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Eli Lilly and NVIDIA have partnered to build the most powerful supercomputer owned and operated by a pharmaceutical company," which will be used to power an "AI factory" for drug discovery and development.
Eli Lilly, NVIDIA announce new AI partnership
Earlier this week, Eli Lilly announced that it was partnering with NVIDIA to build "the most powerful supercomputer owned and operated by a pharmaceutical company." The supercomputer will be the first NVIDIA DGX SuperPOD with DGX B300 systems and will run on a single network powered by over 1,000 graphics processing units.
According to Lilly, the new supercomputer will be used to power an "AI factory," which will take in data, train models based on internal company experiments, and generate inferences. Lilly plans to use the supercomputer to expand molecule discovery research and to shorten drug development cycles. Currently, the drug development process takes an average of 10 years to go from testing a new drug in people to its launch on the market.
"We're hopeful that we'll be able to discover new molecules that we never would have with humans alone," said Diogo Rau, Lilly's chief information and digital officer.
The supercomputer "is really a novel scientific instrument," said Thomas Fuchs, Lilly's chief AI officer. "It's like an enormous microscope for biologists. It really allows us to do things we couldn't do before at that enormous scale."
Several of the AI models trained by the supercomputer will also be available on Lilly TuneLab, a new AI and machine learning platform. In September, Lilly announced that select biotech companies could soon use its proprietary AI models at no cost if they allow Lilly to use their data to train the models.
"It's really powerful to be able to give that extra starting point to these startups that, you know, otherwise could take a couple of years burning their capital to get to that point,” said Kimberly Powell, VP of healthcare at NVIDIA.
Overall, "Lilly is shifting from using AI as a tool to embracing it as a scientific collaborator," Fuchs said. "This isn't just about speed, but rather interrogating biology at scale, deepening our understanding of disease and translating that knowledge into meaningful advances for people served by Lilly medicines as well as the broader life sciences ecosystem."
Several of the AI models trained by the supercomputer will also be available on Lilly TuneLab, a new AI and machine learning platform. In September, Lilly announced that select biotech companies could soon use its proprietary AI models at no cost if they allow Lilly to use their data to train the models.
"It's really powerful to be able to give that extra starting point to these startups that, you know, otherwise could take a couple of years burning their capital to get to that point,” said Kimberly Powell, VP of healthcare at NVIDIA.
Overall, "Lilly is shifting from using AI as a tool to embracing it as a scientific collaborator," Fuchs said. "This isn't just about speed, but rather interrogating biology at scale, deepening our understanding of disease and translating that knowledge into meaningful advances for people served by Lilly medicines as well as the broader life sciences ecosystem."
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Commentary
According to Fierce Biotech, Lilly is not the first drugmaker to partner with NVIDIA to build a supercomputer. In June, Novo Nordisk partnered with NVIDIA to build a new supercomputer in Copenhagen. In 2020, NVIDIA created Cambridge-1, the United Kingdom's most powerful supercomputer, in partnership with GSK, AstraZeneca, and the National Health Service.
However, AI supercomputers don't guarantee success, with few companies producing tangible results so far.
For example, IBM's Watson supercomputer failed to live up to expectations the company set for it, including in genomics and oncology. In 2022, IBM announced plans to sell Watson Health's data and analytics business. Similarly, high-profile AI-powered startups like Absci and Generate:Biomedicines have been unable to show that their technology can discover and create new drugs.
Ultimately, any progress made with AI supercomputers is likely to be gradual, with drugmakers seeing returns on their technological investments years in the future.
"The things that we're talking about discovering with this kind of power that we have right now, we're really going to see those benefits in 2030," Rau said. Any new molecules discovered with the help of AI supercomputers would also need to go through clinical trials, which take several years.
However, Rau said he believed Lilly's investment in AI would eventually pay off. "We have a strong belief that the medicines of the future, medicines that we're going to see in the 2030s, 2040s in the hands of patients, those are going to be discovered by AI, with the help of AI, over the next several years," he said.
(Trang, STAT+ [subscription required], 10/28; Constantino, CNBC, 10/28; Loftus/Whelan, Wall Street Journal, 10/28; Incorvaia, Fierce Biotech, 10/28; Trang, STAT+ [subscription required], 2/10)
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