2016 AIChE Annual Meeting
(194c) Protein a Resin Evaluation in a Chromatography Process through Process Modeling and Doe Approach
Authors
Behere, K. - Presenter, University of Mass Lowell
Yoon, S., University of Massachusetts Lowell
Increased product yield at reduced cost and time has been the driving force of any manufacturing process. However, inevitable increase in future demand for biopharmaceutical drugs, along with intensified competition and stringent regulatory laws have exhibited an imperative need for established platform processes. In this regard, the implementation of continuous processing, in whole or in components, has demonstrated to increase the manufacturing productivity with key impact on speed, cost and facility implications. The Protein A chromatography process as a capture step has shown enormous potential in terms of high affinity to the mAb, translating to higher purity and considerable reduction in volume for downstream polishing steps. However, Protein A resin costs remains a high contributor to the overall economics of the mAb purification process. Protein A resin is considered to be highly sensitive and loses its performance efficiency after 100-120 sanitization cycles. We have approached the Protein A degradation as a leaching problem primarily caused by caustic in the sanitization phase. A Shrinking Core Model (SCM) was utilized to explain the Protein A leaching kinetics in the column. The model parameters viz rate constant, stoichiometry factor and effective diffusivity were further estimated and validated with Protein A affinity chromatography batch and breakthrough experiments. The binding capacity of Protein A resin in terms of residual Protein A ligands was appraised for process efficiency. A 3-level fractional factorial DOE study using MODDE was performed to describe the leaching mechanism by varying caustic concentration, with or without product and three different resins. A regression model was developed in SIMCA to ascertain the resin lifetime. The results and associated outcome confirmed that this model can be employed to predict the column conditions during 100-120 operating cycles. The model can also be applied as a decision tool for column switching in a continuous separation. The approach elucidates the conditions required to perform the affinity separation for mAb capture step, with indications of improving the resin performance and extending the resin lifetime. The outcomes of the evaluated approach supports the optimized utilization of the Protein A resin in continuous processing for improved biomanufacturing.