Rhythm Pharmaceuticals will discuss their work with Genomenon to create the landscape of genomic mutations associated with rare genetic disorders of obesity. They will describe how the genomic landscape was optimized to facilitate a deep understanding of the variant landscape of melanocortin-4 receptor (MC4R)-pathway genes. The end result of their work may help identify MC4R-pathway deficient individuals who might benefit from future precision therapies.
Genomenon indexed over 6 million full-text genomic articles to identify 120 genes and over 10,000 variants associated with obesity in the medical literature. Each individual genomic variant was interpreted using the evidence assembled through a machine-learning based technical process. This novel Artificial Intelligence (A.I.) approach vetted and annotated each variant using American College of Medical Genetics and Genomics (ACMG) guidelines.
Join Alastair Garfield, PhD, Vice President, Translational Research & Development (TRAD) at Rhythm Pharmaceuticals and Dr. Mark Kiel, Founder and Chief Science Officer at Genomenon, as they share how a database of genes and variants associated with obesity was developed in less than 60 days, including scientific evidence complete with literature citations and ACMG interpretations for each mutation. The machine-learning driven process replaced years of manual research of the scientific literature to find and interpret these obesity-related mutations.
You will learn:
- The importance of having the entire published landscape of genetic evidence at your fingertips in the precision drug development process
- How Genomenon rapidly assembled a comprehensive biomarker database of the genetic evidence tied to obesity
- How A.I. and Machine Learning can be used to interpret the genomic variants by ACMG guidelines in a fraction of the time of manual curation processes