Comparison of multi‐column chromatography configurations through model‐based optimization

Abstract

AbstractIntegrated continuous bioprocessing has been identified as the next important phase of evolution in biopharmaceutical manufacturing. Multiple platform technologies to enable continuous processing are being developed. Multi‐column counter‐current chromatography is a step in this direction to provide increased productivity and capacity utilization to capture biomolecules like monoclonal antibodies (mAbs) present in the reactor harvest and remove impurities. Model‐based optimization of two prevalent multi‐column designs, 3‐column and 4‐column periodic counter‐current chromatography (PCC) was carried out for different concentrations of mAbs in the feed, durations of cleaning‐in‐place and equilibration protocols. The multi‐objective optimization problem comprising three performance measures, namely, product yield, productivity, and capacity utilization was solved using the Radial basis function optimization technique. The superficial velocities during load, wash, and elute operations, along with durations of distinct stages present in the multi‐column operations were considered as decision variables. Optimization results without the constraint on number of wash volumes showed that 3‐Column PCC performs better than 4‐Column PCC. For example, at a feed concentration of 1.2 mg/mL, productivity, yield and capacity utilization, respectively, were 0.024 mg/mL.s, 0.94, and 0.94 for 3‐Column PCC and 0.017 mg/mL.s, 0.87, and 0.83 for 4‐column PCC. Similar trends were observed at higher feed concentrations also. However, when the constraint on number of wash volumes is included, 4‐Column PCC was found to result in consistent productivity and product yield under different operating conditions but at the expense of reduced capacity utilization.