Data-rich process development of immobilized biocatalysts in flow

Abstract

Immobilization has been widely applied to improve the productivity and lifetime of select enzyme classes used in commodity chemical synthesis. Advances in enzyme engineering capabilities and high throughput experimentation have dramatically increased the use of novel enzyme classes and their applications to pharmaceutical synthesis, where immobilization is used to increase enzyme loading and stability and improve protein-product isolation. Conventional approaches to immobilization development are time and resource-intensive and cannot meet pharmaceutical development's demanding timelines. We developed a data-rich methodology that uses a medium pressure chromatography system to automate the screening and development of affinity-based enzyme immobilizations. We integrated inline PAT to characterize the immobilization process in real-time and facilitate rapid decision making. Most critically, this approach served to significantly reduce the amounts of enzyme and resin required for meaningful process development, transforming immobilization process development and optimization from a manual 6–8 week process to an automated overnight process. This paper demonstrates the development and application of data-rich experimental methods to rapidly identify, develop, and optimize robust, scalable immobilization processes, provide improved fundamental understanding, and describes how this methodology has enabled multiple successful commercial-scale immobilizations.