Integrated Continuous Biomanufacturing reduces manufacturing costs while maintaining product quality. A key contributor to high biopharmaceutical costs, specifically monoclonal antibodies (mAbs), is chromatography. Protein A ligands are usually preferred but still expensive in the manufacturing context, and batch chromatography under-utilizes the columns' capacity, compromising productivity to maintain high yields. Continuous chromatography increases columns' Capacity Utilization (CU) without sacrificing yield or productivity. This work presents the in-silico optimization of a 3 Column Periodic Counter-current Chromatography (3C-PCC) of a capture and polishing step for mAbs from a high titer harvest (c_mAb = 5 g/L). The 3C-PCC was modeled and Pareto-fronts for continuous and batch modes were used to optimize the 3C-PCC steps varying the flow rate and percentage of breakthrough achieved in the interconnected loading, maximizing Productivity and CU, for varying concentrations of mAb (batch mode concentration of 5 g/L and continuous mode concentration of 2.5, 5, 7.5, and 10 g/L). The shape of the breakthrough curve significantly impacts the optimization of 3C-PCC. The model output was validated for three different protein A ligands using a pure mAb solution. MAb Select SuRe pcc was selected to continuously capture mAb from a high-titer clarified cell culture supernatant (harvest). The product eluates were pooled and used for continuous polishing using a Cation-Exchange resin (CaptoS ImpAct). Experimental results validated model predictions (<7% deviation in the worst case) and a process with two 3C-PCC in sequence was proposed, with a productivity of approximately 100 mg/mL res/h.

The monoclonal antibody (mAb) industry is becoming increasingly digitalized. Digital twins are becoming increasingly important to test or validate processes before manufacturing. High-Throughput Process Development (HTPD) has been progressively used as a tool for process development and innovation. The combination of High-Throughput Screening with fast computational methods allows to study processes in-silico in a fast and efficient manner. This paper presents a hybrid approach for HTPD where equal importance is given to experimental, computational and decision-making stages. Equilibrium adsorption isotherms of 13 protein A and 16 Cation-Exchange resins were determined with pure mAb. The influence of other components in the clarified cell culture supernatant (harvest) has been under-investigated. This work contributes with a methodology for the study of equilibrium adsorption of mAb in harvest to different protein A resins and compares the adsorption behavior with the pure sample experiments. Column chromatography was modelled using a Lumped Kinetic Model, with an overall mass transfer coefficient parameter (k_ov). The screening results showed that the harvest solution had virtually no influence on the adsorption behavior of mAb to the different protein A resins tested. k_ov was found to have a linear correlation with the sample feed concentration, which is in line with mass transfer theory. The hybrid approach for HTPD presented highlights the roles of the computational, experimental, and decision-making stages in process development, and how it can be implemented to develop a chromatographic process. The proposed white-box digital twin helps to accelerate chromatographic process development.