Eli Lilly and NVIDIA Announce Partnership to Build Advanced AI Supercomputer

Pharmaceutical giant Eli Lilly and technology firm NVIDIA have disclosed a collaboration to construct a new supercomputing system. The project is considered one of the largest Artificial Intelligence (AI) partnerships within the pharmaceutical sector to date, designed to hasten the discovery process and reduce the development timeframe for novel medicines.

The computing system, which will operate on renewable electricity, is scheduled to be housed within Lilly facilities. Utilizing more than a thousand Graphics Processing Units (GPUs), the installation is set to function as a powerful computational infrastructure capable of managing the entire AI lifecycle, from training to deployment.

1. Breakthrough Application in Life Sciences

This formidable computing capability will enable researchers to train AI models on millions of experimental data points, allowing for the rapid identification of potential therapeutic compounds.

Select AI models will be integrated into Lilly TuneLab, the company’s $1 billion AI/Machine Learning (ML) drug discovery platform. This platform is offered to biotech companies free of charge, provided they contribute necessary training data in return.

Beyond enhancing early-stage discovery, Lilly plans to leverage the supercomputer to compress the journey from research to market. The technology is slated for use across various processes, including critical planning, medical image analysis, and manufacturing optimization.

2. The Transformation of Drug Research

Kimberly Powell, Vice President of Healthcare at NVIDIA, stated that contemporary AI infrastructures are emerging as the new instrumentation of science. This shift moves discovery away from guesswork-based experimentation toward the deliberate and intentional design of treatments.

Thomas Fuchs, Lilly’s Chief AI Officer, emphasized that the objective extends beyond mere speed, focusing instead on the ability to query biology at a massive scale. This will deepen the understanding of disease and translate that knowledge into meaningful scientific and therapeutic advancements.

The integration of AI into drug development is not a novel concept. Employing AI early in the drug lifecycle can boost success rates, lower operational expenses, and broaden the capacity for identifying new therapeutic agents.

Other major pharmaceutical companies have also pursued AI partnership deals:

• AstraZeneca asserted that AI must be regarded as a “thought partner” in the drug discovery process (March 2025).

• Novo Nordisk signed an agreement with NVIDIA to utilize the latter’s supercomputer housed at the Danish Centre for AI Innovation (June 2025).

• NVIDIA previously collaborated on the construction of Cambridge-1, the UK’s most powerful supercomputer, partnering with GSK, AstraZeneca, and the National Health Service (NHS).

According to a report by GlobalData, the specialized global market for AI applications is anticipated to reach $512 billion by 2030.