2025 AIChE Annual Meeting

(385aa) Application of Mechanistic Modeling for the Development of a Miniaturized Size Exclusion Chromatography (SEC) Column for on-Site Quantitative Analysis.

Authors

Govind Rao, University of Maryland-Baltimore County
Douglas Frey, University of Maryland Baltimore County
Research Interests: Downstream Processing, Process Purification, Chromatography, Mechanistic Modeling, Sensor Development

Size exclusion chromatography (SEC) is a widely used technique for the purification of biological proteins and characterization of product related impurities or critical quality attributes (CQAs) such as aggregates (HMW) and fragments (LMW). However, application of SEC for continuous CQA monitoring and process control is often limited by the lengthy, offline and complex high performance liquid chromatography (HPLC) analysis. Expensive columns of long lengths also make small-scale operation of SEC difficult. To address these concerns, we have developed a miniaturized chromatography column (µCol) (5cm x 0.5cm ID, ~1mL CV) fabricated in-house with a polymethyl methacrylate (PMMA) framework, containing HPLC-grade SEC resin in an engraved channel for a low-cost (~$20), simple and rapid (~5 min) on-site quantitative detection of CQAs, in the form of a definitive assay. A mechanistic model was prepared using COMSOL Multiphysics to gain a detailed understanding of the transport phenomena occurring inside the SEC resin, and to screen various innovative designs to obtain minimal wall-effects, ease of pressure packing, increased path lengths for good resolution, and compact shapes for integration into microfluidic chips. Preliminary scale-down studies were performed using simulations to select suitable kinetic parameters such as column length, inner diameter, resin particle size, flow rate, injection volume and theoretical plate height; followed by screening of discrete geometries as well as validation of the predicted elution profiles using the van Deemter analysis. The physics involved in this model contains various interconnected partial differential equations (PDE) governing mass transfer kinetics and fluid flow. It accounts for the flow disparity inside the column, axial and radial dispersion, adsorption on the particle surface, diffusion from bulk liquid and diffusion within the particle pores. Our objective was to develop a predictive model using computational fluid dynamics (CFD) to overcome the experimental challenges of high resource consumption and limited access to target molecules. The developed SEC µCol prototype will also be assessed conceptually for virus clearance studies, polishing and scale-up.