00:00 julie
Eli Lilly partners with Nvidia to advance learning systems for drug discovery. Here, we will talk about how healthcare is moving into the realm of AI. Please welcome Lucas Montals, Executive Vice President and Chief Financial Officer of Eli Lilly. Lucas, nice to meet you. Thank you for joining us.
00:23 Lucas Montals
Have a nice day. Thank you for having me.
00:26 julie
So let’s talk about this new lab. You guys, uh, it’s a billion dollar lab that uses Nvidia technology and teams up with some of Eli Lilly’s scientists and doctors to discover drugs. There is a lot of talk about AI in drug discovery. Can you please explain exactly how this works?
00:53 Lucas Montals
Yeah. Well, first of all, this is a real investment that we’re making here in San Francisco. We bring together both the company’s scientists and Nvidia’s researchers and engineers – the best talent from both companies – here in San Francisco. You mentioned a total investment of up to $1 billion, and that investment is going to be invested not only in infrastructure, but also in computing to basically tackle some of the toughest problems in drug discovery, across our core therapeutic areas and portfolio. It’s very exciting. This is also based on the additional investments we are making. We are rebuilding supercomputers. This is located in Indianapolis. We are building that supercomputer in our corporate center. The computer is expected to be operational as early as next month. This is a very exciting time to further develop our journey in AI.
01:43 julie
Lucas, when you say you are, you are trying to solve some of the most difficult problems in medicine. What is the most difficult problem? What will you focus your efforts on?
02:05 Lucas Montals
Well, as I said, there is a concentration of energy across all treatment areas. Again, all of the challenges with small molecule, gene therapy are fundamentally driven by how much you can put in scope or test different target discoveries. AI can help make it much stronger and faster, but it can also explore different combinations much faster than before. Scientists and our bright minds are still very much needed, but again, this will help strengthen it over time.
02:45 julie
Lucas, I’m also interested in how that impacts some sort of cost equation over time, right? You’re investing in technology right now. Um, but if it gets faster, or if more drugs can come out to treat more different things, ultimately, are we going to see overall costs go down as a result of AI and this method of drug discovery?
03:22 Lucas Montals
As time goes on, Julie, I think you’ll see that there are two sides to this. The first one is what you alluded to, which is basically speeding up the time to market for molecules. This is critical as we think about bringing these solutions back to patients around the world. That is our main focus and how we can bring further innovation. But at the same time, you also mentioned the cost part. Of course, over time you may find that this also improves efficiency in how it furthers your development focus. But the main focus is how to do this quickly and bring more molecules to market.
