Evaluation of dynamic control of continuous capture with periodic counter-current chromatography under feedstock variations

Abstract

Multi-column periodic counter-current chromatography is a promising technology for continuous antibody capture. However, dynamic changes due to disturbances and drifts pose some potential risks for continuous processes during long-term operation. In this study, a model-based approach was used to describe the changes in breakthrough curves with feedstock variations in target proteins and impurities. The performances of continuous capture of three-column periodic counter-current chromatography under ΔUV dynamic control were systematically evaluated with modeling to assess the risks under different feedstock variations. As the concentration of target protein decreased rapidly, the protein might not breakthrough from the first column, resulting in the failure of ΔUV control. Small reductions in the concentrations of target proteins or impurities would cause protein losses, which could be predicted by the modeling. The combination of target protein and impurity variations showed complicated effects on the process performance of continuous capture. A contour map was proposed to describe the comprehensive impacts under different situations, and nonoperation areas could be identified due to control failure or protein loss. With the model-based approach, after the model parameters are estimated from the breakthrough curves, it can rapidly predict the process stability under dynamic control and assess the risks under feedstock variations or UV signal drifts. In conclusion, the model-based approach is a powerful tool for continuous process evaluation under dynamic changes and would be useful for establishing a new real-time dynamic control strategy.