Leverage automated workflows combining computational planning, microcultivation, and data science to enhance peptide production processes. Ideal for strain screening and process optimization, with proven success in diverse microbial hosts.
Our automated workflows for bioprocess optimization significantly enhance peptide production by integrating computational experimental planning, microcultivation, and data science. These workflows are designed to improve the quality and quantity of cultivation experiments, making them ideal for tasks such as strain screening, strain characterization, and process optimization. With over five years of experience at the MiBioLab in Forschungszentrum Jülich, our platform has successfully accelerated bioprocess development for industrial clients, demonstrating its effectiveness across various microbial hosts including bacteria, yeasts, and filamentous fungi.
Key features:
This solution is at Technology Readiness Level 6, indicating that it has been demonstrated in relevant environments and is ready for further industrial validation and deployment through collaborative research plans with industrial partners.
Forschungszentrum Jülich is a large-scale Helmholtz research center in North Rhine‑Westphalia with over 7,000 employees. Companies tap co‑located user facilities and the Jülich Supercomputing Centre, home to Europe’s first exascale system (JUPITER) for large‑scale modeling. Through the Jülich Aachen Research Alliance with RWTH Aachen University, industry benefits from joint labs, shared appointments, and a strong regional talent pipeline. Research is backed by long‑term base funding via the Helmholtz Association and competitive awards from German and EU programs. A dedicated technology transfer office supports IP, licensing, collaboration contracts, and de‑risks prototypes via an internal innovation fund.