Mechanistic Modeling for Enhanced Chromatographic Productivity

Performance Period: 5/15/2019 to 8/31/2021

The industry has employed extensive empirical experimentation for the development of robust, downstream processes. This project will address key gaps in the current downstream process development space by providing a mechanistic model and supporting laboratory workflows for accurately predicting challenging and complex chromatography applications, including multimodal chromatography and separation of a range of product- and process-related impurities. We will employ state-of-the-art high-throughput chromatographic data generation, isotherm modeling and process simulations to create a mechanistic modeling platform that can accurately account for product heterogeneity, multicomponent effects, and multiple modes of interactions. We will then apply this approach to industrial case studies ranging from early development to final commercialization of a process. Mechanistic models derived from this project will enable a reduction in the downstream process development time. Improved process understanding through model application will lead to more consistent product quality and improved process manufacturability. Finally, the availability of the resulting commercial modeling strategy and tools will allow researchers with a range of process development skill sets to leverage these models. This collaboration will bring the technology from MRL 4 to 6 by enabling modeling to be used in making development decisions on industrially relevant separations.