00:00 Speaker A
You recently joined the board of Anthropic. Not going to ask you about that specifically, but I am going to ask you about AI because there’s been so much talk within the pharmaceutical community about AI for drug discovery. We haven’t really like gotten anywhere on that yet. There’s a lot, it seems like there’s a lot of promise. So I’m curious how you guys are using that internally, how you’re thinking about it, and when you expect it to become maybe a meaningful part of the drug development story, not just at Novartis, but for the industry.
00:43 Speaker B
You know, Julie, it’s really interesting that we started investing in in kind of the beginnings of AI long ago. We started working with Palantier in 2016, 2017 to create a data platform we call Data 42. and now we’re really scaling our AI efforts across um, R&D at every single phase from early pre-clinical through entering the clinic and then actually running our our major clinical trials.
01:21 Speaker B
But I think it’s important to note that it’s going to be, I think 8 to 10 years before we really know the scale of the impact of AI, which I believe will be significant. I think we have the opportunity to speed up the overall timelines from 12 to 14 years down to eight years from how we get a discovery all the way to patients. Hopefully we can increase probability of success once we’re in humans from 8% to 15% or higher.
02:00 Speaker B
But the reason it’s going to take that much time is we can’t shorten the timeline that we have within animals to do the animal testing and then in humans to actually do the clinical trial testing. That’s fixed. And we need enough of these AI supported medicines or AI developed medicines to actually go through that process. I think when we look back in 2035, 2034, we’ll say, wow, this actually had a big impact. But until that happens, uh, we won’t know for sure.