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Updated: Feb 22, 2026

Purification and Analytics of a Monoclonal Antibody from Chinese Hamster Ovary Cells Using an Automated Microbioreactor System
Published on: May 1, 2019
Purification of Monoclonal Antibodies Using a Fiber Based Cation-Exchange Stationary Phase: Parameter Determination
Jan Schwellenbach1,2, Steffen Zobel3, Florian Taft4
1Sartorius Stedim Biotech GmbH, Göttingen 37079, Germany. jan.schwellenbach@sartorius-stedim.com.
Abstract:
Monoclonal antibodies (mAb) currently dominate the market for protein therapeutics. Because chromatography unit operations are critical for the purification of therapeutic proteins, the process integration of novel chromatographic stationary phases, driven by the demand for more economic process schemes, is a field of ongoing research. Within this study it was demonstrated that the description and prediction of mAb purification on a novel fiber based cation-exchange stationary phase can be achieved using a physico-chemical model. All relevant mass-transport phenomena during a bind and elute chromatographic cycle, namely convection, axial dispersion, boundary layer mass-transfer, and the salt dependent binding behavior in the fiber bed were described. This work highlights the combination of model adaption, simulation, and experimental parameter determination through separate measurements, correlations, or geometric considerations, independent from the chromatographic cycle. The salt dependent binding behavior of a purified mAb was determined by the measurement of adsorption isotherms using batch adsorption experiments. Utilizing a combination of size exclusion and protein A chromatography as analytic techniques, this approach can be extended to a cell culture broth, describing the salt dependent binding behavior of multiple components. Model testing and validation was performed with experimental bind and elute cycles using purified mAb as well as a clarified cell culture broth. A comparison between model calculations and experimental data showed a good agreement. The influence of the model parameters is discussed in detail.
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