Insilico Medicine has signed a drug discovery collaboration with Eli Lilly and Company worth up to $2.75bn to develop AI-driven therapeutics across multiple disease areas.

The agreement combines Insilico’s generative artificial intelligence platform with Lilly’s clinical development and commercial capabilities, with a focus on accelerating the identification and progression of novel drug candidates.

Under the terms of the deal, Lilly will receive an exclusive worldwide licence to develop, manufacture and commercialise selected oral therapeutics currently in preclinical development. The companies will also collaborate on additional research and development programmes using targets selected by Lilly.

Insilico is eligible for an upfront payment of $115m, along with development, regulatory and commercial milestone payments that could bring the total value of the agreement to approximately $2.75bn. The company is also set to receive tiered royalties on future product sales.

The collaboration will use Insilico’s Pharma.AI platform to support target identification and early-stage drug discovery. The company said its technology is designed to analyse complex biological data and identify novel mechanisms across multiple diseases.

Alex Zhavoronkov, chief executive at Insilico Medicine, said: “Working with Lilly, we aim to deliver transformative therapies that treat diseases with high unmet need. This collaboration is a testament to the power of AI in tackling the most complex challenges in human health.”

Lilly will apply its expertise in clinical development and disease biology to advance candidates generated through the collaboration, with a focus on improving the efficiency of drug discovery and development.

Andrew Adams, group vice president of molecule discovery at Lilly, said: “This collaboration allows us to explore novel mechanisms and accelerate the identification of promising therapeutic candidates across multiple disease areas.”

The deal reflects continued investment by large pharmaceutical companies in artificial intelligence platforms, particularly in early-stage discovery where failure rates remain high and timelines are long.

AI-driven approaches are increasingly being used to identify drug targets, design molecules and prioritise candidates, with partnerships between biotech companies and pharma groups becoming a common route to scale these technologies.