In various adsorptive formats�microtiter plates, batch systems, differential reactors, conventional batch chromatography, and simulated moving beds or other effectively countercurrent techniques�mathematical models are developed and tested against experimental data. In order to improve model fits, additional terms may be included, e.g., it is quite common to add surface diffusion to film mass-transfer and pore diffusion in order to conform better to dynamic batch uptake data. However, it is not always clear that the experimental data is rich enough to identify uniquely all the parameters contained within a particular model. The adequacy of the data becomes more problematic as the number of competitive species in the system increases and the nonlinear interactions among the species become more complex. Model identifiability is evaluated for various experimental formats. The need for global optimization methods to ensure appropriate parameter estimation is stressed. If models of varying complexity are used to fit data obtained in different formats, identifying the �right� model to use for scale-up is not obvious. An approach to reconcile data across scales is proposed. Experimental data in various formats is generated for a protein mixture, and �best� models for each format identified in this competitive case-study. Finally, the appropriate scale-up model is developed and tested.

Scale-adapted chromatographic models and implications for scale-up

247th National Meeting (2014)

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