Model-based design of peptide chromatographic purification processes

In this work we present a general procedure for the model-based optimization of a polypeptide crude mixture purification process through its application to a case of industrial relevance. This is done to show how much modeling can be beneficial to optimize complex chromatographic processes in the industrial environment. The target peptide elution profile was modeled with a two sites adsorption equilibrium isotherm exhibiting two inflection points. The variation of the isotherm parameters with the modifier concentration was accounted for. The adsorption isotherm parameters of the target peptide were obtained by the inverse method. The elution of the impurities was approximated by lumping them into pseudo-impurities and by regressing their adsorption isotherm parameters directly as a function of the corresponding parameters of the target peptide. After model calibration and validation by comparison with suitable experimental data, Pareto optimizations of the process were carried out so as to select the optimal batch process.

► A general procedure for the model-based optimization of a peptide purification process is presented.
► The peptide and impurities model parameters are determined experimentally.
► The model is used for Pareto optimization of the process.
► The model prediction validity is tested against suitable set of experimental data.