Prediction of pH Gradient Elution of Ion Exchange Chromatography for Antibody Charge Variants Separation Based on Salt Gradient Elution Experiments

Abstract

Mechanistic modeling of ion exchange chromatography (IEC) is a promising technique to improve process development. However, when considering the pH influence, model prediction becomes challenging due to the multiple pH-dependent parameters and complex interactions. In order to more effectively predict the pH gradient elution behavior, a two-step model calibration strategy was proposed for the pH-dependent steric mass action (SMA) model with the empirical correlations of characteristic charge ν and equilibrium coefficient k_eq. The strategy was verified through a case study of monoclonal antibody charge variants purification with IEC. All nine calibration experiments were conducted using linear salt gradient elution at three fixed pH values. The average root mean square error (RMSE) was 14.28% between the model calculation and experiments. Both ν and ln(k_eq) exhibited good linear correlations with pH (R² > 0.99). Then, the well-calibrated pH-dependent SMA model showed a satisfactory capability for predicting the pH gradient elution behaviors with an RMSE of 16.18%. Moreover, the model was used for process optimization under different elution modes, including salt gradient, pH gradient, and salt-pH dual gradient, improving the yield from 70.07% to 74.91%. The optimized linear pH gradient elution was verified by experiment (RMSE = 8.30%). Finally, a methodological framework for utilizing the simplified pH-dependent SMA model developed in this work was summarized to explore its practical applications. The two-step calibration strategy proposed significantly alleviates the workload for the pH-dependent IEC modeling. The model-based process optimization effectively enables faster pH-dependent process development with minimal experiments.