It was noted, however, that the model had notable limitations. A second pathway may not always accurately depict diffusive pathways; as such, this belief must be considered a simplification. Further, the underlying mechanisms of pore diffusion limitation has not yet been elucidated. The potential role of diffusive pore size or a bridge size distribution within the stationary phase in this limitation needs to be investigated further (1).
Generally, independent measurements of the effective pore diffusion coefficient inside the membrane material would be preferred. However, experimental resin chromatography techniques cannot currently be employed for membranes. The housing volume exceeds the membrane volume by more than double, meaning that peak parking experiments with stopped flow exhibit low resolution, thus being prone to error. Additionally, the free diffusion coefficient is employed to calculate the effective pore diffusion coefficient. Any observed discrepancies in the experimental determination of the free diffusion coefficient would be incorporated into the effective pore diffusion coefficient (1).
In the context of membrane chromatography modeling, researchers must differentiate between the contributions to the hydrodynamic dispersion from the chromatography system, the membrane housing, and the membrane material. With this study, the system was described using a simplified version of a model, including two continuously stirred tank reactors (CSTRs)–which are reactors characterized by substrate blending systems that ensure high mixing levels in the reaction medium– to account for the system dead volume and one for a ultraviolet (UV) detector (3). In the future, the proposed model could help simulate and investigate mass transfer within other chromatographic media with modifications based on the same base material (1).
This study presents a comprehensive mass transfer model for Sartobind® Rapid A protein A membranes, offering valuable insights into the distinct transport mechanisms governing antibody capture in convective membrane systems. By integrating experimental data with a hybrid modeling approach that accounts for both convective and diffusive transport, the work provides a solid foundation for understanding and optimizing membrane-based chromatographic purification processes. While some simplifications in the model—such as assumptions about diffusion pathways—highlight areas for further refinement, the framework proves effective for describing key performance characteristics and supports its use in process development and scale-up. These findings underscore the potential of advanced membrane chromatography to replace or augment traditional resin-based systems in the biomanufacturing of monoclonal antibodies (1).
References
(1) Gehrmann, N.; Adametz, P.; Taft, F.; Thom, V.; Hahn, R. Modelling the Mass Transfer of a Polysaccharide-Based Protein A Chromatography Membrane with a Bimodal Porous Structure. J. Chromatogr. A 2025, 1756, 466057. DOI: 10.1016/j.chroma.2025.466057
(2) Monoclonal Antibodies. Cleveland Clinic 2021. https://my.clevelandclinic.org/health/treatments/22246-monoclonal-antibodies (accessed 2025-6-2)
(3) Continuous Stirred Tank Reactor. ScienceDirect 2021. https://www.sciencedirect.com/topics/engineering/continuous-stirred-tank-reactor (accessed 2025-6-3)