Dell Tech World 2026: Eli Lilly and Company Scales AI-Driven Drug Discovery and Manufacturing with Dell

• Dell Technologies provides trusted AI infrastructure and storage that supports Lilly’s work in drug discovery and global manufacturing operations
• A proven foundation of Dell compute and storage underpins work across scientific computing, AI training, and production capabilities

For 15 years, Dell Technologies has been supporting Eli Lilly and Company (Lilly) as the company works to get medicines to patients faster.Today, Lilly uses Dell compute and storage infrastructure to power operations from the research lab to the factory floor.

Why it matters
The medicines Lilly is developing and manufacturing today, including those to help address obesity, Alzheimer’s and cancer, are reaching more people than at any point in the company’s history. Technology is a key lever for closing the gap between a scientific breakthrough and a medicine that reaches a patient. 

Dell infrastructure has helped Lilly move from experimentation to production across scientific computing, manufacturing and now AI at scale. AI investment can translate into measurable outcomes: improved drug discovery cycles, higher R&D productivity and manufacturing efficiency built to meet global demand, all without compromising quality or regulatory compliance.

Dell infrastructure fuels research computing and AI training
Powering multiple AI and HPC environments at Lilly, Dell PowerEdge servers support high-volume scientific computation, including AI-driven protein analysis to understand how proteins interact with drug candidates, molecular modeling to simulate how potential drug molecules behave and interact at the atomic level, and related workloads. This allows researchers to evaluate drug candidates computationally before advancing them into physical lab work, with the goal of identifying better candidates and improving timelines.

When Lilly began building AI training clusters three years ago, a deliberate proof-of-concept to validate that it could operate large-scale AI training in house, Dell provided hardware, architecture consulting and integration support. As Lilly accelerated its AI adoption and built LillyPod—its powerful AI supercomputer—Dell’s storage infrastructure played a critical role. Delivering nearly two terabytes per second of read bandwidth across the cluster ensures that its more than 1,000 GPUs are fed data fast enough so LillyPod can train large AI models at full capacity. 

Dell provides compute and storage backbone for manufacturing footprint
Beyond research, Dell provides on‑premises compute, storage and backup across Lilly’s manufacturing sites. Dell PowerEdge, Dell PowerStore and Dell PowerProtect systems support and protect production data and manufacturing workflows, providing a common architecture that can be replicated as new facilities come online.

Dell AI infrastructure also supports digital twins and simulation, allowing Lilly to test manufacturing process changes virtually before they reach the production floor, while AI-driven visual inspection on production lines can support Lilly’s standards across every facility.

Preparing for the next era of AI
As organizations scale AI across research, manufacturing and enterprise operations, the underlying infrastructure must evolve to keep pace. Dell offers the foundation for that next step — from storage with proactive and predictive monitoring to infrastructure designed to support agentic AI systems and self-healing operations that can detect, diagnose and resolve issues with increasing autonomy. These capabilities help organizations move faster, work better and operate confidently as AI workloads grow.

Perspectives
“When manufacturing stops, it affects our ability to make medicine more efficiently for patients,” said Diogo Rau, EVP and CIDO, Eli Lilly and Company. “We’ve never been more dependent on technology — components may fail, but the system cannot. Dell has been the infrastructure underneath that operation for more than 15 years.”

“The work Lilly is doing spans the full lifecycle of a medicine, from AI-powered discovery through worldwide manufacturing.” said Arthur Lewis, president, infrastructure solutions group, Dell Technologies. “Today, we’re feeding more than 1,000 GPUs at nearly two terabytes per second so LillyPod can train the models behind some of the most important medicines in the world. The infrastructure has changed dramatically — the commitment hasn’t. When the work matters this much, you build for what’s next, not just what’s needed today.”