4.5 Article

Solubility Prediction of Drugs in Mixed Solvents Using Partial Solubility Parameters

期刊

JOURNAL OF PHARMACEUTICAL SCIENCES
卷 100, 期 10, 页码 4368-4382

出版社

ELSEVIER SCIENCE INC
DOI: 10.1002/jps.22589

关键词

solubility; Jouyban-Acree model; prediction; physicochemical properties; mathematical modelling; QSPR; in silico modelling

资金

  1. Drug Applied Research Center, Tabriz University of Medical Sciences [88-122]

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Solubility of drugs in binary and ternary solvent mixtures composed of water and pharmaceutical cosolvents at different temperatures were predicted using the Jouyban-Acree model and a combination of partial solubility parameters as interaction descriptors in the solution. The generally trained version of the model produced the overall mean percentage deviation values for the back-calculated solubility of drugs in binary solvents of 34.3% and the predicted solubilities in ternary solvent mixtures of 38.0%. In addition, the applicability of the trained model for predicting the solvent composition providing the maximum solubility of a drug was investigated. The results of collected solubility data of drugs in various mixed solvents and the newly measured solubility data of five drugs in ethanol + propylene glycol + water mixtures at 25 degrees C showed that the model provided acceptable predictions and could be used in the pharmaceutical industry. (C) 2011 Wiley-Liss, Inc. and the American Pharmacists Association J Pharm Sci 100:4368-4382, 2011

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