(257d) A Refined Non-Random Two-Liquid Segment Activity Coefficient Model for Solubility Modeling | AIChE

(257d) A Refined Non-Random Two-Liquid Segment Activity Coefficient Model for Solubility Modeling

Authors 

Hao, Y. - Presenter, Texas Tech University
Chen, C. C. - Presenter, Texas Tech University

Accurate correlation and robust prediction for drug molecule solubility or solid-liquid equilibrium (SLE) in solvents and solvent mixtures have drawn much interest recently [Tanveer et al., Chem. Eng. Prog. 2014, 110 (9), 37-47]. Solubility models such as the Non-Random Two Liquid Segment Activity Coefficient (NRTL-SAC) model [Chen and Song, Ind. Eng. Chem. Res. 2004, 43, 8354-8362] are now routinely used in the pharmaceutical industry. However, an important unfilled need is to model drug solubility in polymers/surfactants for lipid-based or solid dispersion formulation [Tung, Org. Proc. Res. Dev. 2013, 17, 445-454]. This paper presents a refinement to the very successful NRTL-SAC model to better account for the contribution due to size differences of molecules. Specifically, the model is refined by substituting the Flory-Huggins combinatorial entropy expression with the Staverman-Guggenheim expression. We present the rationale for the refined model, the updated conceptual segment numbers for common solvents, and the newly identified conceptual segment numbers for common drug excipients. The refined NRTL-SAC model offers enhanced capability to correlate and predict drug molecule solubility in common solvents and excipients used in drug formulation.