A Thermodynamic Approach for the Prediction of Oiling Out Boundaries from Solubility Data

Abstract

Many pharmaceutical molecules, fine chemicals, and proteins exhibit liquid–liquid phase separation (LLPS, also known as oiling out) during solution crystallization. LLPS is of significant concern in crystallization process development, as oiling out can compromise the effectiveness of a crystallization and can lead to operational problems. A comprehensive methodology that allows a process scientist/engineer to characterize the various phase boundaries relevant to oiling out is currently lacking. In this work, we present a modeling framework useful in predicting the binodal, spinodal, and gelation boundaries starting from the solubility data of a solute that is prone to oiling out. We collate the necessary theoretical concepts from the literature and describe a unified approach to model the phase equilibria of solute–solvent systems from first principles. The modeling effort is validated using experimental data reported in the literature for various solute–solvent systems. The predictive methods presented in this work can be easily implemented and help a process engineer establish the design space for a crystallization process that is affected by liquid–liquid phase separation.