- Lonza and Onava have entered a Research Evaluation Agreement to support AI-enabled biologics discovery using Lonza’s GS Gene Expression System® platform and GS Ori-Go® vectors.
- Onava will use experimentally generated biological data to refine its predictive models and assess the development readiness and manufacturability of AI-designed therapeutic candidates.
Lonza and biotechnology company Onava have announced a collaboration to connect AI-enabled biologics discovery with experimental validation. Under a Research Evaluation Agreement (REA), Onava will use Lonza’s GS Gene Expression System® technology with GS Ori-Go® vectors to generate biological data earlier in the drug discovery process and incorporate the results into subsequent design cycles.
The collaboration is intended to establish a feedback loop between computational predictions and experimental results. Onava will use the generated data to refine its predictive models, assess candidates earlier, and evaluate their readiness for development. The approach also aims to help Onava design biologics with consideration for both biological function and manufacturability.
Onava plans to apply the GS Gene Expression System® technology across multiple external partnerships and selected internal programs. As candidates progress, Lonza’s cell line development, process development, and manufacturing capabilities could support their continued development.
“AI-enabled drug discovery depends on the ability to connect computational design with robust experimental validation. The agreement provides a framework for generating biological data earlier in discovery and supporting more informed development decisions.”
Peter Droc, vice president and head of licensing at Lonza
Sharrol Bachas, chief scientific officer at Onava, said experimental expression data is an important source of training data for AI-native biologics discovery. The companies aim to combine AI-enabled discovery, expression technologies, and a flexible licensing framework to help translate computational insights into therapeutic candidates with improved development readiness.
