Mechanistic models have demonstrated utility in optimizing chromatography performance.  Simulations utilizing the chromatography analysis design toolkit (CADET) with a multicomponent steric mass action isotherm have allowed reduced experimentation and improved visualization in process development.  In order to effectively predict column performance with the model, the isotherm parameters must first be estimated by pulse gradient experiments or back fitting to the experimental elution profiles.  This poster presents a comparison of methods for back-fitting the model to experimental cation exchange purification data for parameter estimation in a monoclonal antibody purification process.  Multiple optimization algorithms, including a genetic search heuristic were utilized in order to estimate the parameters that provided the best fit to process development data.

Method comparison for determining steric mass action isotherm parameters for a multicomponent chromatography model

249th National Meeting (2015)

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