Predicting the performance of chromatographic columns in protein purification processes.
The commercial success of chromatographic methods in large scale protein purification has created a strong demand for predictive techniques which will directly aid the design, scale-up and optimization of the process. This article examines the current state in the development of such techniques which depend for success not only on system analysis and modelling, but also on the collection of appropriate experimental data. A specific mathematical model describing non-porous particle adsorption (NPPAM) developed by the authors, which is simple to use on readily available equipment, is outlined. Examples of using NPPAM for predicting column performance are given, as well as the potential of applying the model in process simulation and optimization.
Department of Biochemistry, Monash University, Clayton, Vic., Australia.
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Mao
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Prince
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Hearn
D000327:Adsorption; D002845:Chromatography / Q000379:methods / Q000592:standards* / Q000706:statistics & numerical data; D003198:Computer Simulation; D008433:Mathematics; D008863:Microspheres; D009113:Muramidase / Q000302:isolation & purification; D011506:Proteins / Q000302:isolation & purification*; D011786:Quality Control
D011506:Proteins; D009113:Muramidase