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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