UCB and Cradle Expand AI-Powered Antibody Discovery

Brussels, Belgium, and Amsterdam, Netherlands, November 4, 2026

UCB Integrates Cradle’s AI Platform Into Antibody Discovery

Under the strategic collaboration, UCB will use Cradle’s AI-powered protein engineering platform across selected discovery programs. The technology is designed to help researchers generate and refine protein-based molecules by evaluating their properties and identifying promising molecular designs. The collaboration will support multiple stages of the discovery process, beginning with hit generation, progressing through lead optimization and continuing toward preclinical readiness. Antibody engineering is a complex process that requires scientists to balance several molecular characteristics, including binding performance, stability, developability and other properties that influence the suitability of a candidate for further development. Traditional discovery approaches can involve extensive laboratory experimentation and repeated optimization cycles. By integrating computational prediction into these workflows, UCB aims to help its research teams evaluate molecular designs more efficiently and prioritize promising candidates. The partnership builds on UCB’s existing antibody discovery capabilities, which combine its proprietary discovery platform, computational science, disease biology expertise and collaborations with external technology and research organizations. Cradle’s platform will add another computational capability to this established research ecosystem, supporting scientists as they investigate complex therapeutic molecules.

Lab-in-the-Loop Approach Combines AI With Laboratory Validation

A central element of the collaboration is the lab-in-the-loop approach, which connects AI-based predictions with experimental results generated by scientists. Under this model, UCB researchers will use Cradle’s platform to support molecular design and optimization. The resulting candidates can then be evaluated through laboratory experiments, with the experimental findings fed back into program-specific computational models. This continuous feedback process is intended to improve the accuracy and usefulness of predictions as research progresses. Instead of treating each experiment as an isolated activity, the platform is designed to use accumulated experimental information to guide subsequent design decisions. This creates a learning cycle in which computational models and laboratory science work together to refine candidate molecules. UCB’s Chief Scientific Officer, Alistair Henry, said the company views AI as a scientific tool that strengthens human expertise across biology, chemistry and translational research. The collaboration is intended to help scientists apply predictive modeling alongside wet-lab validation to design improved molecules and advance high-quality therapeutic candidates. Cradle Co-Founder and Chief Executive Officer Stef van Grieken highlighted the importance of integrating AI across broader biotherapeutics research organizations rather than limiting its use to individual experiments. The partnership will give UCB scientists a common platform to apply computational protein engineering across more research programs, therapeutic modalities and complex molecular challenges.

Collaboration Strengthens UCB’s Biologics Development Strategy

The agreement reflects the increasing importance of AI-driven biologics discovery across the pharmaceutical industry. Antibodies and other protein-based medicines can offer highly targeted therapeutic approaches, but designing molecules with the required combination of biological activity and development characteristics remains challenging. Computational platforms can help researchers explore molecular possibilities and prioritize designs for experimental testing. For UCB, the collaboration supports its broader strategy of combining scientific expertise with digital technologies to advance medicines for people living with severe immune-system and central nervous system diseases. The company operates internationally, with research and development activities focused on innovative therapeutic solutions. Cradle’s platform brings together AI-driven molecular engineering, experimental-data learning and multi-property optimization within an integrated protein-design workflow. The company reports that its technology is used across research and development programs in pharmaceutical, industrial biotechnology, agriculture and consumer-goods sectors. Financial terms of the UCB–Cradle collaboration were not disclosed. The announcement does not identify specific drug candidates, clinical trials or regulatory submissions arising from the partnership. Instead, the immediate objective is to strengthen early-stage discovery and preclinical preparation across selected research projects. Overall, the collaboration highlights how artificial intelligence and experimental biology are increasingly working together to support next-generation antibody engineering. Its long-term value will depend on whether the integrated platform helps UCB identify and optimize promising therapeutic candidates that can successfully progress through preclinical research and clinical development.

Source: UCB, Cradle press release