{BACKGROUND Continuous multicolumn Protein A chromatography offers various advantages for capture stage purification of monoclonal antibody therapeutics, like higher productivity and resin capacity utilization, lower buffer consumption, small footprint, etc. Due to the complexity of the continuous process, experimental optimization is time-consuming and cost-intensive. This investigation proposes a hybrid process development approach integrating experimental and mechanistic modeling for time- and cost-effective development and optimization of continuous Protein A affinity chromatography. RESULTS Productivity and capacity utilization of the continuous CaptureSMB process under varying operating conditions were predicted using the Chromatography Analysis and Design Toolkit (CADET) framework and validated with experimental results. Effects of critical process parameters like feed concentration (c(0)), loading breakthrough (s) and residence time (RT) on productivity and capacity utilization were evaluated. Model predictions were validated using the experimental results proving the reliability and feasibility of the modeling approach. At 15.00 +/- 0.20 mg mL(-1) feed model mAb concentration, the model-based approach predicted the best performance giving 27.56 g L-1 h(-1) productivity (RT = 2 min

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