Model-based tools for optimal experiments in bioprocess engineering

Currently applied methods for characterization and optimization of bio-pharmaceutical processes are still strongly empirical. This often involves Design of Experiment (DoE) methods that require a large number of time-consuming experiments and can hardly fulfill the requirements of 'Quality by Design' (QbD). Linking mathematical models with experimental methods is seen as an efficient strategy that significantly reduces development time and costs. Furthermore, if combined with advanced Process Analytical Technology (PAT), higher automation and more efficient workflows can be established along the product lifecycle. This contribution presents the state of the art of model-based tools for experimental design and gives an outlook on future trends in the field of bio-process engineering.