German title: Prozesse der weißen Biotechnologie mit informierten KI-Model

The research project focuses on the efficient and scalable production of biotechnological products through microbial fermentation. Its objective is to systematically optimize existing production processes in order to achieve higher yields, ensure stable and reproducible operations, and accelerate the transfer from laboratory development to industrial application. A key emphasis is placed on improving the scalability of processes, enabling a smoother and faster transition from research to real-world production systems.

The project combines experimental investigations with modern data-driven methods. In a series of systematic studies, key influencing factors such as operating conditions and reactor settings are analyzed with respect to their impact on process performance. The insights gained are then used to transfer these processes to larger scales while identifying and controlling scale-up effects.

A central component of the project is the development of an AI-based model that integrates experimental data with existing process knowledge. This model is designed to predict optimal operating conditions, support the efficient planning of experiments, and enable early detection of potential process disturbances. As a result, adjustments can be made during ongoing production, significantly improving both efficiency and economic performance. At the same time, the use of artificial intelligence allows for a more accurate representation of complex process interactions that are difficult to capture with conventional modeling approaches.

By closely integrating experimental research with data-driven modeling, the project establishes a holistic approach that is both scientifically rigorous and practically relevant. In collaboration with an industrial partner, the developed methods are tested and refined under realistic production conditions. This contributes to more sustainable production processes, reduced costs, and facilitates the industrial implementation of new biotechnological solutions.

Overall, the project makes an important contribution to the advancement of modern biotechnological production systems by combining innovative technologies and methodologies to create processes that are more efficient, robust, and adaptable.