{"id":143269,"date":"2025-11-20T09:36:09","date_gmt":"2025-11-20T09:36:09","guid":{"rendered":"https:\/\/www.newsbeep.com\/il\/143269\/"},"modified":"2025-11-20T09:36:09","modified_gmt":"2025-11-20T09:36:09","slug":"why-big-pharma-is-teaming-up-with-ai-giants-to-speed-up-drug-discovery-and-make-work-easier-for-health-care-workers","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/il\/143269\/","title":{"rendered":"Why big pharma is teaming up with AI giants to speed up drug discovery and make work easier for health care workers"},"content":{"rendered":"\n

AI chip maker Nvidia\u2019s fresh partnerships with Eli Lilly<\/a> and Johnson & Johnson point to a broader trend in the pharmaceutical industry, where tie-ups with AI giants are intended to speed up drug discovery and make work easier for health care workers.<\/p>\n

\u201cWe want everything to move really, really fast and we want to get a new molecule that\u2019s going to change the world in another six months,\u201d says Diogo Rau, Eli Lilly\u2019s chief information and digital officer. But despite that urgency, Rau acknowledges that science still takes time. New drug discovery can take well over a decade and well north of $2 billion<\/a>, on average, before they can obtain regulatory approval.<\/p>\n

Rau and Eli Lilly are betting that AI can speed things up. In late October, the company announced plans to create a new Nvidia-chip powered \u201csupercomputer\u201d and \u201cAI factory\u201d that will go online by early 2026, allowing scientists to utilize models trained on millions of experiments to test new therapies. Some of the proprietary AI models will be made available on Lilly TuneLab, a platform that Lilly launched<\/a> in September that gives smaller biotech firms access to AI models that have been trained on the larger firm\u2019s research.<\/p>\n

Separately, J&J on the same day, announced its own partnership with Nvidia, relying on the AI company\u2019s foundation models to create simulated environments for surgical teams to plan their kidney stone procedures. J&J says this application of so-called \u201cphysical AI\u201d will optimize the process to map out procedures, make it easier to train doctors, and will result in more consistent and better clinical outcomes for patients.<\/p>\n

\u201cThere\u2019s only so many hours in the day,\u201d says Neda Cvijetic, senior vice president and global head of robotics and digital research and development for J&J\u2019s MedTech division. \u201cSometimes it\u2019s super helpful to see that difficult case in a very realistic, simulated environment first, to help best prepare.\u201d<\/p>\n

The pharmaceutical and medical products industries can potentially unlock tens of billions in value<\/a> from investments in generative AI alone if the sector is successfully able to deploy the technology to improve drug discovery, speed up clinical trials and the regulatory process, and more adeptly market and administer new treatments to the right patients.<\/p>\n

But there still remains a bit of a gap between the highly specific AI use cases that are most powerful for the life sciences industry and the technologies that AI hyperscalers offer today. Recently, solutions have become more tailored for the sector, partly reflected by partnerships emerging between Eli Lilly and J&J with Nvidia, and also Novo Nordisk\u2019s relationship<\/a> with Anthropic and Amazon<\/a> Web Services, as well as AI hyperscaler\u2019s own efforts. Last month, Anthropic launched<\/a> Claude for Life Sciences, which was designed to speed up R&D.<\/p>\n

Delphine Zurkiya, a senior partner in both the life sciences and technology practices at McKinsey<\/a>, said that until recently, AI hyperscalers were spending most of their time working with chief information officers. But as AI budgets have expanded and use cases proliferated, there\u2019s been more interest in business-specific applications for those technologies all across the pharmaceuticals industry.<\/p>\n

\u201cThe business leaders have less patience with generic platforms,\u201d says Zurkiya. \u201cThey\u2019ll want something that\u2019s customized to what they need.\u201d<\/p>\n

\u201cWe don\u2019t even just want the life sciences knowledge model,\u201d says Rau. \u201cWe want one that knows Lilly.\u201d<\/p>\n

Lilly\u2019s Chief AI Officer Thomas Fuchs adds that the greatest AI advancements will come from the combination of the company\u2019s trove of proprietary data, the compute investments Lilly is making to train large foundation models, and then deploying that tech to thousands of chemists and biologists, who can use those AI tools to make new discoveries.<\/p>\n

Fuchs says that precise science can\u2019t be echoed for every large pharmaceutical company. That would be like an astronomer relying on a telescope sold by a big-box retailer. \u201cWe are building a space-based telescope,\u201d says Fuchs.<\/p>\n

Kimberly Powell, a VP of healthcare at Nvidia who worked on the J&J surgical AI project, touts the potential for physical AI to tap the advancements of computer vision technology and large language models to turn AI into physical workers.<\/p>\n

While that may raise questions about the impact of AI on the job of a surgeon, Powell points to data from the World Health Organization that projects<\/a> a shortfall of 11 million health workers globally by 2030. She also predicts that a new operating room\u2014a hybrid mix of human surgeons working alongside physical robots and digital agents\u2014could result in breakthroughs in new procedure techniques.<\/p>\n

\u201cThere is a future goal of how we go from robotic-assisted surgery to robotic surgery, where the robot is actually taking some action on its own,\u201d says Powell. \u201cWe\u2019re laying all the groundwork to do that.\u201d<\/p>\n

John Kell<\/p>\n

Send thoughts or suggestions to\u00a0CIO Intelligence here<\/a>.<\/p>\n

This story was originally featured on Fortune.com<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"AI chip maker Nvidia\u2019s fresh partnerships with Eli Lilly and Johnson & Johnson point to a broader trend…\n","protected":false},"author":2,"featured_media":143270,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[34],"tags":[9211,88187,4676,8829,2495,163,3078,88188,521,85,46,4272,4136,27215],"class_list":{"0":"post-143269","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-healthcare","8":"tag-ai-company","9":"tag-diogo-rau","10":"tag-drug-discovery","11":"tag-eli-lilly","12":"tag-generative-ai","13":"tag-health","14":"tag-health-care-workers","15":"tag-health-workers","16":"tag-healthcare","17":"tag-il","18":"tag-israel","19":"tag-johnson-johnson","20":"tag-nvidia","21":"tag-pharmaceutical-industry"},"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/posts\/143269","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/comments?post=143269"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/posts\/143269\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/media\/143270"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/media?parent=143269"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/categories?post=143269"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/tags?post=143269"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}