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Development of a Segmented Model for a Continuous Electrophoretic Moving Bed Enantiomer Separation
Author(s) -
Thome Brian M.,
Ivory Cornelius F.
Publication year - 2003
Publication title -
biotechnology progress
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.572
H-Index - 129
eISSN - 1520-6033
pISSN - 8756-7938
DOI - 10.1021/bp034072g
Subject(s) - simulated moving bed , separation process , scaling , separation (statistics) , enantiomer , biological system , chemistry , mechanics , volumetric flow rate , process (computing) , chromatography , computer science , mathematics , physics , statistics , adsorption , geometry , organic chemistry , biology , operating system
Abstract With the recent demonstration of a continuous electrophoretic “moving bed” enantiomer separation at mg/h throughputs, interest has now turned to scaling up the process for use as a benchtop pharmaceutical production tool. To scale the method, a steady‐state mathematical model was developed that predicts the process response to changes in input feed rate and counterflow or “moving bed” velocities. The vortex‐stabilized apparatus used for the separation was modeled using four regions based on the different hydrodynamic flows in each section. Concentration profiles were then derived on the basis of the properties of the Piperoxan‐sulfated β‐cyclodextrin system being studied. The effects of different regional flow rates on the concentration profiles were evaluated and used to predict the maximum processing rate and the hydrodynamic profiles required for a separation. Although the model was able to qualitatively predict the shapes of the concentration profiles and show where the theoretical limits of operation existed, it was not able to quantitatively match the data from actual enantiomer separations to better than 50% accuracy. This is believed to be due to the simplifying assumptions involved, namely, the neglect of electric field variations and the lack of a competitive binding isotherm in the analysis. Although the model cannot accurately predict concentrations from a separation, it provides a good theoretical framework for analyzing how the process responds to changes in counterflow rate, feed rate, and the properties of the molecules being separated.