Eli Lilly launches TuneLab, sharing $1B AI drug discovery platform with biotech partners

Eli Lilly has launched TuneLab, an AI-powered platform that provides biotech companies access to drug discovery models trained on over $1 billion worth of the pharmaceutical giant’s proprietary research data. The platform aims to democratize AI capabilities in drug development, allowing smaller companies to leverage the same advanced tools used by Lilly’s scientists while contributing their own data to enhance the system.

Why this matters: The pharmaceutical industry is increasingly turning to AI to accelerate drug discovery and reduce costs, with analysts projecting AI-related R&D spending to reach $30-40 billion by 2040 as companies seek faster, cheaper alternatives to traditional development methods.

How it works: TuneLab operates on datasets representing experimental data from hundreds of thousands of unique molecules, creating AI models that can predict drug behavior and effectiveness.

• Selected biotech partners gain access to Lilly’s AI capabilities in exchange for contributing their own training data to enhance the platform.
• The system is designed to level the playing field between large pharmaceutical companies and smaller biotech firms that lack extensive research databases.
• Partners can use the platform for various applications, from cancer therapy development to small molecule discovery.

Who’s already on board: Two privately held companies have announced partnerships with Lilly for TuneLab access.

• Circle Pharma will use the platform to develop cancer therapies.
• Insitro plans to build new AI models that will be integrated into TuneLab for discovering small molecule therapies.

What they’re saying: “Lilly TuneLab was created to be an equalizer so that smaller companies can access some of the same AI capabilities used every day by Lilly scientists,” said Daniel Skovronsky, Lilly’s chief scientific officer.

The bigger trend: This launch aligns with an FDA push to reduce animal testing in drug development, as AI technologies offer alternative methods for safety testing and efficacy prediction that could transform how new medications reach patients.