Intensification of Kinetic Studies for a Multi-step Reaction in a Milli-structured Plate Reactor by using Model-based Design of Experiments

In the context of process intensification, milli-structured plate reactors provide significant advantages over conventional reactors in terms of heat and mass transfer as well as process safety. The ART® plate reactor PR37 of Ehrfeld Mikrotechnik GmbH offers excellent heat transfer, narrow residence time distributions and high mixing efficiency, while simultaneously allowing an effective scale-up to industrial applications due to its modular set up. This does not only enable the realization of novel process windows exceeding the limits of conventional reactors, but also provides optimal prerequisites for kinetic modelling due to the well-defined process conditions, providing key information regarding process design and optimization. The integration of the ART PR37 with Model-based Design of Experiments (MBDoE) allows for an intensification of kinetic studies, combining the well-defined operating conditions with a rapid and targeted identification of kinetic models. In the current study this combination is applied to successfully identify the kinetics of a multi-step aromatic nucleophilic substitution reaction with low experimental effort, saving time and resources compared to conventional factorial Design of Experiments

Closed-loop identification of enzyme kinetics applying model-based design of experiments

Accurate kinetic models for enzyme catalysed reactions are integral to process development and optimisation. However, the collection of useful kinetic data is heavily dependent on the experimental design and execution. In order to reduce the limitations associated with traditional statistical design and manual experiments, this study introduces an integrated, automated approach to identifying kinetic models based on model-based optimal experimental design. The immobilised formate dehydrogenase of Candida boidinii catalyses the enzymatic reduction of NAD+ to NADH and is used as a model system. Continuous collection of UV/Vis data under steady-state conditions is employed to determine the kinetic parameters in a packed bed reactor. Automation of the experimental work was utilised in Python to compensate for the need for more time-consuming data collection. A completely automated closed-loop system was created and appropriate kinetic models for anticipating process dynamics were identified. The automated platform was able to identify the correct kinetic model out of eight candidate models with only 15 experiments. Further extension of the design space improved model discrimination and led to a properly parameterized kinetic model with sufficeintly high parameter precision for the conditions under examination