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%.
Keywords: continuous chromatography; economics; multicolumn process.
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