Nvidia’s AI ambitions in medicine and healthcare are becoming evident.

  • NVIDIA launched nearly two dozen new AI-powered, healthcare-focused tools at its 2024 GTC AI conference last week, and has deals with Johnson & Johnson and GE Healthcare for surgery and medical imaging.
  • For the AI ​​chip leader, the foray into healthcare is an endeavor that has been in development for a decade and has significant revenue potential.
  • AI for drug discovery, a process that can take 12 years and cost billions, is rapidly being adopted.

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Nvidia CEO Jensen Huang delivers a keynote address during the Nvidia GTC conference on March 18, 2024 in San Jose, California.

Justin Sullivan | Getty Images

Last week, Nvidia announced deals with Johnson & Johnson to use generative AI in surgery and with GE Healthcare to improve medical imaging. Healthcare advancements at its 2024 GTC AI conference, including the release of nearly two dozen new AI-powered, healthcare-focused tools — show that Nvidia’s non-tech sector is in the future. How important is medicine to income opportunities?

“The reason why Nvidia is so popular today is because it basically provided the plumbing and technology that you couldn’t do before or if you had to do it, it would probably take you many times more time, money and cost. will be needed,” said Raj Joshi, a technology analyst and senior vice president at Moody’s Ratings. “Health care, whether it’s biotechnology, chemicals, or drug discovery is a very powerful field.”

Shares of Nvidia are up nearly 100% year-to-date, and the biotech industry is an example of the untapped potential that investors continue to bet on. AI can speed up the drug discovery process and even find uses for drugs that may fail to produce results in the initial disease it was designed to target.

“Over the last 18 months or so, we believe it’s more hope than hype because of concrete results and then very compelling use cases of how AI can help the pharmaceutical industry, the medtech industry or the biotech industry. of,” said Arda Ural, EY Americas Health and Life Sciences Industry Market Leader.

Drug development is a risky process that can take at least a decade from concept to clinical studies, Ural said. It is also a process that can cost billions with a high chance of failure.

About 41 percent of biotech CEOs surveyed by EY at the end of 2023 said they were considering “concrete” ways that generative AI could be used for their companies. “That’s a lot for my experience, 30 years in the industry,” Ural said. “It’s a really unique feature that we’re seeing with AI that’s being picked up much faster than other technologies.”

Nvidia’s focus on healthcare at its conference doubled down on an ambition it’s had for a long time. During an earnings call with investors in February, Nvidia mentioned several ways its technology is being adapted for the medical field. Companies like Recursion Pharmaceuticals and Generate: Biomedicines are expanding their biomedical research with the help of hyperscale or GPU specialized cloud providers, and they need Nvidia AI infrastructure to facilitate the process.

“In healthcare, digital biology and generative AI are helping to reinvent drug discovery, surgery, medical imaging and wearable devices,” said Colette Kress, Nvidia’s chief financial officer. “We’ve built deep domain expertise in healthcare over the last decade, building on the NVIDIA Clara healthcare platform and NVIDIA BioNeMo, an innovative AI service that builds AI foundational models for computer-aided drug discovery. Designed to do, customize and deploy.”

Last year, NVIDIA invested $50 million in Recursion for its drug discovery projects. Recursion is feeding its biological and chemical data to train NVIDIA’s AI models on its cloud platform. The company has also worked with Roche’s Genentech to develop new drugs and improved treatment protocols. It also partnered with Schrödinger for drug discovery in 2021.

One of NVIDIA’s biggest strengths in healthcare to date is the BioNeMo platform, an innovative AI cloud service designed specifically for drug development.

“It’s one thing to design semiconductors and computing platforms for others to do something. But it’s another thing when you can build complete technology packages that you can sell to a customer,” Joshi said. “Let’s say if you’re a biotech firm, you take a whole technology from Nvidia, and you just start working on it, as opposed to figuring out, ‘How do I use this information technology?’ ”

Biotech-focused generative AI platforms have the potential to reduce costs beyond the drug manufacturing process for pharmaceutical companies. Many firms offshored their back office processes for supply chain, finance and administrative functions as well as manufacturing to save money. But with geopolitical tensions rising and an emphasis on bringing jobs back to the U.S., moving jobs overseas has become a growing cost.

“Now you can do this at home with AI at a much lower cost because you now have robotic process automation, powered by AI,” Ural said. “So not only does it help speed up drug development, it also helps lower the cost of running a company. That means you can invest more in drug development and more. can quickly find a cure.”

The healthcare space is an example of how far a company that designed gaming graphics cards a decade ago has come. “You have to give them credit that Jensen had a foresight in 2012 when he saw some people at Stanford University using their graphics cards to solve some kind of math problem,” Joshi said. said “He said, ‘You know what, this can actually be used for so-called general computing, you know, things that we all do on a day-to-day basis.'”

But to fully realize the benefits of AI that are just becoming apparent in the healthcare sector, leaders will need to gain more support from the nation’s largest workforce. According to EY’s AI Anxiety in Business survey, more than two-thirds of health science and wellness employees are concerned about the use of AI, and 7 in 10 are concerned about the adoption of AI in the workplace. .

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