Since last year, has generated shockwaves in many industries 鈥� with healthcare being no exception.
Boasting a market cap of $2.92trn, the tech powerhouse is one of the most valuable companies in the world 鈥� and even briefly occupied the global top spot last month. Shares in NVIDIA鈥� up about 785% since the start of 2023鈥� paint the rise of the company and the emergence of AI.
Alongside this, NVIDIA has been expanding its presence in the healthcare sector, with activities ranging from developing drug discovery applications such as the BioNeMo tool kits to partnerships with heavyweights such as MedTech for surgical technologies.
In an exclusive interview with Pharmaceutical Technology, NVIDIA鈥檚 EMEA business development lead for healthcare and life sciences David Ruau, talks about the company鈥檚 ever-strengthening affinity with healthcare, and how the future of the technology鈥檚 use in the sector might look amid a dynamic regulatory environment and changing public perception.
This interview has been edited for length and clarity.
Robert Barrie [RB]: NVIDIA has made plenty of in-roads into healthcare recently. Where are the biggest opportunities in this sector?
David Ruau [DR]: I would rephrase the premise of the question. I would instead say that healthcare made in-roads into AI for treating patients, inventing new drugs, and developing new technologies in medical devices. There is a massive amount of data generated in healthcare, and that naturally led to the need to have an accelerated computing platform. And yes, NVIDIA has been ideally placed to fulfil this particular market segment because of our graphics processing unit (GPU) capabilities. The GPU, being a processing unit that allows parallel processing of data on a massive scale, is a game-changing approach. It is not that we pushed into the healthcare domain for AI, it was an emerging market, and we grew with it.
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A good use case for us has been digital radiology and medical imaging. Medical imaging has been one of the very first sectors of the healthcare market that we addressed, and we made very strong partnerships in this space. AI has been very important for image processing. Applications for digital radiology popped up and became much more mainstream鈥攂eing able to process images such as the segmentation of organs and bones. That’s what our partners have developed. And yes, they needed a computing platform which was fit for purpose, and that was by NVIDIA.
RB: NVIDIA has partnerships with big pharma such as Amgen and Genentech. Do you think the majority of drugs arriving to market in the future will be designed by AI?
DR: The classic question! A drug is never designed by one single software. If readers should take away one thing from this interview, it鈥檚 that it takes a large group of individuals, skills, and know-how to deliver a drug to patients. It鈥檚 not only a story about algorithms. We can鈥檛 just generate a prompt (鈥渢he greatest prompt in history!鈥�) and ask it to create a new drug for a particular disease and have it go and do everything: target ID, design, animal testing, toxicity, and submission to the FDA. At least for now, it does not work like that.
AI provides tools and increases our capacity to process data. So instead of searching and reading every single paper, you can ask an AI agent to summarise a lot of them. It helps humans make sense of such a vast volume of information and literature. But designing new drugs is a really complex endeavour. AI agents can help in some tasks but are not the only tool.
AI is speeding up the drug development process by simplifying some steps to allow better choices. But it’s not a one-size-fits-all solution. 聽
RB: Where do you see regulation with AI heading, and will it facilitate or hamper its long-term use in healthcare?
DR: At NVIDIA, we pay very careful attention to this particular topic. We think it’s a healthy debate to have within the society. People do wonder, what is going on with a particular technology. And it’s part of the process to demystify it. The progress made by these AI agents is quite surprising and it鈥檚 normal that people who are not close to the subject 鈥� which is in a way, the vast majority of us 鈥� wonder about the consequences. The debate around the regulation of AI is helping to demystify the topics. A regulation coming into place is the conclusion of reflection from the society, and that is a very healthy thing.
It will help the adoption of AI, and help guide us in the right direction. And this happens whether a company likes it or not. We need this reflection to be able to progress in our research to create the best algorithm for the job.
RB: A recent survey showed that the majority of US employees have concerns about AI. How close is healthcare, at the level of medical staff, to accepting AI?
DR: We spend quite a lot of energy in this space [of demystification]. There are already quite a few companies developing tools to simplify the workload and reduce the burden on the medical staff. One example is Hippocratic AI 鈥� a company we highlighted at our last GTC conference. Hippocratic AI is a virtual interface, powered by a large language model, which helps patients to adhere to their therapeutic regimen. Not only does it alleviate the burden of needing medical staff to do that, but it also helps people to be treated at home.
Virtual assistants are not a new concept, but finally, we are beginning to see them being implemented in real life; for example in AI applications for taking medical notes and saving time for doctors, and it can go even further nowadays. We also see some innovation along those lines with AI agents that are used as 鈥榗opilots鈥� for a medical doctor, the latter still being the one in charge.
RB: How will AI in healthcare look in 2050?
DR: Nobody can predict anything with certainty, but I think AI will be in every application we use. It will be the new type of 鈥榯ransaction鈥�. Jensen Huang [NVIDIA鈥檚 CEO] described this concept in his keynote this year at GTC. It is a new commodity. AI engines are basically producing tokens, interpreting what you say, and answering questions. It can be applied to many domains of data coming in and information coming out, and that’s basically what we describe as AI factories.
Research is progressing, and the future is looking very bright for this technology in healthcare. It will be pervasive, both in the daily lives of patients and in new drug research such as NVIDIA鈥檚 BioNeMo [a generative AI platform for drug discovery]. It comes back to what I said at the start, AI expands our available toolbox. 聽
The future will be based on the present, and the present is going in this particular direction at the moment. [AI factories] are powering all the tools that we use every day. It’s a new 鈥渋Phone鈥� moment for AI, and it’s not only benefiting NVIDIA.
