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Linear isotherm determination from linear gradient elution experiments.

David Pfister1, Fabian Steinebach1, Massimo Morbidelli1

  • 1Institute for Chemical and Bioengineering, Department of Chemistry and Applied Bioscience, ETH Zurich, 8093 Zurich, Switzerland.

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|December 16, 2014
PubMed
Summary
This summary is machine-generated.

A new method estimates adsorption parameters in chromatography using linear gradient elution. This accounts for size exclusion differences between proteins and modifiers, improving accuracy for modifier concentration effects.

Keywords:
Chromatography modelExclusion effectLinear gradient elutionParameter estimation

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Area of Science:

  • Chromatography
  • Adsorption Science
  • Chemical Engineering

Background:

  • Analytical solutions for linear gradient elution chromatography often assume equal access of proteins and modifiers to porous particle pores.
  • This assumption overlooks the size exclusion effect, where different molecules may access different pore fractions.

Purpose of the Study:

  • To develop a procedure for estimating equilibrium adsorption parameters as a function of modifier concentration in linear gradient elution chromatography.
  • To account for the size exclusion effect impacting protein and modifier access to pore sizes.

Main Methods:

  • Derived a new analytical solution using perturbation theory for differential equations.
  • Presented the 1st-order approximated solution to model the system.
  • Validated the procedure by comparing with experimental data.

Main Results:

  • The developed procedure reliably estimates isotherm parameters across varying modifier concentrations.
  • The new analytical solution accurately models systems with differential size exclusion effects.
  • The method provides a turnkey solution for analyzing linear gradient elution experiments.

Conclusions:

  • The proposed procedure offers a reliable and efficient method for estimating adsorption parameters in chromatography.
  • Accounting for size exclusion significantly improves the accuracy of models under linear gradient elution.
  • This advancement facilitates better understanding and optimization of chromatographic separations.