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June 14, 2024

Backend to Front End: NVIDIA Launches AI Microservices in Bid to Revolutionize Healthcare

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Medically Reviewed by
Updated On
September 17, 2024

NVIDIA, the technology company at the heart of the AI revolution, has recently launched over two dozen AI microservices for use in the healthcare industry.

According to a press release, the chipmaker unveiled a series of generative AI tools and software development kits in mid-March, 2024 to help healthcare enterprises develop drugs cheaper and faster, along with a list of other use cases.

With the AI market expected to hit $740 billion by 2030, and some analysts even estimating a ninefold increase to over $1 trillion in U.S. dollars, healthcare companies will have to adapt to artificial intelligence to stay competitive.1

Kimberly Powell, the vice president of healthcare at NVIDIA, expects AI to impact everything from drug discovery and med tech to treatment and diagnostics.

“For the first time in history, we can represent the world of biology and chemistry in a computer, making computer-aided drug discovery possible,” said Powell in the press release. “By helping healthcare companies easily build and manage AI solutions, we’re enabling them to harness the full power and potential of generative AI.”

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NVIDIA’s Vision For The Future of Healthcare

NVIDIA, a manufacturer of GPU computer chips with hundreds of data centers globally, is the backbone of AI technology.

With a market capitalization of 3 trillion and over a 200% stock price increase last year, the chip giant has ventured beyond computer hardware, software applications, and gaming, and is poised to play a critical role in the healthcare and biotechnology industries.

The company has made significant strides over the last few months, particularly within the pharmaceutical, biotech, and MedTech sectors.

Technology analyst Raj Joshi explained NVIDIA’s foundational role in the future of healthcare.

“The reason why Nvidia is so popular today is because it basically provided the plumbing and the technology for something that you could not do simply before or if you had to do something like this you would need probably several times more time, money and cost,” Joshi told CNBC. “Health care, whether it’s biotechnology, chemicals, or drug discovery is a very powerful area.”

NVIDIA Chief Financial Officer Colette Kress envisions the company as having a universal role in healthcare, from aiding in drug discovery and design to facilitating the invention of wearable devices.

“In healthcare, digital biology and generative AI are helping to reinvent drug discovery, surgery, medical imaging and wearable devices,” Kress told CNBC.

The company’s foray into healthcare began nearly a decade ago, Kress explained.

“We have built deep domain expertise in healthcare over the past decade, creating the NVIDIA Clara healthcare platform and NVIDIA BioNeMo, a generative AI service to develop, customize and deploy AI foundation models for computer-aided drug discovery,” said Kress.

On top of creating solutions for healthcare companies, NVIDIA has also invested in several, such as Recursion Pharmaceuticals and Nano-X Imaging.

The investments were a small portion of the roughly $20 billion in pharmaceutical AI deals that took place over the past year, according to a report by GlobalData.2

NVIDIA’s Software Solutions in the Spotlight

Although the chipmaker is known for its hardware, its software platforms are equally important.

CUDA-X, a software platform created by NVIDIA, allows computers to run AI microservices – such as complex AI models that require heavy computational workloads – from GPUs located at NVIDIA data centers.3

These microservices, accessed via the cloud, are potential game-changers for the healthcare industry.

On March 26, NVIDIA showcased 25 healthcare-oriented AI microservices at the GTC AI global conference.

Among these were healthcare-tailored AI tools like NIM™ AI – a suite of workflows and models that allows for the deployment of native cloud applications, particularly within the context of biotechnology and chemistry.

According to experts, such models can help predict how certain drugs affect the body, thus allowing companies to optimize drug development while reducing unnecessary costs during the research and development process.

“We care about fast and fast means in this industry, that we’ll be able to do more, and we know that drug discovery is essentially an infinite problem. You’re looking at a chemical space and 10 to the 60th power potential chemical compounds,” Powell explained.

Given the roughly 90% failure rate for drug trials, Powell believes that AI will boost the accuracy of predictive models and increase the success rate for pharma companies.

“With generative AI, we’re going to be able to not only generate more ideas and predict with better accuracy, but we’re also going to be able to model biology in new and exciting ways so that when we put a new chemical entity into the clinic, we have a higher success rate,” she said.

NVIDIA also showcased several software development kits and tools at the conference, such as Parabricks®, MONAI, NeMo™, Riva, and Metropolis, now available as NVIDIA CUDA-X™ microservices.

These tools enhance healthcare workflows for drug discovery, medical imaging, and genomics analysis.

Such applications offer numerous opportunities for pharmaceutical companies, doctors, and hospitals, including the ability to screen trillions of drug compounds, improve patient data collection for early disease detection and personalized treatment, and to develop smarter digital assistants.

The microservices listed featured several specific models for drug discovery, such as MolMIM for generative chemistry, ESMFold for protein structure prediction, and DiffDock to help researchers understand drug-target interactions.

