Eli Lilly Secures $2.75 Billion Deal for AI-Developed Drugs

American pharmaceutical giant Eli Lilly has secured a $2.75 billion deal to implement drugs developed with the help of artificial intelligence by Hong Kong-based Insilico Medicine, CNBC reports.

Under the agreement, Insilico will receive an upfront payment of $115 million. The remaining amount will be paid upon reaching regulatory and commercial milestones, as well as through royalties (a percentage of revenue from future sales), the companies announced.

According to Insilico founder and CEO Alex Zhavoronkov, the company has developed at least 28 drugs using generative artificial intelligence. Nearly half of them are already in the clinical stage.

In many respects, Lilly is superior to us in certain areas of artificial intelligence, Zhavoronkov stated. He noted that the American company employs a specialist who has integrated biology, chemistry, and automation “under one roof.” He added that as part of the deal, Insilico will join Lilly’s Gateway Labs platform for biotech development.

The two companies have been collaborating since 2023, when they signed an agreement for licensing AI-based software.

“This collaboration allows us to explore new mechanisms and accelerate the identification of promising therapeutic candidates across various disease areas,” said Andrew Adams, Vice President of Molecule Discovery at Lilly. He described Insilico’s AI-based developments as a “strong complement” to the company’s clinical pipeline.

Eli Lilly CEO David Ricks participated in a high-level forum in Beijing earlier this month. This comes just weeks after the company announced plans to invest $3 billion in China over the next decade. According to company data, just under 3% of its revenue last year came from the Chinese market.

Insilico develops its AI technologies outside of China—in Canada and the Middle East. The company conducts the early stages of preclinical drug development in China, Zhavoronkov explained. According to him, artificial intelligence not only shortens research time but also allows for the synthesis of molecules significantly faster compared to traditional methods.