Multi-column periodic counter-current chromatography (PCC) has been developed for continuous antibody capture, but the complexity of continuous processes makes experimental optimization time consuming and costly. In this work, with twin-column continuous system as a typical case, mathematical models were established and used to evaluate the impacts of operating parameters for process development. The model fitted well with the experimental breakthrough curves and process performance under varying protein concentrations and residence times. Three important operating parameters, residence time for interconnected feeding (RTC), breakthrough percentage control for interconnected feeding (s) and disconnected feeding time (tDC), were evaluated systematically. The profiles of productivity and resin capacity utilization showed three phases as a function of RTC, which resulted in different optimization strategies towards s and tDC. Based on the model prediction, a working window of RTC and s can be determined for process development. Finally, a model-based design approach was proposed to determine the optimum operating conditions and to design a suitable continuous process for high productivity and capacity utilization. With the model-based design approach developed, the best performance of 12.8 g/L/h productivity and 91.9% capacity utilization was found for MabSelect SuRe resin under 1 mg/mL feeding IgG concentration at RTC = 2 min, s = 65% and tDC = 26 min.
Keywords: Capacity utilization; Continuous chromatography; Mathematical model; Process design; Productivity.
Copyright © 2020. Published by Elsevier B.V.