Multi-column counter-current chromatography is an advanced technology used for continuous capture processes to improve process productivity, resin capacity utilization and product consistency. However, process development is difficult due to process complexity. In this work, some general and convenient guidances for three-column periodic counter-current chromatography (3C-PCC) were developed. Boundaries and distributions of operating windows of 3C-PCC processes were clarified by model-based predictions. Interactive effects of feed concentration (c0), resin properties (qmax and De), recovery and regeneration times (tRR) were evaluated over a wide range for maximum productivity (Pmax). Furthermore, variation of Pmax was analyzed considering the constraint factors (capacity utilization target and flow rate limitation). The plateau value of Pmax was determined by qmax and tRR. The operating conditions for Pmax were controlled by qmax, tRR and c0 interactively, and a critical concentration existed to judge whether the operating conditions of Pmax under constraints. Based on the comprehensive understanding on 3C-PCC processes, a model-free strategy was proposed for process development. The optimal operating conditions could be determined based on a set of breakthrough curves, which was used to optimize process performance and screen resins. The approach proposed was validated using monoclonal antibody (mAb) capture with a 3C-PCC system under various mAb and feed concentrations. The results demonstrated that a thorough model-based process understanding on multi-column counter-current chromatography is important and could improve process development and establish a model-free strategy for more convenient applications.
Keywords: Continuous capture process; Model-based approach; Periodic counter-current chromatography; Process development; Protein A affinity chromatography.
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