Simulation of Frontal Protein Affinity Chromatography Using MATLAB

Abstract

In this study a transport model that includes axial dispersion in the bulk liquid, pore diffusion, external film resistance and finite kinetic rate, was used to mathematically describe a frontal affinity chromatography system. The corresponding differential equations system was solved in a simple and accurate form by using the numerical method of lines implemented in MATLAB. The solution was compared with experimental data from literature and the analytic Thomas solution. The frontal affinity chromatography of lysozyme to Cibacron Blue Sepharose was used as a model system. A good fit to the experimental data was obtained with the simulated runs of the transport model using this methodology. This approach was used to perform a parametric analysis of the experimental frontal affinity system. The solution of the transport model results in simple way to predict frontal affinity performance as well a better understanding of the fundamental mechanisms responsible for the separation.

The use of predictive models to develop chromatography-based purification processes

“…Elution experiments for inverse fitting can be complemented with frontal experiments, where a column is loaded until protein breakthrough, to increase the precision of parameter values or to determine additional model parameters such as the shielding factor of the SMA isotherm ( Osberghaus et al, 2012a ). The latter requires no limitation on liquid film and pore diffusion mass transfer, which would otherwise distort the chromatogram shape and thus the isotherm parameter values ( Persson et al, 2004 ; Seidel-Morgenstern 2004 ; German 2012 ). If frontal analysis alone is used for isotherm parameter determination, multiple breakthrough experiments are needed spanning a range of feed protein concentrations (e.g., 1–100 mM) to determine corresponding stationary phase concentrations at equilibrium ( Andrzejewska et al, 2009 ; Kamarei et al, 2014 ).…”