Role of Mechanistic Modeling in Optimization and Control of Bioseparation Processes

The initiatives of Quality by Design (QbD) and Process Analytical Technology (PAT) have gained momentum in the biopharmaceutical industry. Central to both is the necessity to gain a deep understanding of the process and identify the primary sources of process variability. This talk will highlight the benefits that the industry can gain by performing mechanistic modelling. Two case studies will be presented. In the first case study prediction of the impact of variability in feed quality and in gradient shape on separation of charge variants by cation exchange process chromatography has been attempted to facilitate feed forward control. Five batches having different compositions of charge variants have been used to demonstrate the proposed pooling strategy based on simulated chromatograms and the outcome has been compared to offline pooling based on fractionation. For all the conditions examined and for the desired target of main product (67%), the proposed approach resulted in remarkable consistency in product quality (67±2%) while delivering a yield of greater than 90%. In the second case study, ultrafiltration of a monoclonal antibody product to a high concentration (> 150 mg/ml) has been modelled. It has been seen that when protein concentration goes to such high level, deviations in pH and excipient concentrations are observed. Mechanistic model of the step has been created and used to improve process control. The two case studies showcase the utility of process modelling in process optimization and control.