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Insilico, Lilly strike AI drug discovery deal worth up to $2.75 billion

By Zhang Chenxu | chinadaily.com.cn | Updated: 2026-03-31 16:31
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Insilico Medicine Cayman TopCo, a Hong Kong-based AI-driven drug discovery startup, said on Monday that it has entered into a global licensing and research deal with US pharmaceutical giant Eli Lilly worth up to $2.75 billion to advance drug discovery across multiple therapeutic areas.

Under the agreement, Lilly will obtain an exclusive worldwide license to develop, manufacture and commercialize potentially best-in-class novel oral therapeutics currently in preclinical development for certain indications, while the two sides will also collaborate on multiple research and development programs focused on targets selected by Lilly, the company said.

The deal includes an upfront payment of $115 million, with development, regulatory and commercial milestones bringing its total potential value to about $2.75 billion, plus tiered royalties on future sales, according to the company.

Alex Zhavoronkov, founder and CEO of 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."

In a recent interview with China Daily, Zhavoronkov said that for both AI-driven and traditional drug developers, the key benchmark is how quickly, cost-effectively and innovatively they can generate preclinical candidate compounds.

Insilico has produced 28 preclinical candidate compounds over the past five years, 12 of which have received investigational new drug approvals and entered the clinical stage, according to Zhavoronkov.

"Insilico's AI-enabled discovery capabilities represent a powerful complement to Lilly's deep expertise in clinical development across multiple therapeutic areas," said Andrew Adams, group vice-president of Molecule Discovery at Lilly. "This collaboration allows us to explore novel mechanisms and accelerate the identification of promising therapeutic candidates across multiple disease areas."

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