Finding the best purification process is a challenging task. Recently, mechanistic models that can accelerate the development of chromatographic unit operations, the most important purification units, became widely available. In previous work, several chromatographic models have
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Finding the best purification process is a challenging task. Recently, mechanistic models that can accelerate the development of chromatographic unit operations, the most important purification units, became widely available. In previous work, several chromatographic models have been linked together to simulate and optimize integrated processes. However, considering only chromatographic steps may lead to a suboptimal process. Consequently, the aim of this study was to include models for ultra- and diafiltration units into the optimization approach to account for buffer exchange steps before or between chromatography units. This approach was applied to an industrial case, the purification of a monoclonal antibody, where cation exchange, hydrophobic interaction and mixed mode were the possible chromatographic separation modes. It turned out that only the duration of the total filtration step and the duration of the ultrafiltration step were crucial variables for the optimization of the ultra- and diafiltration steps. The ‘best’ in silico purification process was found based on the performance criteria yield and solvent usage. The purity was required to be at least 99.9%.
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