ABSTRACT
The solubilization power of a cosolvent is defined based on the maximum solubility of a solute in the water-cosolvent mixtures (X(m,max)) and the corresponding solvent composition (f(c,max)) predicted by trained versions of the Jouyban-Acree model. The applicability of the proposed definition was checked using solubility data of three cosolvent systems where the solubilization power was ordered as: dioxane > ethanol > polyethylene glycol 400. Using this definition, one could select the most appropriate cosolvent for solubilization of a poorly water soluble drug. There are linear relationships between the solubilization power of a cosolvent and the solute's logarithm of partition coefficients.
Subject(s)
Solvents/chemistry , Algorithms , Chemical Phenomena , Chemistry, Pharmaceutical , Chemistry, Physical , Temperature , Terminology as TopicABSTRACT
Deviations of the predicted solubilities using the Jouyban-Acree model from experimental data were correlated to the structural descritptors of the drugs computed by HyperChem software. The proposed models are able to predict the solubility in water-cosolvent mixtures and reduced the mean percentage deviations (MPD) of predicted solubilities from 24%, 48%, and 53% to 16%, 33% and 38%, respectively for water-propylene glycol, water-ethanol and water-polyethylene glycol 400 mixtures, with the overall improvement in prediction capability of the model being approximately 13%.
