Schrödinger Adds Eli Lilly’s AI Drug-Discovery Models to Its Molecular Design Platform
Schrödinger will integrate Eli Lilly’s AI drug discovery platform, TuneLab, into its cloud-based molecular design environment, LiveDesign. The partnership allows existing Schrödinger clients to access Lilly’s internal models for molecular generation, optimization, and predictive screening directly through LiveDesign starting in Q1 2026, with broader rollout by Q2.
Schrödinger’s cloud-based LiveDesign supports small molecule and biologics research, compound design, ADME property prediction, allows real-time data sharing across teams and external partners, and integrates with corporate systems via API in a single environment. Embedding TuneLab into LiveDesign is intended to enable drug developers to run Lilly’s in-house AI models on their own targets.
Lilly’s TuneLab is a federated learning platform for small molecule and antibody design, trained on over $1 billion in proprietary chemistry, biology, and safety data, and designed to let external partners generate predictions while contributing to model improvement without exposing proprietary inputs.
This week, Lilly also saw other expansions beyond the Schrödinger integration. Access was extended to more than 1,300 biotech companies through a Benchling integration and collaboration with Revvity. Two months ago, Lilly also collaborated with Nvidia to build an AI supercomputer for training models on discovery and manufacturing data.
The LiveDesign integration sits within the context of a wider industry trend toward reducing reliance on animal models, aligned with recent FDA roadmap to phase down animal use in preclinical safety studies through New Approach Methodologies (NAMs), developed with NIH and complemented by new NIH structures to coordinate validation of organoids, organ-on-chip, and computational models.
See also: From Animals to Algorithms: How AI Brings Drug Testing Closer to Human Biology
Contract research providers such as Charles River now report roughly $200 million in annual revenue from NAMs, including AI-supported in vitro and organ-on-chip assays, underscoring that non-animal safety tools are moving from pilot projects into a scaled service line.
Our recent deep dive, How Organoids and AI Are Replacing Animal Testing, outlines how this shift is unfolding across the sector, with startups and pharma alike integrating AI-driven toxicity models, organoids, and organ-on-chip systems into preclinical workflows.
Topic: Industry Movers
