{"id":4487,"date":"2026-02-26T20:39:32","date_gmt":"2026-02-26T20:39:32","guid":{"rendered":"https:\/\/salarydistribution.com\/machine-learning\/2026\/02\/26\/now-live-the-worlds-most-powerful-ai-factory-for-pharmaceutical-discovery-and-development\/"},"modified":"2026-02-26T20:39:32","modified_gmt":"2026-02-26T20:39:32","slug":"now-live-the-worlds-most-powerful-ai-factory-for-pharmaceutical-discovery-and-development","status":"publish","type":"post","link":"https:\/\/salarydistribution.com\/machine-learning\/2026\/02\/26\/now-live-the-worlds-most-powerful-ai-factory-for-pharmaceutical-discovery-and-development\/","title":{"rendered":"Now Live: The World\u2019s Most Powerful AI Factory for Pharmaceutical Discovery and Development"},"content":{"rendered":"<div>\n<p><!-- OneTrust Cookies Consent Notice start for nvidia.com --><\/p>\n<p><!-- OneTrust Cookies Consent Notice end for nvidia.com --><\/p>\n<p><!-- Broadcast could not find a linked parent for the canonical. --><\/p>\n<p>\t<!-- This site is optimized with the Yoast SEO Premium plugin v27.0 (Yoast SEO v27.0) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ --><br \/>\n\t<title>Now Live: Lilly AI Factory for Pharmaceutical Discovery and Development | NVIDIA Blog<\/title><\/p>\n<p>\t<!-- \/ Yoast SEO Premium plugin. --><\/p>\n<p><!-- Stream WordPress user activity plugin v4.1.1 --><\/p>\n<p>\t\t\t\t<!-- Hotjar Tracking Code for NVIDIA --><\/p>\n<p><img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/www.nvidia.com\/content\/dam\/1x1-00000000.png\" width=\"1\" height=\"1\" alt=\"country_code\"><\/p>\n<div id=\"page\" class=\"hfeed site\">\n\t<a class=\"skip-link screen-reader-text\" href=\"#content\">Skip to content<\/a><\/p>\n<p>\t<!-- #masthead --><\/p>\n<div class=\"full-width-layout light\">\n<div class=\"full-width-layout__hero light\">\n<div class=\"full-width-layout__hero-content light\">\n<div class=\"full-width-layout__hero-content__inner light\">\n<p>\n\t\t\t\t\tBuilt with over 1,000 NVIDIA Blackwell Ultra GPUs, LillyPod is now online to power scientific research and supercharge the future of medicine.\t\t\t\t<\/p>\n<\/p><\/div>\n<\/p><\/div>\n<\/p><\/div>\n<div class=\"full-width-layout__sections\">\n<div class=\"full-width-layout__article-copy-section light\">\n<div class=\"full-width-layout__copy\">\n<p>Saving and improving lives \u2014 that most human endeavor \u2014 just got a super-computational boost.\u00a0<\/p>\n<p>Lilly this week launched the most powerful AI factory wholly owned and operated by a pharmaceutical company to help its teams make meaningful medical advancements faster, more accurately and at unprecedented scale. Dubbed LillyPod, it\u2019s the world\u2019s first <a href=\"https:\/\/www.nvidia.com\/en-us\/data-center\/dgx-superpod\/\" target=\"_blank\" rel=\"noopener noreferrer\">NVIDIA DGX SuperPOD<\/a> with <a href=\"https:\/\/www.nvidia.com\/en-us\/data-center\/dgx-b300\/\" target=\"_blank\" rel=\"noopener noreferrer\">DGX B300 systems<\/a>.\u00a0<\/p>\n<p>Powered by a DGX SuperPOD with 1,016 NVIDIA Blackwell Ultra GPUs, Lilly\u2019s AI factory delivers more than 9,000 petaflops of AI performance. It was assembled in just four months.<\/p>\n<\/div>\n<\/div>\n<div class=\"full-width-layout__standard-video-section\">\n\t<video class=\"full-width-layout__video js-responsive-video\" autoplay muted loop playsinline data-sources='{\"mobile\":[{\"src\":\"https:\/\/blogs.nvidia.com\/wp-content\/uploads\/2026\/02\/ribbon-cutting-combo.mp4\",\"type\":\"video\/mp4\"}],\"tablet\":[{\"src\":\"https:\/\/blogs.nvidia.com\/wp-content\/uploads\/2026\/02\/ribbon-cutting-combo.mp4\",\"type\":\"video\/mp4\"}],\"desktop\":[{\"src\":\"https:\/\/blogs.nvidia.com\/wp-content\/uploads\/2026\/02\/ribbon-cutting-combo.mp4\",\"type\":\"video\/mp4\"}]}'>Your browser does not support the video tag.<\/video><\/p>\n<p>\n\t\t\t<span class=\"full-width-layout__media-caption-callout\"><br \/>\n\t\t\tLillyPod was inaugurated Wednesday at a ribbon-cutting in Indianapolis.\t\t<\/span><\/p>\n<\/div>\n<div class=\"full-width-layout__article-copy-section light\">\n<div class=\"full-width-layout__copy\">\n<p>\u201cIt\u2019s a big day for us with the supercomputer coming on board, but it\u2019s a day 150 years in the making,\u201d said Diogo Rau, executive vice president and chief information and digital officer at Lilly. \u201cLillyPod is a powerful symbol of who we are and why we do this work: to make life better for people around the world. We are, right here, right now, at the right moment to advance biology in a way that has just never been done before.