Bayer Enters Three-Year AI Antibody Discovery Collaboration with Cradle
Bayer has entered a three-year collaboration with Cradle to integrate Cradle’s generative AI platform for protein engineering into Bayer's internal workflows for therapeutic antibody discovery and optimization. The agreement is positioned as a technology deployment with Bayer maintaining full ownership of resulting intellectual property. Beyond deployment, Bayer and Cradle will jointly conduct a machine learning research project focused on enhancing protein engineering capabilities.
The collaboration follows internal benchmarking by Bayer, which reportedly compared Cradle’s software with other commercial platforms and in-house tools, citing performance advantages in molecule quality, development speed, and workflow integration. Bayer aims to reduce optimization cycles, improve manufacturability, and accelerate lead selection as its pipeline expands into more complex biologics.
Headquartered in Amsterdam, Cradle’s team includes former technologists from Google, DeepMind, and Generate Biomedicines. The company is backed by IVP, Index Ventures, and Kindred Capital. Cradle’s platform supports lab-in-the-loop automation and design-test-learn cycles. It is currently reportedly in use across over 50 programs and by six of the top 25 global pharma companies, including Johnson & Johnson, Novo Nordisk, and AbbVie. Reported outcomes include reducing preclinical development costs by $7–22 million and compressing timelines up to 12-fold per candidate.
Bayer’s selection of Cradle sits alongside a wider pattern in large drug development: surveys and industry analyses from 2025 indicate that a majority of large pharma companies are treating AI as an immediate strategic priority and are embedding generative AI into workflows. Our recent deep dive into Big Pharma’s AI strategies outlines how top companies are deploying AI platforms across target discovery, molecule design, synthesis, and clinical development.
One way this shows up is in the specific builds and partnerships companies have chosen: Eli Lilly partnered with Nvidia to build an AI supercomputer aimed at training proprietary models on large experimental datasets and integrating these into its TuneLab federated platform for discovery and development, which later was opened to select external biotech partners. Merck also expanded its internal generative AI solutions in 2025 to support clinical study report generation and other R&D tasks using advanced data engineering and large language models, while Takeda deepened its AI-driven discovery work with Nabla Bio’s Joint Atomic Model platform to design protein therapeutics, extending a multi‑year collaboration that began earlier, and Bristol Myers Squibb together with Accenture launched a generative AI‑enabled content hub to enhance medical education and communication outputs at scale.
Topic: Industry Movers
