Model based process optimization of an industrial chromatographic process for separation of lactoferrin from bovine milk.

Model based process development using predictive mechanistic models is a powerful tool for in-silico downstream process development. It allows to obtain a thorough understanding of the process reducing experimental effort. While in pharma industry, mechanistic modeling becomes more common in the last years, it is rarely applied in food industry.

Predictive scaling of fiber-based protein A capture chromatography using mechanistic modeling.

Protein A affinity chromatography is an important step in the purification of monoclonal antibodies (mAbs) and mAb-derived biotherapeutics. While the biopharma industry has extensive expertise in the operation of protein A chromatography, the mechanistic understanding of the adsorption/desorption processes is still limited, and scaling up and scaling down can be challenging because of complex mass transfer effects in bead-based resins. In convective media, such as fiber-based technologies, complex mass transfer effects such as film and pore diffusions do not occur which facilitates the study of the adsorption phenomena in more detail and simplifies the process scale-up.

Adsorption of organic molecules on carbon surfaces: Experimental data and molecular dynamics simulation considering multiple protonation states.

Owing to their high specific surface and low production cost, carbon materials are among the most important adsorption materials. Novel usages, for instance in pharmaceutical applications, challenge existing methods because charged and strongly polar substances need to be adsorbed. Here, we systematically investigate the highly complex adsorption equilibria of organic molecules having multiple protonation states as a function of pH.