\u201d<\/p>\n<\/div>\n<\/div>\n<div class=\"full-width-layout__article-copy-section light\">\n<h2 class=\"full-width-layout__heading\">Step Behind the Scenes of the LillyPod<\/h2>\n<div class=\"full-width-layout__copy\">\n<p>Computational power that once required 7 million Cray supercomputers now fits inside a single NVIDIA GPU \u2014 and LillyPod contains more than 1,000 of them. This infrastructure enables Lilly\u2019s genomics team to harness 700 terabytes of data using over 290 terabytes of high-bandwidth GPU memory.\u00a0<\/p>\n<p>\u201cComputation is at the heart of biology and it is at the heart of science,\u201d said Thomas Fuchs, senior vice president and chief AI officer at Lilly. \u201cBeing able to compute at scale is not something optional for a company like ours, it is absolutely necessary. So we are building the computational future of medicine and you see that in all areas along the pharmaceutical value chain.\u201d<\/p>\n<\/div>\n<\/div>\n<div class=\"full-width-layout__full-width-image-section\">\n\t\t\t<img decoding=\"async\" width=\"2048\" height=\"455\" src=\"https:\/\/blogs.nvidia.com\/wp-content\/uploads\/2026\/02\/Lilly-AI-Factory_triptych1-scaled.png\" class=\"full-width-layout__image\" alt=\"\" loading=\"lazy\">\n\t<\/div>\n<div class=\"full-width-layout__article-copy-section light\">\n<div class=\"full-width-layout__copy\">\n<p>Lilly\u2019s AI factory is set to support the large-scale training of protein diffusion models, small-molecule <a href=\"https:\/\/blogs.nvidia.com\/blog\/what-are-graph-neural-networks\/\" target=\"_blank\" rel=\"noopener noreferrer\">graph neural network<\/a> models and genomics <a href=\"https:\/\/blogs.nvidia.com\/blog\/what-are-foundation-models\/\" target=\"_blank\" rel=\"noopener noreferrer\">foundation models<\/a>.<\/p>\n<p>NVIDIA\u2019s full-stack AI factory architecture offered with NVIDIA DGX SuperPOD \u2014 including accelerated computing, <a href=\"https:\/\/www.nvidia.com\/en-us\/networking\/spectrumx\/\" target=\"_blank\" rel=\"noopener noreferrer\">NVIDIA Spectrum-X Ethernet<\/a> networking and optimized AI software \u2014 provides a secure, scalable platform for the highly regulated workflows of healthcare and life sciences.\u00a0<\/p>\n<p><a href=\"https:\/\/www.nvidia.com\/en-us\/data-center\/mission-control\/\" target=\"_blank\" rel=\"noopener noreferrer\">NVIDIA Mission Control<\/a> software allows Lilly to manage its DGX SuperPOD, orchestrate workloads, monitor performance and automate AI operations securely and efficiently.<\/p>\n<p>The supercomputer\u2019s nearly 5,000 connections are built with more than 1,000 pounds of fiber cables. Lilly aims for its new AI supercomputing infrastructure to run on 100% renewable electricity by 2030, using efficient liquid cooling and minimal incremental energy impact.<\/p>\n<\/div>\n<\/div>\n<div class=\"full-width-layout__full-width-image-section\">\n\t\t\t<img decoding=\"async\" width=\"2048\" height=\"455\" src=\"https:\/\/blogs.nvidia.com\/wp-content\/uploads\/2026\/02\/Lilly-AI-Factory_triptych2-scaled.png\" class=\"full-width-layout__image\" alt=\"\" loading=\"lazy\">\n\t<\/div>\n<div class=\"full-width-layout__article-copy-section light\">\n<h2 class=\"full-width-layout__heading\">Advancing Foundation Models, Physical and Agentic AI\u00a0<\/h2>\n<div class=\"full-width-layout__copy\">\n<p>LillyPod is more than a tool \u2014 it\u2019s a new scientific instrument that brings together proprietary data and advanced AI models.\u00a0<\/p>\n<p>With this foundation, Lilly teams can analyze genomes, explore billions of chemical possibilities and apply AI across clinical development and manufacturing to design better trials, optimize production and accelerate decision\u2011making. Together, these capabilities enable faster, more precise and more scalable creation and delivery of medicines.<\/p>\n<p>\u201cLillyPod will usher in a new era of AI-driven drug discovery,\u201d said Tim Coleman, senior vice president and chief technology officer at Lilly. \u201cWe believe that computation is foundational to science and that Lilly patients deserve every advantage that we can give them.\u201d<\/p>\n<\/div>\n<\/div>\n<div class=\"full-width-layout__full-width-video-section\">\n\t\t\t<video class=\"full-width-layout__video\" autoplay muted loop playsinline><\/p>\n<p>Your browser does not support HTML5 video.<\/p>\n<p>\t\t<\/video><\/p><\/div>\n<div class=\"full-width-layout__article-copy-section light\">\n<div class=\"full-width-layout__copy\">\n<p>Select models will be made available through Lilly TuneLab, an AI and machine learning platform that provides biotech companies with access to drug discovery models built on proprietary Lilly data generated at a cost of over $1 billion.