Optimized Continuous Multicolumn Chromatography Enables Increased Productivities and Cost Savings by Employing More Columns.

The advantages of continuous chromatography with respect to increased capacity are well established. However, the impact of different loading scenarios and total number of columns on the process economics has not been addressed. Here four different continuous multicolumn chromatography (MCC) loading scenarios are evaluated for process performance and economics in the context of a Protein A mAb capture step. To do so, a computational chromatography model is validated experimentally. The model is then used to predict process performance for each of the loading methods. A wide range of feed concentrations and residence times are considered, and the responses of operating binding capacity, specific productivity, and the number of process columns are calculated. Processes that are able to add more columns proved to be up to 65% more productive, especially at feed concentrations above 5 g L-1 . An investigation of the operating costs shows that discrete column sizing and process performance metrics do not always correlate and that the most productive process is not necessarily the most cost effective. However, adding more columns for the non-load steps at higher feed concentrations allows for overall cost savings of up to 32%.

Scale-up of continuous multicolumn chromatography for the protein a capture step: From bench to clinical manufacturing.

The awareness about implementing continuous processing for biopharmaceutical products has significantly increased throughout the recent years not only at developmental scale but also for phase I supply in clinical trial manufacturing. In this study, we focused on upscaling continuous protein A chromatography from lab to pilot scale using the Cadence™ BioSMB PD and the Cadence™ BioSMB Process 80 system, respectively. Additionally, we evaluated hardware and software capability whilst running the system for 10 days non-stop using feed from a perfusion bioreactor. In terms of product quality and removal of impurities, comparable data was obtained regarding lab scale and production scale. Compared to batch mode, productivity was increased by 400 to 500%. Furthermore, the system worked accurately during the whole trial, proving its potential for the implementation into a hybrid or an end-to-end continuous process.

Phase behavior of an intact monoclonal antibody.

Understanding protein phase behavior is important for purification, storage, and stable formulation of protein drugs in the biopharmaceutical industry. Glycoproteins, such as monoclonal antibodies (MAbs) are the most abundant biopharmaceuticals and probably the most difficult to crystallize among water-soluble proteins. This study explores the possibility of correlating osmotic second virial coefficient (B(22)) with the phase behavior of an intact MAb, which has so far proved impossible to crystallize. The phase diagram of the MAb is presented as a function of the concentration of different classes of precipitants, i.e., NaCl, (NH4)2SO4, and polyethylene glycol. All these precipitants show a similar behavior of decreasing solubility with increasing precipitant concentration. B(22) values were also measured as a function of the concentration of the different precipitants by self-interaction chromatography and correlated with the phase diagrams. Correlating phase diagrams with B(22) data provides useful information not only for a fundamental understanding of the phase behavior of MAbs, but also for understanding the reason why certain proteins are extremely difficult to crystallize. The scaling of the phase diagram in B(22) units also supports the existence of a universal phase diagram of a complex glycoprotein when it is recast in a protein interaction parameter.