The High Throughput Bioprocess Develoment (HTBD) working group focus on automated methods and model-based bioprocess engineering. Our main aim is to to find optimal process conditions for biotechnological applications. To this aim, pipetting robots / liquid handling stations are combined with process models and machine learning approaches. By combining automation and modeling, highly complex tasks can be completed quickly and accurately that would not be possible manually.
A wide range of biotechnological process development from library screening to conditional screening under scale-down conditions is dedicated by the HTBD group. The development and application of mechanistic models represents a large part of the work of the HTBD group. In collaborations and especially in the KIWI-biolab project, hybrid models and machine learning tool are increasingly becoming the focus of our work. Developed models are used for process monitoring as well as for process control (Model Predictive Control). In addition to the model-based methods, the HT laboratory is the heart of this research group. In building up this laboratory, the HTBD group has gained great competences in automation, integration of laboratory equipment and software engineering. This knowledge is contributed to various projects and in the SiLA consortium.
Katharina Paulick objective is to improve science and healthcare by promoting new technologies. ML and digitization is a challenge, especially in biological labs. She is expert in image recognition, visual microbial analytic and founder.
Mariano Nicolas Cruz-Bournazou is an expert in the development and application of mechnistic bioprocess models. His research includes the accurate application of mechnical, data-driven and hybrid models, as well as their online calibration and application.
Sebastian Hans is engaged in the automation of bioprocesses, laboratory digitalization up to smart laboratories. The intelligent linking of models, laboratory devices and software are among his particular strengths.