\u00a0<\/p>\n<p>As the first drug discovery platform with plans to offer both Lilly models and <a href=\"https:\/\/www.nvidia.com\/en-us\/industries\/healthcare-life-sciences\/biopharma\/\" target=\"_blank\" rel=\"noopener noreferrer\">NVIDIA BioNeMo<\/a> open foundation models for healthcare and life sciences, TuneLab uses a federated learning infrastructure built on <a href=\"https:\/\/developer.nvidia.com\/flare\" target=\"_blank\" rel=\"noopener noreferrer\">NVIDIA FLARE<\/a>, which enables biotech companies to tap into powerful proprietary AI models while keeping their data private and separate from other users. As more companies participate, the models improve, benefitting all users and further expanding AI access for the biotech ecosystem.<\/p>\n<\/div>\n<\/div>\n<div class=\"full-width-layout__full-width-video-section\">\n\t\t\t<video class=\"full-width-layout__video\" autoplay muted loop playsinline><\/p>\n<p>Your browser does not support HTML5 video.<\/p>\n<p>\t\t<\/video><\/p><\/div>\n<div class=\"full-width-layout__article-copy-section light\">\n<div class=\"full-width-layout__copy\">\n<p>Historically, drug discovery has been constrained by the physical limits of the wet lab. Even highly productive teams can typically analyze roughly 2,000 molecular ideas per target per year, because each experiment requires physical synthesis and testing.\u00a0<\/p>\n<p>\u201cNow the supercomputer center essentially just breaks the physical limit [of the wet lab],\u201d said Yue Wang Webster, vice president of research and development informatics at Lilly. \u201cNow in the dry lab, you can test billions of molecule ideas at your fingertips.\u201d<\/p>\n<p>LillyPod removes this constraint by creating a computational dry lab at massive scale, where scientists can simulate and evaluate billions of molecular hypotheses in parallel before committing to physical experiments.\u00a0<\/p>\n<p>With its internal AI platforms, Lilly employees can also use LillyPod to build chatbots, agentic workflows and research lab agents without reinventing the wheel.<\/p>\n<\/div>\n<\/div>\n<div class=\"full-width-layout__standard-image-section\">\n\t\t\t<img decoding=\"async\" width=\"2048\" height=\"1365\" src=\"https:\/\/blogs.nvidia.com\/wp-content\/uploads\/2026\/02\/Lilly-AI-Factory_2R7A2042-scaled.jpg\" class=\"full-width-layout__image\" alt=\"\" loading=\"lazy\">\n\t<\/div>\n<div class=\"full-width-layout__article-copy-section light\">\n<div class=\"full-width-layout__copy\">\n<p>By combining science, data and compute power, Lilly and NVIDIA are breaking new ground for AI in life sciences.<\/p>\n<p>\u201cThis machine is exactly how AI should be used,\u201d said Fuchs. \u201cIt should be used for science. It should be used to lessen suffering and improve the human condition.\u201d<\/p>\n<p>Hear from Lilly at <a href=\"https:\/\/www.nvidia.com\/gtc\/?ncid=prsy-146963\" target=\"_blank\" rel=\"noopener noreferrer\">NVIDIA GTC<\/a> in the following sessions:\u00a0<\/p>\n<p><i>Learn more about Lilly\u2019s collaboration with NVIDIA on <\/i><a href=\"https:\/\/blogs.nvidia.com\/blog\/lilly-ai-factory-nvidia-blackwell-dgx-superpod\/\" target=\"_blank\" rel=\"noopener noreferrer\"><i>this AI factory<\/i><\/a><i> and an upcoming <\/i><a href=\"https:\/\/nvidianews.nvidia.com\/news\/nvidia-and-lilly-announce-co-innovation-lab-to-reinvent-drug-discovery-in-the-age-of-ai\" target=\"_blank\" rel=\"noopener noreferrer\"><i>co-innovation AI lab<\/i><\/a><i>.\u00a0<\/i><\/p>\n<\/div>\n<\/div>\n<\/div><\/div>\n<p><!-- #colophon --><\/p>\n<\/div>\n<p><!-- #page --><\/p>\n<p><!-- #has-highlight-and-share -->\t\t<\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>https:\/\/blogs.nvidia.com\/blog\/lilly-ai-factory-live\/<\/p>\n","protected":false},"author":0,"featured_media":4488,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[3],"tags":[],"_links":{"self":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/posts\/4487"}],"collection":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/comments?post=4487"}],"version-history":[{"count":0,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/posts\/4487\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/media\/4488"}],"wp:attachment":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/media?parent=4487"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/categories?post=4487"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/tags?post=4487"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}