The VISTA 3D microservice is another digital biology tool that creates 3D segmentation models, while the Universal DeepVariant microservice delivers up to 50 times faster genomic analysis compared to the standard CPU-based DeepVariant implementation.

Cadence Design Systems, a computational software company, has already integrated NVIDIA’s microservice BioNeMo into their Orion® molecular design platform to enhance AI-guided molecular discovery and lead optimization for drug development.

BioNeMo microservices, such as the MolMIM generative chemistry model and the AlphaFold-2 model for protein folding, help pharmaceutical researchers search through compounds and significantly enhance Orion’s capabilities.

“Our pharmaceutical and biotechnology customers require access to accelerated resources for molecular simulation,” Cadence Vice President Anthony Nicholl said. “By leveraging BioNeMo microservices, researchers can generate molecules that are optimized according to scientists’ specific needs.”

Drug developer Cognizant, like Cadence, also uses BioNeMo microservice to speed up drug development.4

Other large pharmaceutical and biotech companies such as Amgen, Astellas, DNA Nexus, Iambic Therapeutics, Recursion and Terray, and V7 have harnessed NVIDIA’s technology as well.

NVIDIA Announces Partnership with Leading Healthcare Companies

NVIDIA publicized several key partnerships with important players in the industry: Johnson & Johnson, GE Healthcare, and startup Hippocratic AI.

Each partnership represents a unique avenue by which the company can impact healthcare.

Pharma giant J&J, for instance, aims to leverage NVIDIA technology to improve surgical medicine, while GE Healthcare looks to advance its medical imaging software and research models.

Tim Schmid, Executive Vice President for J&J MedTech, said the partnership with NVIDIA is focused on optimizing decision-making and training within the surgical ecosystem. J&J also plans to leverage NVIDIA microservices to create medical devices that use AI for surgical applications.

He further predicted that AI would lead to a “more connected and personalized” healthcare industry.

“This future will be increasingly enabled by digital technologies that deliver efficiency, inform decision-making, and extend surgical training and education,” Schmid said in a press release.

“Our deep heritage in healthcare and digital ecosystem in surgery and NVIDIA’s AI platforms hold enormous potential to create a more connected surgical experience,” he continued.

NVIDIA is not just impacting what happens behind the scenes in the lab, but is also shaping the consumer end of the healthcare business.

For example, Hippocratic AI has developed AI-powered “healthcare agents” powered by NVIDIA in an effort to alleviate staffing shortages and streamline administrative functions.

Built on Hippocratic’s safety-focused LLM Polaris and integrated with NVIDIA’s technology stack, the conversational AI bots have demonstrated superior performance compared to other AI models and even human nurses in specific benchmarks, according to the company.

The primary role of the agents is to communicate with patients via phone or video and help with tasks like health risk assessments, chronic illness management, pre-op check-ins, and post-discharge follow-ups.

The key, according to the startup, is to ensure agents interact with patients in a natural and empathetic way.

Although there has been some hesitancy regarding replacing humans with AI, NVIDIA’s Kimberly Powell stressed that they will continue to work closely with Hippocratic AI to solve problems that arise.

“Voice-based digital agents powered by generative AI can usher in an age of abundance in healthcare, but only if the technology responds to patients as a human would,” Powell stated. “This type of engagement will require continued innovation and close collaboration with companies, such as Hippocratic AI, developing cutting-edge solutions.”

[signup]

Key Takeaways

  • Computer chip manufacturer NVIDIA leads the AI boom; sets its sights on the healthcare industry
  • The AI market could surpass $1 trillion by 2030
  • NVIDIA launches over two dozen AI microservices for healthcare, with applications in drug discovery, medical imaging, and genomics analysis.
  • NVIDIA’s microservices have already seen widespread adoption in the healthcare industry
  • AI-driven tools like NIM™ AI and BioNeMo™ enable pharmaceutical companies to accelerate drug discovery and optimize molecular design.
  • Partnerships with industry leaders like Johnson & Johnson and GE Healthcare show adoption of NVIDIA’s AI technology for unique use cases
  • Consumer-facing technology, such as digital healthcare agents developed by Hippocratic AI, is also being driven by NVIDIA technology

NVIDIA, the technology company at the heart of the AI revolution, has recently launched over two dozen AI microservices for use in the healthcare industry.

According to a press release, the chipmaker unveiled a series of generative AI tools and software development kits in mid-March, 2024 to help healthcare enterprises develop drugs more efficiently, along with a list of other use cases.

With the AI market expected to hit $740 billion by 2030, and some analysts even estimating a ninefold increase to over $1 trillion in U.S. dollars, healthcare companies may need to adapt to artificial intelligence to stay competitive.1

Kimberly Powell, the vice president of healthcare at NVIDIA, anticipates AI to influence various aspects of healthcare, including drug discovery and med tech.

