Chromatographic purification of therapeutic proteins is highly complex with respect to process input parameters. During process development the impact of these parameters has to be assessed thoroughly in order to achieve the desired product quality attributes. Especially for interrelated parameters often high experimental effort is needed for this assessment.<br/>Detailed mechanistic models or mathematical models based on first principles have been established for preparative chromatography. These models describe the underlying physicochemical principles of purification and summarize process knowledge. During process development we used steric mass action (SMA) models for the description and simulation of ion exchange chromatography.<br/>In different case studies we applied SMA models for both analyzing established process conditions and optimizing industrial purification methods of therapeutic proteins. Model calibration incorporated the impact of process parameters like pH, conductivity, impurities and load density. Model predictions were used to examine process output parameters such as yield, purity and robustness for wash steps, gradient and isocratic elution profiles.<br/>These unit operation-specific models provided in general improved process understanding and allowed for predicting the impact of parameter changes and model based design of new experiments. Therefore mechanistic modeling is a valuable tool for efficient development of robust preparative chromatography processes.

Mechanistic modeling of chromatography and its application in biopharmaceutical process development

251st National Meeting (2016)

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