Statistically-aided development of protein A affinity chromatography for enhancing recovery and controlling quality of a monoclonal antibody

Protein A chromatography is widely used for isolation of monoclonal antibodies (mAbs) from cell culture components. In this study, the effect of different process parameters of the Protein A purification namely, binding pH, elution pH, flow rate, neutralization pH and tween concentration, on the concentration and quality of the purified mAb were evaluated. Using design of experiments approach, the critical process parameters of protein A chromatography were identified and experimentally optimized. Their impact on quality attributes, such as size variants and charge variants, of the mAb was studied. Multivariate data analysis was subsequently performed using multiple linear regression and partial least squares regression methods. It was observed that the elution pH primarily governed the concentration of the purified mAb and the content of monomers and aggregates, while the tween concentration primarily influenced the main peak of the charge variants. This is the first study that evaluates the impact of tween concentration in buffers on the protein A chromatography purification step. These studies helped in identifying the design space and defining the target robust and optimal setpoints of the responses, which were subsequently verified experimentally. These setpoints not only passed the target criteria but also resulted in the highest recoveries during the investigation. Through this statistically-aided approach, an optimized and robust protein A chromatography process was rationally developed for purification of mAbs, while achieving the desired product quality. This study highlights the influence of multiple parameters of the protein A purification process on critical quality attributes of mAbs, such as the size and charge variants, which has been a very scarcely explored area.