Nvidia’s AI ambitions in medicine and healthcare are becoming clear

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

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Last week, Nvidia announced contracts with Johnson & Johnson for the use of generative AI in surgery and with GE Healthcare to improve medical imaging. Healthcare developments at the 2024 GTC AI conference – which included the launch of around two dozen new AI-powered healthcare-focused tools – demonstrate how important medicine is to Nvidia’s future non-tech revenue opportunities .

“The reason Nvidia is so popular today is because it basically provided the installation and the technology to do something that you simply couldn’t do before, or if you had to do something like that you would probably take a lot more time “We need money and costs.” said Raj Joshi, technology analyst and senior vice president at Moody’s Ratings. “Healthcare, be it biotech, chemistry or drug discovery, is a very high-performing area.”

Nvidia shares 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 development process and even find applications for drugs that may not have produced results in the original disease for which they were developed.

“Over the last 18 months or so, we tend to think that it is more hope than hype because of the tangible results and then the very compelling use cases of how AI has helped in the pharmaceutical, medtech or biotech industries.” said Arda Ural, EY is the market leader in the healthcare and life sciences industry in America.

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

About 41 percent of biotech CEOs surveyed by EY in late 2023 said they are looking for “concrete” ways to use generative AI for their companies. “This is very high for my experience, which I have had in this industry for 30 years,” said Ural. “This is a truly unique capability that we are seeing in AI and is gaining adoption much more quickly than other technologies.”

Nvidia’s focus on healthcare at its conference was a doubling down on its long-held ambitions. During a conference call with investors in February, Nvidia mentioned several ways its technology is being adapted for the medical field. Companies like Recursive pharmaceuticals and Generate: Biomedicines have expanded their biomedical research using hyperscale or GPU-specialized cloud providers and need Nvidia’s 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, chief financial officer of Nvidia. “We have built deep expertise in healthcare over the last decade, creating the NVIDIA Clara healthcare platform and NVIDIA BioNeMo, a generative AI service to develop, customize and deploy foundational AI models for computational drug discovery.”

Last year, NVIDIA invested $50 million in Recursion for its drug discovery projects. Recursion feeds its biological and chemical data to train NVIDIA’s AI models on its cloud platform. The company has also worked with Roche Genentech to develop new drugs and better treatment protocols. In 2021 it also entered into a partnership with Schrödinger for drug research.

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

“It’s one thing to design semiconductors and computing platforms so that others can do something. But it’s a whole different thing when you can put together complete technology packages that you can sell to a customer,” said Joshi. “Let’s say if you’re a biotech company, you take all of Nvidia’s technology and just start working on it, rather than figuring out how can I use this information technology.”

Biotech-focused generative AI platforms can reduce costs for pharmaceutical companies beyond the drug development process. Many companies have outsourced their back-office processes for supply chain, financial and administrative functions, and manufacturing to save money. But with geopolitical tensions rising and emphasis on returning jobs to the U.S., moving jobs overseas has become an increasing 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 accelerate drug development, but it also helps reduce a company’s operating costs. This means you can allocate more capital to drug development and find more cures faster.”

The healthcare space is an example of how far a company that developed gaming graphics cards a decade ago has come. “To their credit, Jensen had the foresight back in 2012 when he saw some people actually using his graphics card at Stanford University to solve some types of math problems,” Joshi said. “He said, ‘You know what? This actually allows you to do what’s called general computing, you know, the things that we all do every day in a normal way.'”

But to fully realize the benefits of AI that are emerging in the healthcare sector, leaders will need more support from one of the largest workforces in the country. According to EY’s AI Anxiety in Business survey, more than two-thirds of health sciences and wellness employees have concerns about the use of AI, and 7 in 10 are worried about introducing AI in the workplace.

Nvidia has to compete with itself, analysts say

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