Eli Lilly's TuneLab Offers Smaller Biotechs Big AI Power at No Cost

Eli Lilly has launched TuneLab, an artificial intelligence platform that gives biotech partners access to models trained on more than $1 billion of proprietary research data. The company is providing the platform at no cost, but every new dataset contributed by partners improves Lilly’s models. This structure allows Lilly to expand its data advantage and strengthen relationships with emerging biotechs, even as it supports broader innovation in drug discovery.

Chief Scientific Officer Daniel Skovronsky called TuneLab “an equalizer so that smaller companies can access some of the same AI capabilities used every day by Lilly scientists”. For many small firms, building high quality datasets is too expensive. Nisha Nanda, who leads Lilly’s Catalyze360 program, said TuneLab helps by “compressing decades of learning into instantly accessible intelligence”.

The company estimates that the first release of models includes data valued at over $1 billion. These datasets cover drug disposition, safety, and preclinical research. They also include failed experiments, which Thomas Fuchs, Lilly’s first Chief AI Officer, described as “enormously valuable” because they provide unique training signals for machine learning. Analysts at Jefferies estimate that the industry’s annual spending on AI could reach $40 billion by 2040.

TuneLab is hosted by a third party and uses federated learning. This means Lilly’s AI models are sent to a partner’s systems for training, and only encrypted model updates return to Lilly. Neither side has to share raw proprietary data. Lilly says this structure creates a loop where each partner contributes new data that improves the models for everyone.