Mechanistic modeling of continuous capture step purification of biosimilar monoclonal antibody therapeutic

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, s = 80%) using MabSelect (TM) PrismA resin. This productivity prediction was validated by performing the continuous CaptureSMB experiment at the same operating conditions and was found to be 25.59 g L-1 h(-1) with a root mean square error of 1.96. CONCLUSIONS The hybrid process development and optimization approach for CaptureSMB purification of biosimilar mAb purification is demonstrated and validated using the experimental and model-based framework. The observed results showcase the effectiveness of the proposed hybrid process development approach, enabling a better understanding of the chromatography process and parameters affecting the CaptureSMB process. (c) 2021 Society of Chemical Industry (SCI).