Clinical geneticists frequently report their most challenging and time-consuming task is the identification of rare disease-causing variants.
While the Congenica clinical decision support (CDS) platform has long used AI principles of rules-based automation and variant prioritization to reduce the challenges, it was recognised that developing an ML solution for variant ranking, one that continuously learns as it’s exposed to ever more cases, would provide further enhancements.
The Congenica team has developed Congenica AI, a highly scalable, innovative and fully explainable ML framework for the interpretation of rare disease cases. It can predict the pathogenicity of any variant in the genome (following the ACMG standards) and accurately identify the most likely causative variants, providing an heterogenous set of
supporting evidence for each prediction.
