Over 300 million people around the world live with a rare genetic disease. For most, the journey from first symptom to diagnosis lasts over 5 years, with many receiving incorrect or no diagnosis at all. Without diagnosis, patients remain without access to targeted medical interventions and potentially life-saving treatments.
New sequencing technologies are allowing millions of people to benefit from diagnostic genetic testing. However, the last step in genetic testing – variant interpretation – remains laborious and costly. A lab can spend hours, days or even weeks interpreting data from a single patient. Additionally, because of limited understanding of the consequences of variants throughout our genome, genetic test results are often inconclusive. Only about 30% of patients undergoing next-generation sequencing receive a diagnosis, leaving the majority without a clear answer.
A NEW APPROACH
Our ML model interprets variants in a way that is auditable and reproducible. Moreover, it learns from new data, but also benefits from expert knowledge: in addition to 30+ data sources, we modeled a decade of experience in clinical genetics.
To solve more variants of unknown significance, the data we currently have is not enough. We solve this by generating new data in-house in a scalable manner with massive parallel experiments leveraging new approaches in synthetic biology.
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