Enzymes are the essential catalysts behind biomanufacturing, but inefficient enzymes often limit the performance, scalability and commercial viability of biobased production processes. Improving enzyme performance is therefore critical to unlocking the next generation of biosolutions.

Enzidia has developed a breakthrough enzyme engineering platform, the Enzidia Evolutionary Wheel, which combines ultra-high-throughput screening, large-scale data generation and machine learning. The platform enables the screening of billions of enzyme variants while generating datasets several orders of magnitude larger than conventional approaches.

The project will develop a next-generation version of the platform that reduces development time, increases robustness and improves the quality of the enzyme variants identified. New machine learning tools will strengthen the platform’s ability to learn from large datasets and design more effective enzyme libraries.

DTU Biosustain, Nexxar and Cysbio contribute expertise in enzyme expression, analytics, fermentation and industrial validation. Together, the partners will validate the platform under industrially relevant conditions and demonstrate its ability to improve bioprocess performance.

The project aims to accelerate enzyme innovation across a wide range of applications, enabling more efficient biomanufacturing processes and supporting the development of future sustainable chemicals, ingredients and biosolutions.