Model-based process development and evaluation of twin-column continuous capture processes with Protein A affinity...

Area of Science:

• Biotechnology
• Chemical Engineering
• Biopharmaceutical Manufacturing

Background:

• Multi-column continuous chromatography offers advantages in resin utilization, productivity, and resource efficiency.
• Experimental optimization of continuous chromatography is complex and time-consuming.

Purpose of the Study:

• To investigate a model-based approach for optimizing twin-column continuous chromatography process development.
• To evaluate the impact of key operating parameters on productivity and capacity utilization (CU).

Main Methods:

• Development and application of a predictive model for breakthrough curves, productivity, and CU.
• Evaluation of feed concentration (c0), interconnected feed residence time (RT), and breakthrough percentage control (s).
• Experimental verification of model-predicted optimal conditions.

Main Results:

• The model accurately predicted process performance under various conditions.
• Optimal ranges for RT (1-2 min) and s (0.6-0.75) were identified for IgG capture with MabSelect PrismA.
• Maximum productivity ranged from 14 to 47 g/L/h across feed concentrations of 1-10 mg/mL.

Conclusions:

• Model-based optimization is a feasible and reliable method for continuous chromatography process development.
• Contour maps can guide the selection of operating windows to balance productivity and CU.
• This approach facilitates efficient process development and target-oriented design for continuous bioprocesses.