This AI-powered genomics company is turning its attention to drug development
The next blockbuster drug could be developed with help from machine-learning techniques that are rapidly spreading from AI research to pharmacology labs.
Deep Genomics, a Canadian company that uses machine learning to trace potential genetic causes for disease, announced Tuesday that it’s getting into drug development. It joins a growing list of AI companies betting that their techniques can help produce powerful new drugs by finding subtle signals in huge quantities of genomic data.
Deep Genomics was founded by Brendan Frey, a professor at the University of Toronto who specializes in both machine learning and genomic medicine. His company uses deep learning, or very large neural networks, to analyze genomic data. Identifying one or more genes responsible for a disease can help researchers develop a drug that addresses the behavior of the faulty genes.
Until now the company has focused on scouring the genome for hard-to-detect mutations that might have a causal relationship with a particular disease. The company will focus, at first, on early-stage development of drugs for Mendelian disorders, inherited diseases that result from a single genetic mutation. These diseases are estimated to affect 350 million people worldwide.
The rush to apply AI techniques to medicine and drug development is partly driven by the emergence of powerful new algorithms, but also by cost-effective new ways of sequencing whole genomes, the entire readout of a person’s DNA. “There’s an opening of a new era of data-rich, information-based medicine,” Frey says. “There’s a lot of different kinds of data you can obtain. And the best technology we have for dealing with large amounts of data is machine learning and artificial intelligence.”
Deep learning has emerged in recent years as a very powerful way to find abstract patterns using large amounts of training data. It has proved especially valuable for speech recognition and for classification (see “10 Breakthrough Technologies 2013: Deep Learning”).
