Hydrophobic Interaction Chromatography (HIC) is a chromatographic separation technique that is today successfully used for the purification of proteins. However, to achieve highly efficient separations, key operating parameters – like pH and ionic strength – must be well tuned. For this purpose, modeling tools can be of great help to minimize the experimental burden.
Yohann Le Guennec demonstrates that statistic models derived from DoE analysis cannot reproduce pH and ionic strength effects observed in HIC, and are thus not adapted for HIC process development and optimization.
He provides fundamentals on chromatography modeling and presents a new mechanistic model that was shown to accurately describe experimental data. Lastly, he illustrates how mechanistic modeling can improve process understanding and lead to the optimization of a HIC process performances.
Watch the full video below: