Biotech firm Chai Discovery has announced a collaboration with Eli Lilly, a major global pharmaceutical company, to advance biologics discovery through artificial intelligence. The strategic partnership will leverage Chai’s expertise in computational modelling, machine learning, and large scale data integration to accelerate identification and optimisation of biologics candidates.

Biologics therapeutic proteins, antibodies and other large molecule therapies require extensive screening, design and validation efforts across multiple stages of development. By integrating Chai Discovery’s AI platform with Eli Lilly’s scientific expertise and laboratory ecosystem, the two organisations aim to improve efficiency in biologics research, reduce resource intensive experimentation, and enable data driven decision making.

The collaboration will focus on refining predictive models that guide early target identification, 3D structure predictions and binding affinity assessments. These AI-powered insights are expected to support more accurate candidate ranking, improved lead optimisation and stronger translational readiness for clinical development.

Officials from both companies emphasised that AI complements, rather than replaces, traditional experimental workflows. The partnership will adopt an iterative hybrid approach combining computational hypothesis generation with targeted wet-lab validation to enhance the productivity and robustness of biologics discovery pipelines.

Industry observers note that this type of collaboration reflects broader trends in drug discovery, where machine learning and systems biology are being used to tackle the complexity of modern therapeutic modalities. By embedding AI at the earliest stages of biologics research, Chai Discovery and Eli Lilly hope to unlock innovative therapies across areas such as immunology, oncology and rare diseases.