The British scientist's company employs artificial intelligence to drastically reduce the speed of drug development.

It was early one morning in 1996 when Andrew Hopkins, then a PhD biophysics student at Oxford University, had a brainwave as he walked home from a late-night lab meeting. He was trying to find molecules to fight HIV and to better understand drug resistance. "I remember this idea struck me that there must be a better way to do drug discovery other than the complex and expensive way everyone was following," he says. "Why couldn't we design an automated approach to drug design that would use all the information in parallel so that even a humble PhD student could create a medicine? That idea really stuck with me. I remember almost the exact moment to this day. And that was the genesis of the idea that eventually became Exscientia."

This week at the World Medical Innovation Forum in Boston, industry experts gathered to discuss the role of artificial intelligence (AI) in healthcare. While AI has made waves in diagnosing certain diseases better than doctors, there's another area where the tech is being applied that might eventually have even greater impacts on health. Today, at least 18 pharmaceutical companies and more than 75 startups are applying machine learning to drug discovery--the complex, expensive process of identifying and testing new drug compounds. These companies are betting hundreds of millions of dollars that AI will reduce costs, shorten timelines, and lead to new and better drugs. At the Forum on Monday, Exscientia founder and CEO Andrew Hopkins, formerly a professor at the University of Dundee in Scotland and a 10-year veteran of Pfizer, spoke about how AI can lead to improvements in drug development.