PARTNERSHIPS

The Shot Is So Last Year. Lilly Wants You to Pop a Pill

Eli Lilly and Nimbus Therapeutics team up in a deal worth up to $1.3B to develop a new oral obesity drug

31 Mar 2026

Lilly scientists working with lab equipment in pharmaceutical research lab

Eli Lilly has signed a multi-year research collaboration and exclusive worldwide licence agreement with Nimbus Therapeutics, a Boston-based AI drug discovery company, to develop an oral small-molecule treatment for obesity and metabolic disease.

Under the terms announced on 6 January 2026, Nimbus will receive $55 million in upfront and near-term milestone payments, with the total deal value reaching up to $1.3 billion if development, commercial, and sales targets are met. Tiered royalties on global net sales are also included.

Lilly will draw on Nimbus's computational chemistry platform, which combines machine learning with structure-based drug design to identify and refine molecules against difficult-to-treat biological targets. The programme is at an early discovery stage. This is the second collaboration between the two companies; the first focused on AMPK, a protein involved in energy metabolism and cardiometabolic disease.

Ruth Gimeno, Group Vice President of Diabetes and Metabolic Research and Development at Lilly, described the partnership as "an important addition to the company's efforts to advance innovative treatment options for patients with metabolic disorders." Peter Tummino, President of R&D at Nimbus, said the agreement "brings together the company's discovery capabilities and Lilly's metabolic expertise to develop a treatment that could make a meaningful difference for people living with obesity."

The deal reflects growing pressure on large pharmaceutical companies to develop oral alternatives to injectable GLP-1 receptor agonists, the class of drugs that has driven a surge in obesity treatment over the past two years. Several major drugmakers are pursuing small-molecule programmes that could offer patients a more convenient dosing option.

Whether early-stage computational approaches can reliably produce clinical candidates in a field where many programmes have stalled remains an open question, as does the timeline for any potential treatment to reach patients.

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