Report: Speed up drug development with artificial intelligence

More and improved use of artificial intelligence, and an overhaul of medical education to include advances in machine learning, could cut down significantly the time it takes to develop and bring new drugs to market, according to a new joint report by the National Academy of Medicine and the Government Accountability Office. Before that can happen, however, the United States must address legal and policy impediments that inhibit the collection and sharing of high-quality medical data among researchers, the report said. "Machine learning holds tremendous potential in drug development," according to the two-part report released Tuesday, which said such technologies could cut down the current time of about 10 to 15 years it takes to develop and bring a new drug to market. "In drug discovery, researchers are using [machine learning] to identify new drug targets, screen known compounds for new therapeutic applications, and design new drug candidates, among other applications." Researchers involved in drug discovery said infusion of machine learning technologies at the early stage of drug development could result in savings of between $300 million and $400 million per successful drug, the GAO said.