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Updated: Jul 1, 2025

Ion Exchange Chromatography IEX Coupled to Multi-angle Light Scattering MALS for Protein Separation and Characterization
Published on: April 5, 2019
Standardized approach for accurate and reliable model development of ion-exchange chromatography based on
Yu-Cheng Chen1, Hui-Li Lu2, Rong-Zhu Wang2
1Key Laboratory of Biomass Chemical Engineering of Ministry of Education, Zhejiang Key Laboratory of Smart Biomaterials, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou, China.
Abstract:
Developing an accurate and reliable model for chromatographic separation that meets regulatory requirements and ensures consistency in model development remains challenging. In order to address this challenge, a standardized approach was proposed in this study with ion-exchange chromatography (IEC). The approach includes the following steps: liquid flow identification, system and column-specific parameters determination and validation, multi-component system identification, protein amount validation, steric mass action parameters determination and evaluation, and validation of the calibrated model's generalization ability. The parameter-by-parameter (PbP) calibration method and the consideration of extra-column effects were integrated to enhance the accuracy of the developed models. The experiments designed for implementing the PbP method (five gradient experiments for model calibration and one stepwise experiment for model validation) not only streamline the experimental workload but also ensure the extrapolation abilities of the model. The effectiveness of the standardized approach is successfully validated through an application about the IEC separation of industrial antibody variants, and satisfactory results were observed with R2 ≈ 0.9 for the majority of calibration and validation experiments. The standardized approach proposed in this work contributes significantly to improve the accuracy and reliability of the developed IEC models. Models developed using this standardized approach are ready to be applied to a broader range of industrial separation systems, and are likely find further applications in model-assisted decision-making of process development.
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