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The Importance of Correct Protein Concentration for Kinetics and Affinity Determination in Structure-function Analysis

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Short-cut method for predicting the productivity of affinity chromatography.

S Yamamoto¹, Y Sano

¹Department of Chemical Engineering, Yamaguchi University, Ube, Japan.

Journal of Chromatography

|April 24, 1992

Summary

A new method predicts affinity chromatography (AFC) productivity by analyzing breakthrough curves. It identifies optimal operating speeds (uM) for maximizing protein recovery, aiding in process scale-up.

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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.