“For the first time in history, we can represent the world of biology and chemistry in a computer, making computer-aided drug discovery possible,” said Powell in the press release. “By helping healthcare companies easily build and manage AI solutions, we’re enabling them to harness the full power and potential of generative AI.”

[signup]

NVIDIA’s Vision For The Future of Healthcare

NVIDIA, a manufacturer of GPU computer chips with hundreds of data centers globally, is a key player in AI technology.

With a market capitalization of 3 trillion and over a 200% stock price increase last year, the chip giant has ventured beyond computer hardware, software applications, and gaming, and is poised to play a significant role in the healthcare and biotechnology industries.

The company has made notable progress over the last few months, particularly within the pharmaceutical, biotech, and MedTech sectors.

Technology analyst Raj Joshi explained NVIDIA’s foundational role in the future of healthcare.

“The reason why Nvidia is so popular today is because it basically provided the plumbing and the technology for something that you could not do simply before or if you had to do something like this you would need probably several times more time, money and cost,” Joshi told CNBC. “Health care, whether it’s biotechnology, chemicals, or drug discovery is a very powerful area.”

NVIDIA Chief Financial Officer Colette Kress envisions the company as having a universal role in healthcare, from aiding in drug discovery and design to facilitating the invention of wearable devices.

“In healthcare, digital biology and generative AI are helping to reinvent drug discovery, surgery, medical imaging and wearable devices,” Kress told CNBC.

The company’s foray into healthcare began nearly a decade ago, Kress explained.

“We have built deep domain expertise in healthcare over the past decade, creating the NVIDIA Clara healthcare platform and NVIDIA BioNeMo, a generative AI service to develop, customize and deploy AI foundation models for computer-aided drug discovery,” said Kress.

On top of creating solutions for healthcare companies, NVIDIA has also invested in several, such as Recursion Pharmaceuticals and Nano-X Imaging.

The investments were a small portion of the roughly $20 billion in pharmaceutical AI deals that took place over the past year, according to a report by GlobalData.2

NVIDIA’s Software Solutions in the Spotlight

Although the chipmaker is known for its hardware, its software platforms are equally important.

CUDA-X, a software platform created by NVIDIA, allows computers to run AI microservices – such as complex AI models that require heavy computational workloads – from GPUs located at NVIDIA data centers.3

These microservices, accessed via the cloud, are potential game-changers for the healthcare industry.

On March 26, NVIDIA showcased 25 healthcare-oriented AI microservices at the GTC AI global conference.

Among these were healthcare-tailored AI tools like NIM™ AI – a suite of workflows and models that allows for the deployment of native cloud applications, particularly within the context of biotechnology and chemistry.

According to experts, such models can help predict how certain drugs may interact with the body, thus allowing companies to optimize drug development while managing costs during the research and development process.

“We care about fast and fast means in this industry, that we’ll be able to do more, and we know that drug discovery is essentially an infinite problem. You’re looking at a chemical space and 10 to the 60th power potential chemical compounds,” Powell explained.

Given the roughly 90% failure rate for drug trials, Powell believes that AI could enhance the accuracy of predictive models and potentially increase the success rate for pharma companies.

“With generative AI, we’re going to be able to not only generate more ideas and predict with better accuracy, but we’re also going to be able to model biology in new and exciting ways so that when we put a new chemical entity into the clinic, we have a higher success rate,” she said.

NVIDIA also showcased several software development kits and tools at the conference, such as Parabricks®, MONAI, NeMo™, Riva, and Metropolis, now available as NVIDIA CUDA-X™ microservices.

These tools enhance healthcare workflows for drug discovery, medical imaging, and genomics analysis.

Such applications offer numerous opportunities for pharmaceutical companies, doctors, and hospitals, including the ability to screen numerous drug compounds, improve patient data collection for early disease detection and personalized treatment, and to develop smarter digital assistants.

The microservices listed featured several specific models for drug discovery, such as MolMIM for generative chemistry, ESMFold for protein structure prediction, and DiffDock to help researchers understand drug-target interactions.

The VISTA 3D microservice is another digital biology tool that creates 3D segmentation models, while the Universal DeepVariant microservice delivers up to 50 times faster genomic analysis compared to the standard CPU-based DeepVariant implementation.

Cadence Design Systems, a computational software company, has already integrated NVIDIA’s microservice BioNeMo into their Orion® molecular design platform to enhance AI-guided molecular discovery and lead optimization for drug development.

BioNeMo microservices, such as the MolMIM generative chemistry model and the AlphaFold-2 model for protein folding, help pharmaceutical researchers search through compounds and significantly enhance Orion’s capabilities.

