Fewer than 50 percent of rare disease cases are solved on initial analysis,” says Einat Metzer, CEO of Emedgene. “But genomics knowledge is growing at a fast pace, and at rerun, an estimated 10 percent of cases can be solved with new information. We’d like to close the gap between scientific knowledge and patient care. In this era of extremely rapid discovery, ironically, computational AI approaches can demonstrate human compassion.”

 

Rare Genomics Institute is one of the organizations that have worked closely with Emedgene over the past year. Debora Varon, a senior genetics analyst at RGI, believes the benefits of automatically reanalyzing patients cases with novel scientific approaches will bring renewed hope to undiagnosed rare disease patients.

 

Emedgene’s AI-based genomic interpretation platform has been adopted by genetic labs including Baylor Genetics, Baylor College of Medicine, Medical College of Wisconsin, Greenwood Genetic Center, TGEN and Clalit HMO. The platform automates the genomic analysis and interpretation workflow, and, according to the company, reduces the time spent per case by 50 percent or more, while increasing yield and accelerating discovery.

 

Photo: Einat Metzer, CEO of Emedgene

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