A new partnership has been created between the genomics data search company Genomenon and Rhythm Pharmaceuticals, which aims to create and manufacture therapies that can treat rare disorders that cause obesity. The team has aimed to establish a database that compiles genetic mutations that have been linked, by published research studies, with the development of obesity. The hope is that drug development can be accelerated with this new tool.
Genomenon has utilized the Mastermind Genomic Search Engine so that genes and variants that have been associated with obesity are easily searchable. An evidence-based method will be employed to ensure the integrity of the findings; only clinically relevant genes and variants, as well as the studies that identified them, will be included. Rhythm can then learn more about how genetic factors influence obesity, and how they might be manipulated to combat it.
"We are combining computational variant analysis and population studies with the published scientific evidence identified and collated by Genomenon to create a knowledge base on the molecular genetics related to obesity,” said Lex Van der Ploeg, Chief Scientific Officer of Rhythm. "The evidence provided by Genomenon’s advanced machine learning tools and genomic search database may help identify patients who might be appropriate for treatment with therapies specifically targeted towards genetic pathways that contribute to obesity.”
Mastermind will be the first genomic search engine that combines genetic data with evidence obtained in the laboratory and reported in peer-reviewed literature. Genomenon used machine learning and Genomic Language Processing that can sift through articles to find relevant information; the bioinformaticians harvested information about mutations that cause disease from millions of research articles. A team of scientists at Genomenon then reviewed the work.
The result was a database of biomarkers, including over 10,000 mutations from 120 genes that have been connected with obesity. It took less than 60 days to compile the information, which includes the citations for every one of the mutations. Machine learning was thus able to quickly complete a task that takes a person about a year to do.
“This is an exciting demonstration on how genomic language processing and machine learning can drive important advances in drug development,” said Mike Klein, CEO of Genomenon. “We’re thrilled to be working with Rhythm Pharmaceuticals and look forward to our ongoing work together.”
You can find out more about how to use Mastermind from the video, produced by Genomenon.