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Journal article

Lumped parameter model for prediction of initial breakthrough profiles for the chromatographic capture of antibodies from a complex feedstock

From

Computer Aided Process Engineering Center, Department of Chemical and Biochemical Engineering, Technical University of Denmark1

Department of Chemical and Biochemical Engineering, Technical University of Denmark2

A simple mathematical model to predict initial breakthrough profiles from preparative chromatographic separations of biological macromolecules has been developed. A lumped parameter approach was applied, employing Langmuirian adsorption kinetics to describe the rate of mass transfer (MT) from the bulk liquid in the column to the bound state.

Equilibrium and kinetic adsorption data were determined for six different packed bed chromatographic adsorbents: two derivatised with rProtein A; and four functionalised with synthetic low molecular weight ligands. All adsorption isotherms were well described by the Langmuir model, whereas the data fitting to kinetic batch experiments showed that the model was inadequate after the first approximately 25 min of adsorption for four of the six adsorbents.

The model underestimated the dynamic Ig breakthough on packed beds of rProtein A Sepharose FF, MabSelect, MBI HyperCel, and MabSorbent A1P, applying a feedstock of 20-100% (v/v) clarified rabbit antiserum. However, when employing a maximum adsorption capacity 25% greater than that determined in batch binding studies, excellent agreement was obtained at all antiserum strengths for most adsorbents.

Useful insights into scale-up and process design can be obtained by applying the model, without determining tentative parameters specific for each adsorbent and target protein concentration. However, the model parameters are solvent dependent so a prerequisite for its true applicability is that binding is both Langmuirian and essentially independent of the ionic strength of the feedstock applied.

Language: English
Year: 2007
Pages: 131-141
ISSN: 1873376x , 15700232 , 18785603 and 13872273
Types: Journal article
DOI: 10.1016/j.jchromb.2006.07.020
ORCIDs: Abildskov, Jens

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