Gel compression considerations for chromatography scale-up for protein C purification

Area of Science:

• Biotechnology and Biomedical Engineering
• Chemical Engineering
• Separation Science

Background:

• Protein C deficiency is linked to deep vein thrombosis and embolism risk.
• Large-scale, cost-effective production of Protein C is crucial for prophylactic patient treatment.
• Current production methods require optimization for efficiency and scalability.

Purpose of the Study:

• To establish theoretical and experimental relationships for scaling up Immobilized Metal Affinity Chromatography (IMAC) and Immuno Affinity Chromatography.
• To optimize the production of Protein C for treating protein C deficiency.
• To analyze gel matrix properties and column stability under varying flow rates and pressures.

Main Methods:

• Analysis of gel matrices for column collapse characteristics and material properties.
• Examination of fluid flow rate and pressure drop effects on column stability.
• Application of Darcy's Law and Biot's consolidation theory, solved using finite difference and finite element methods (ABAQUS).
• Experimental measurements of void fraction (pulse testing) and yield stress for validation.
• Utilization of Total Quality Management (TQM) tools, including Taguchi techniques and Scatter Diagrams.

Main Results:

• Development of theoretical and experimental correlations for IMAC and Immuno Affinity Chromatography scale-up.
• Identification of relationships between gel properties, flow dynamics, and column stability.
• Validation of theoretical models through experimental data on flow rate, pressure drop, and yield stress.
• Optimization of gel selection and operating conditions using TQM and Taguchi methods.

Conclusions:

• Established theoretical and experimental frameworks for scalable Protein C purification.
• Demonstrated the importance of understanding gel-matrix interactions and fluid dynamics for chromatographic column stability.
• Successfully applied TQM principles to optimize research and development, simulating an industrial environment for efficient production of therapeutic proteins.