A framework for the prediction of scale-up when using compressible chromatographic packings.
Experimental data are given for the solid pressure distributions in chromatography columns of various column aspect ratios packed with four types of agarose-based resin. The loss of column wall support at large scales can result in unexpectedly high pressures caused by the compression of the matrix via drag forces exerted by fluid flow through the bed. The need for an accurate model to predict flow conditions at increasing scale is essential for the scaling-up of chromatographic processes and for avoiding bed compression during operation. Several studies have generated correlations that allow for the prediction of column pressure drops, but they either are mathematically complex, which impairs their practical use, or require a large number of experiments to be performed before they can be used. In this study an empirical correlation was developed based on a previously proposed model, which links the critical velocity of operation of a chromatographic system (microcrit), to the gravity-settled bed height (L0), the column diameter (D), the feed viscosity (micro), and the compressibility of the chromatographic media used (micro 10%). The methodology developed in this study is straightforward to use and significantly reduces the burden of preceding laboratory-scale experimentation. The approach can be used to predict the critical velocity of any chromatographic system and will be useful in the development of chromatographic operations and for column sizing.
Tran
Richard
R
Innovative Manufacturing Research Centre, Advanced Centre for Biochemical Engineering, University College London, Torrington Place, London WC1E 7JE, United Kingdom.
Joseph
John R
JR
Sinclair
Andrew
A
Bracewell
Daniel
D
Zhou
Yuhong
Y
Titchener-Hooker
Nigel J
NJ
D001704:Biopolymers / Q000737:chemistry* / Q000302:isolation & purification*; D002847:Chromatography, Agarose / Q000295:instrumentation* / Q000379:methods*; D019245:Compressive Strength; D003198:Computer Simulation; D017076:Computer-Aided Design; D004867:Equipment Design; D019544:Equipment Failure Analysis; D044085:Microfluidics / Q000379:methods*; D008956:Models, Chemical; D010865:Pilot Projects; D011312:Pressure
D001704:Biopolymers