Developing new medicines isn’t for the faint of heart. On average, it takes about a decade of research — and an expenditure of $2.6 billion — to shepherd an experimental drug from lab to market. And because of concerns over safety and effectiveness, only about 5 percent of experimental drugs make it to market at all.
But drug makers and tech companies are investing billions of dollars in artificial intelligence with the hope that AI will make the drug discovery process faster and cheaper.
“I believe that AI is a sleeping giant for healthcare in general,” Eric Horvitz, director of Microsoft Research Labs in Redmond, Washington, said last month at the annual meeting of the American Association of the Advancement for Science in Austin, Texas. He said Microsoft was investing in AI for drug design and pharmacology, which studies how drugs act in the body, and called the technology a “tremendous opportunity.”
Microsoft is far from alone in its AI bet. As of late February, the Toronto-based biotech company BenchSci had counted 16 pharmaceutical companies and more than 60 startups using AI for drug discovery.
The biggest bottlenecks in drug development usually lie within the early stages of research, especially in the time needed to go from identifying a potential disease target (typically a protein within the body) to testing whether a drug candidate can hit that target.