Column chromatography is a crucial process for the isolation of biologically active compounds. However, the development of an optimal chromatographic process is lengthy and expensive for each molecule. Therefore, in recent years, the in silico description of column chromatography has been increasingly used for this purpose, and chromatographic models are employed to aid in process development. Mechanistic models of column chromatography are models based on physical equations derived from first principles. In this master’s thesis, we explore and analyze various chromatographic models. In the first part of the thesis, we focus on building a model of an ideal column with the Langmuir adsorption isotherm, while in the second part, with the help of specialized software GoSilico and experimental data, we set up and calibrate a more detailed model of ion-exchange chromatography with a more complex steric mass adsorption isotherm, which we use to solve several process optimization problems. The work is generally aimed at developing an understanding of the key mechanisms and methods for describing various chromatographic systems and conditions.
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