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

Area of Science:

• Biopharmaceutical Manufacturing
• Chemical Engineering
• Process Optimization

Background:

• Continuous chromatography is known for increased capacity.
• The economic impact of loading scenarios and column count in continuous chromatography remains underexplored.

Purpose of the Study:

• To evaluate four continuous multicolumn chromatography (MCC) loading scenarios for process performance and economics.
• To analyze the effect of feed concentration and residence time on MCC.
• To investigate the relationship between productivity and cost-effectiveness.

Main Methods:

• Computational chromatography model validation with experimental data.
• Prediction of process performance across various feed concentrations and residence times.
• Analysis of operating binding capacity, specific productivity, and column number.

Main Results:

• Processes with more columns showed up to 65% increased productivity, particularly at feed concentrations >5 g/L.
• Operating costs do not always correlate with discrete column sizing or productivity metrics.
• Adding columns for non-load steps at higher feed concentrations yielded up to 32% cost savings.

Conclusions:

• Optimizing loading scenarios and column numbers in MCC is crucial for economic viability in Protein A mAb capture.
• Higher productivity does not always equate to lower costs; strategic column addition is key.
• Continuous chromatography can achieve significant cost savings through optimized process design at high feed concentrations.