Artificial intelligence is the hot new thing in drug discovery and development. AstraZeneca (AZN), Pfizer (PFE), and Merck have all relied on machine learning to advance their research. Bristol-Myers Squibb and Boston-based Concerto HealthAI established a new partnership in March. And Relay Therapeutics raised an astonishing $400 million series C round to support its efforts to use AI techniques to understand the way proteins bend and twist and create new drugs.
But if artificial intelligence programs are actually going to make an impact, they’re going to need a lot of data — and high quality data is hard to come by. Currently available data sets aren’t ideal for machine learning, and relying on that data might even set certain algorithms down the wrong path.