“Our pharmaceutical and biotechnology customers require access to accelerated resources for molecular simulation,” Cadence Vice President Anthony Nicholl said. “By leveraging BioNeMo microservices, researchers can generate molecules that are optimized according to scientists’ specific needs.”

Drug developer Cognizant, like Cadence, also uses BioNeMo microservice to support drug development.4

Other large pharmaceutical and biotech companies such as Amgen, Astellas, DNA Nexus, Iambic Therapeutics, Recursion and Terray, and V7 have harnessed NVIDIA’s technology as well.

NVIDIA Announces Partnership with Leading Healthcare Companies

NVIDIA publicized several key partnerships with important players in the industry: Johnson & Johnson, GE Healthcare, and startup Hippocratic AI.

Each partnership represents a unique avenue by which the company can impact healthcare.

Pharma giant J&J, for instance, aims to leverage NVIDIA technology to improve surgical medicine, while GE Healthcare looks to advance its medical imaging software and research models.

Tim Schmid, Executive Vice President for J&J MedTech, said the partnership with NVIDIA is focused on optimizing decision-making and training within the surgical ecosystem. J&J also plans to leverage NVIDIA microservices to create medical devices that use AI for surgical applications.

He further predicted that AI would lead to a “more connected and personalized” healthcare industry.

“This future will be increasingly enabled by digital technologies that deliver efficiency, inform decision-making, and extend surgical training and education,” Schmid said in a press release.

“Our deep heritage in healthcare and digital ecosystem in surgery and NVIDIA’s AI platforms hold enormous potential to create a more connected surgical experience,” he continued.

NVIDIA is not just impacting what happens behind the scenes in the lab, but is also shaping the consumer end of the healthcare business.

For example, Hippocratic AI has developed AI-powered “healthcare agents” powered by NVIDIA in an effort to alleviate staffing shortages and streamline administrative functions.

Built on Hippocratic’s safety-focused LLM Polaris and integrated with NVIDIA’s technology stack, the conversational AI bots have demonstrated superior performance compared to other AI models and even human nurses in specific benchmarks, according to the company.

The primary role of the agents is to communicate with patients via phone or video and help with tasks like health risk assessments, chronic illness management, pre-op check-ins, and post-discharge follow-ups.

The key, according to the startup, is to ensure agents interact with patients in a natural and empathetic way.

Although there has been some hesitancy regarding replacing humans with AI, NVIDIA’s Kimberly Powell stressed that they will continue to work closely with Hippocratic AI to address challenges that arise.

“Voice-based digital agents powered by generative AI can usher in an age of abundance in healthcare, but only if the technology responds to patients as a human would,” Powell stated. “This type of engagement will require continued innovation and close collaboration with companies, such as Hippocratic AI, developing cutting-edge solutions.”

[signup]

Key Takeaways

  • Computer chip manufacturer NVIDIA leads the AI boom; sets its sights on the healthcare industry
  • The AI market could surpass $1 trillion by 2030
  • NVIDIA launches over two dozen AI microservices for healthcare, with applications in drug discovery, medical imaging, and genomics analysis.
  • NVIDIA’s microservices have already seen widespread adoption in the healthcare industry
  • AI-driven tools like NIM™ AI and BioNeMo™ enable pharmaceutical companies to accelerate drug discovery and optimize molecular design.
  • Partnerships with industry leaders like Johnson & Johnson and GE Healthcare show adoption of NVIDIA’s AI technology for unique use cases
  • Consumer-facing technology, such as digital healthcare agents developed by Hippocratic AI, is also being driven by NVIDIA technology
The information in this article is designed for educational purposes only and is not intended to be a substitute for informed medical advice or care. This information should not be used to diagnose or treat any health problems or illnesses without consulting a doctor. Consult with a health care practitioner before relying on any information in this article or on this website.

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1. Artificial Intelligence market size 2024 | Statista. Statista. Published May 28, 2024. https://www.statista.com/statistics/941835/artificial-intelligence-market-size-revenue-comparisons/

2. Hanson I. Nvidia has invested in five AI companies: which are they? Verdict. https://www.verdict.co.uk/nvidia-has-invested-in-five-ai-companies-which-are-they/?cf-view&cf-click. Published February 22, 2024.

3.Witt S. How Jensen Huang’s Nvidia is powering the A.I. Revolution. The New Yorker. https://www.newyorker.com/magazine/2023/12/04/how-jensen-huangs-nvidia-is-powering-the-ai-revolution. Published November 27, 2023.

4. Deswal P, Deswal P. NVIDIA doubles down on AI in healthcare with drug discovery deals. Pharmaceutical Technology. https://www.pharmaceutical-technology.com/news/nvidia-doubles-down-on-ai-in-healthcare-with-drug-discovery-deals/?cf-view&cf-minimized&cf-view. Published March 19, 2024.

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