Biocatalysis in microfluidic systems: an experimental basis for data science

Accelerated development of new biocatalytic processes using data science from designed microfluidic experiments, aimed at scale-down exposure of enzyme variants to conditions mimicking those found in industrial processes. Biocatalysis using (recombinant) enzymes is gaining traction as a method for selective chemical catalysis, especially in the pharmaceutical industry. Flow systems, especially miniaturized microfluidic systems, have proven to be a useful method to test new enzyme reaction sequences and processes. In this brief article, it will be argued that microfluidics not only can be used for rapid testing of reaction processes, but also can be used nowadays for collection of process data, especially for parameters in relevant kinetic and stability models, and thereby to help with scale-up, which remains a major challenge for implementation of biocatalysis in many industries. The ability to quickly change conditions (such as temperature) in microfluidic devices makes them ideally suited to such scale-down studies, and can form the experimental basis for data science as a tool for future process development.