Continuous multicolumn Protein A chromatography offers various advantages for capture stage purification of monoclonal antibody therapeutics, like higher productivity and resin capacity utilization, low buffer consumption, and small footprint, etc. Due to the complexity of the continuous process, experimental optimization is time-consuming and inefficient. In this work, Chromatography Analysis and Design Toolkit (CADET) framework-based modeling approach was proposed, investigated, and validated to improve the efficiency of twin-column continuous chromatography process development. Productivity and capacity utilization (C.U.) of continuous processes under varying operating conditions were predicted using the CADET framework and compared with the experimental results. Effect of critical process parameters like feed concentration (c<sub>0</sub>), loading breakthrough percentage (s), and residence time (R.T.) 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 mg/mL feed IgG concentration, the model-based approach predicts the best performance giving 27.56 g/L/h productivity (RT= 2 minute, s=80 %) on MabSelect™ PrismA resin. This productivity prediction was validated by performing the continuous capture experiment at the same operating conditions and found to be 25.59 g/L/h with an RMSE of 1.96.

Mechanistic modeling of twin-column continuous protein A chromatography

ACS Fall 2021

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