Eli Lilly and Company has launched Lilly TuneLab, an artificial intelligence and machine learning (AI/ML) platform that gives biotech companies access to drug discovery models trained on years of Lilly’s research data.
Lilly estimates that this first release of AI models includes proprietary data obtained at a cost of over $1bn, representing one of the industry’s most valuable datasets used to train an AI system available to biotechnology companies.
“Lilly has spent decades building comprehensive datasets for drug discovery. Today, we’re sharing the intelligence gained from that investment to help lift the tide of biotechnology research,” said Daniel Skovronsky, chief scientific officer, and president, Lilly Research Laboratories and Lilly Immunology.
“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. By opening up access, we hope to accelerate the creation of new medicines for patients who need them.”
Lilly TuneLab is powered by Lilly’s full drug disposition, safety, and preclinical datasets representing experimental data obtained with hundreds of thousands of unique molecules. In return for access, selected biotech partners contribute training data, which fuels continuous improvement for the benefit of others in the ecosystem and ultimately patients.
The platform is hosted by a third-party and employs federated learning, a privacy-preserving approach that enables biotechs to tap into Lilly’s AI models without directly exposing their proprietary data or Lilly’s. Lilly TuneLab was developed through partnerships with leading global technology providers and AI/ML experts. Lilly intends to extend the platform’s features and capabilities beyond this first release, including adding in vivo small molecule predictive models, available exclusively on Lilly TuneLab.
Lilly TuneLab is the newest addition to Lilly Catalyze360’s set of offerings for Lilly’s biotech partners, which includes strategic capital through Lilly Ventures, laboratory facilities at Lilly Gateway Labs, and drug development expertise via Lilly ExploR&D.
“For many early-stage biotech companies, the promise of AI and machine learning in drug discovery remains just that — a promise. While the industry buzzes about the power of AI/ML to accelerate innovation, most small biotechs face a fundamental hurdle: they simply don’t have access to the large-scale, high-quality data needed to impact decisions and train truly effective models,” said Nisha Nanda, group vice president and head, Lilly Catalyze360.
“With Lilly TuneLab we’re not just sharing resources, we are also compressing decades of learning into instantly accessible intelligence. Through this platform, we can help our biotech partners unlock novel scientific insights, make smart development decisions earlier, and increase their likelihood of success.”
To learn more about Lilly TuneLab and explore partnership opportunities, visit tunelab.lilly.com
Jim Cornall is editor of Deeptech Digest and publisher at Ayr Coastal Media. He is an award-winning writer, editor, photographer, broadcaster, designer and author. Contact Jim here.
