Lonza, a premier global contract development and manufacturing organization (CDMO), has partnered with biotechnology startup Onava to accelerate AI-driven drug discovery through a new research collaboration.

Under the Research Evaluation Agreement (REA), Onava will leverage Lonza’s GS Gene Expression System technology through Lonza’s flexible evaluation framework. The agreement enables Onava to connect computational prediction with biological data generation earlier and at greater scale in discovery.

Data generated using the GS Gene Expression System platform will be incorporated into subsequent design cycles, creating a closed-loop system that helps refine Onava’s predictive models, supports earlier candidate assessment and improve development readiness.

Peter Droc, Vice President, Head of Licensing, Lonza, commented: “AI-enabled drug discovery depends on the ability to connect computational design with robust experimental validation. By providing access to the GS Gene Expression System® platform with GS Ori-Go® vectors through a flexible Research Evaluation Agreement, we can help customers generate high-quality biological data earlier in discovery, refine candidates with greater confidence and make better-informed development decisions. We are pleased to support Onava as it applies AI-enabled approaches to advance the next generation of therapeutics.”

The collaboration is expected to extend beyond a single program, with Onava planning to use GS Gene Expression System® technology across multiple external partnerships as well as selected internal programs. As candidates advance, Lonza is well positioned to support continued development through its integrated cell line development, process development and manufacturing capabilities.

Sharrol Bachas, CSO, Onava, added: “For AI-native biologics discovery, expression is not simply a downstream manufacturing consideration; it is a critical source of training data. By incorporating Lonza’s GS Gene Expression System and GS Ori-Go vectors into our platform, we can generate consistent, experimentally grounded data across large numbers of AI-designed molecules and feed it directly back into our models. This improves our ability to design not only for biological function, but for the developability and manufacturability that therapeutics require.” 

By combining AI-enabled discovery, proven expression technologies and a flexible licensing framework, Lonza and Onava aim to help translate computational insights into development-ready therapeutic candidates more efficiently.