AI in Genomics

Genomic data sets pose technical challenges due to their size and complexity. While genomics becomes increasingly utilized in medicine, so too are artificial intelligence (AI) and machine learning (ML) as technology for these practices improve simultaneously. To discuss the ways in which AI and ML could to aid clinicians’ and researchers’ interpretation and management of genomic data, PhenoTips invited Dr. Orion Buske and Dr. Mark Kiel to address the current and future status of AI in genomics.

Dr. Orion Buske is the Chief Technology Officer of PhenoTips, where he has been instrumental to the development of the innovative Genomic Health Record software for nearly a decade. Dr. Buske holds a PhD in Computer Science from the University of Toronto, where he specialized in algorithms for genome analysis and rare disease patient matchmaking, leading the technical working group of the Matchmaker Exchange as well as the redevelopment of RareConnect.org. Throughout his career he has also led the technical developments of both PhenomeCentral and PatientKind. Dr. Buske remains an active member of the Global Alliance for Genomics and Health (GA4GH) where he co-leads the new Pedigree Standards stream of the Clinical & Phenotypic Data Capture working group.

Dr. Mark Kiel completed his M.D., Ph.D., and Molecular Genetic Pathology Fellowship at the University of Michigan, where his research focused on stem cell biology, genomic profiling of hematopoietic malignancies, and clinical bioinformatics. He is the founder and chief scientific officer at Genomenon, a genomic intelligence company, where he oversees the company’s scientific direction and product development. Mark founded Genomenon in 2014 to address the challenge of connecting researchers with evidence in the genomic literature to help diagnose and treat patients with genetic diseases and cancer.

In this discussion, Dr. Mark Kiel and Dr. Orion Buske discuss:

• Current and future applications of AI in genomics
• Limitations to the application of AI in genomics
• The role of AI in advancing precision medicine
• Ethical, legal, and social implications of the application of AI in genomics