The downstream processing of therapeutic proteins is a challenging task. Key information needed to estimate applicable workup strategies (e.g. crystallization) are the interactions of the proteins with other components in solution. This information can be deduced from the second osmotic virial coefficient B22 , measurable by static light scattering. Thermodynamic models are very valuable for predicting B22 data for different process conditions and thus decrease the experimental effort. Available B22 models consider aqueous salt solutions but fail for the prediction of B22 if an additional polymer is present in solution. This is due to the fact that depending on the polymer concentration protein-protein interactions are not rectified as assumed within these models. In this work, we developed an extension of the xDLVO model to predict B22 data of proteins in aqueous polymer-salt solutions. To show the broad applicability of the model, lysozyme, γ-globulin and D-xylose ketol isomerase in aqueous salt solution containing polyethylene glycol were considered. For all proteins considered, the modified xDLVO model was able to predict the experimentally observed non-monotonical course in B22 data with high accuracy. When used in an early stage in process development, the model will contribute to an efficient and cost effective downstream processing development.
Keywords: Modeling second osmotic virial coefficient; Polymer influence on proteins; Protein solubility; Protein-protein interactions.
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