Abstract

TEJEDA-MANSIR, Armando; BUSANI, Ivan; RENTERIA, Ma. Eugenia  and  MONTESINOS, Rosa Ma.. Adsorción de proteínas por afinidad en procesos por lotes: modelación, estimación de parámetros y simulación. Rev. Soc. Quím. Méx [online]. 2002, vol.46, n.1, pp.43-48. ISSN 0583-7693.

The scale-up and optimization of large-scale affinity chromatographic operations is of major industrial importance. The development of mathematical models and their use in computer programs to predict the performance of these chromatographic processes is an approach that can help to perform these bioprocess engineering tasks. In this work, a transport model which include pore diffusion, external film resistance, and finite kinetic rate, was used to mathematically describe the performance of a batch affinity adsorption system. Experimental data from literature describing the adsorption of β-galactosidase onto anti-β-galactosidase immobilized on porous silica was used as a model system. The differential equations system of the mathematical model was solved using the numerical method of lines (NUMOL) with a Runge-Kutta-Fehlberg integration algorithm. This solution was compared with a simpler one, given by the analytical solution of the lumped parameters model. The best fit to the experimental data was obtained with the transport model solution, however, the fit with the lumped parameters model was accurate too. The use of the transport model allowed to obtain the protein concentration profiles in the liquid inside the adsorbent pores and in the solid phase of the adsorbent. The sharp concentration profiles observed during the initial step of the adsorption process in both phases, showed a very high mass-transfer rate in this experimental system. Only under this condition the results using transport model and the lumped parameters model are very close. The use of the transport model is a unique way to predict batch affinity performance as well as to obtain a better understanding of the fundamental mechanisms responsible for the bioseparations.

Keywords : Affinity chromatography; simulation; mathematical models.

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