Short-cut method for predicting the productivity of affinity chromatography

Area of Science:

• Biochemical Engineering
• Separation Science
• Chromatography

Background:

• Affinity chromatography (AFC) is crucial for protein purification.
• Predicting productivity is essential for efficient process scale-up.
• Current methods may lack precision in optimizing operating conditions.

Purpose of the Study:

• To develop a predictive method for affinity chromatography (AFC) productivity.
• To identify the optimal operating velocity (uM) for maximum protein recovery.
• To validate the method across diverse chromatographic media.

Main Methods:

• Employed a constant-pattern approach to model breakthrough curves.
• Derived the optimal velocity (uM) as a function of the number of transfer units (n).
• Experimentally measured breakthrough curves using various packing materials (porous, non-porous, membrane).

Main Results:

• Productivity (P) increases with velocity (u) at low values, exhibiting a maximum.
• Determined 'n' values from experimental data for different media.
• Calculated uM values based on determined 'n' values.

Conclusions:

• The developed method accurately predicts AFC productivity.
• The method facilitates rapid optimization of operating conditions for AFC scale-up.
• This approach is applicable to various chromatographic systems and media.