Interview Transcript (modified slightly for readability):
“Things are changing very quickly now. I feel like we’ll stall because of how many new things there are because when you get a lot of new things, it’s hard to understand what combinations [will work] or how to ration things because there’s only so much money—there’s only so much funding—and there’s only so much personnel to test these ideas.
I think science is growing exponentially, but the rate of the active testing of putting patients in trials [is lagging]. Clinical trials are still something that is hard for patients to wrap their minds around—to be part of something that is experimental and unknown. In the end, there’s a little bit of a narrowing of the tunnel. There will be a little bit of traffic behind the walls of resources and people who are willing to participate in these things.
I think what will potentially be a breakthrough, in terms of pushing past that rate-limiting step is potentially artificial intelligence (AI)—if we get computational analyses. We have big data now, but we haven’t been able to corral it.
I think if we can corral it and use big data to our advantage, we may be able to make sense of rare things that happen across the board and bring them together because we will have a way to computationally pull them together rather than manually call up people and say, ‘Do you have a case like this?’ and put it all together.”