News
Benchling and Lilly TuneLab partner to democratize access to AI models for scientists
Benchling has partnered with Lilly TuneLab to bring AI models trained on over $1 billion in Lilly research data directly into scientists' workflows. Run prediction models for antibodies and small molecules, then share data back for federated learning. Reach out to your Benchling account team for access & information.
Run Lilly TuneLab prediction models, directly from Benchling
Ecosystem
Expanding Benchling Models: TuneLab joins Benchling's growing scientific AI ecosystem
TuneLab expands Benchling Models, our centralized hub where scientists access the world's leading scientific AI. Alongside structure prediction models like AlphaFold, Chai, and Boltz, TuneLab brings Lilly's proprietary drug disposition and safety models directly into your workflows.
Part of Benchling AI, alongside our partnerships with Anthropic, NVIDIA, and others
One place to access open-source and proprietary scientific models
Connected to your structured data for predictions that drive decisions
Access
What is Lilly TuneLab? Lilly's proprietary AI models, built for drug discovery
Lilly TuneLab is a first-of-its-kind collaborative drug discovery platform that gives biotech companies access to Eli Lilly’s AI/ML models trained on decades of Lilly proprietary data. TuneLab levels the playing field, bringing AI capabilities that Lilly scientists use daily to companies of all sizes.
AI/ML models for in silico property predictions across small molecules and antibodies
Built on secure federated learning
Models continuously improve as more companies participate
Integrated
Why TuneLab at Benchling? Predictions where your science already happens
Benchling is the platform where scientists already capture, connect, and analyze R&D data. TuneLab at Benchling means predictions flow directly into your existing workflows—no data exports, no context switching, no disconnected tools.
Run predictions directly from your Benchling Notebook and Registry
Results automatically linked to your sequences, molecules, and experimental metadata
Outputs are traceable and ready for downstream analysis
