Model-based optimization of a preparative ion-exchange step for antibody purification.

A method using a model-based approach to design and optimize an ion-exchange step in a protein purification process is proposed for the separation of IgG from a mixture containing IgG, BSA and myoglobin. The method consists of three steps. In the first step, the model is calibrated against carefully designed experiments. The chromatographic model describes the convective and dispersive flow in the column, the diffusion in the adsorbent particles, and the protein adsorption using Langmuir kinetics with mobile phase modulators (MPM). In the second step, the model is validated against a validation experiment and analyzed. In the third and final step, the operating conditions are optimized. In the optimization step, the loading volume and the elution gradient are optimized with regard to the most important costs: the fixed costs and the feed cost. The optimization is achieved by maximizing the objective functions productivity (i.e. the production rate for a given amount of stationary phase) and product yield (i.e. the fraction of IgG recovered in the product stream). All optimization is conducted under the constraint of 99% purity of the IgG. The model calibration and the analysis show that this purification step is determined mainly by the kinetics, although as large a protein as IgG is used in the study. The two different optima resulting from this study are a productivity of 2.7 g IgG/(s m3) stationary phase and a yield of 90%. This model-based approach also gives information of the robustness of the chosen operating conditions. It is shown that the bead diameter could only be increased from 15 microm to 35 microm with maximum productivity and a 99% purity constraint due to increased diffusion hindrance in larger beads.