A predictive model for the solubility and octanol-water partition coefficient of pharmaceuticals

Chieh Ming Hsieh, Shu Wang, Shiang Tai Lin, Stanley I. Sandler

Research output: Contribution to journalArticlepeer-review

36 Scopus citations

Abstract

The prediction of drug solubility in various pure and mixed solvents and the octanol-water partition coefficient (KOW) are evaluated using the recently revised conductor-like screening segment activity coefficient (COSMO-SAC) model. The solubility data of 51 drug compounds in 37 different solvents and their combinations over a temperature range of 273.15 K to 323.15 K (300 systems, 2918 data points) are calculated from the COSMO-SAC model and compared to experiments. The solubility data cover a wide range of solubility from (10-1 to 10-6) in mole fraction. When only the heat of fusion and the normal melting temperature of the drug are used, the average absolute error from the revised model is found to be 236 %, a significant reduction from that (388 %) of the original COSMO-SAC model. When the pure drug properties (heat of fusion and melting temperature) are not available, predictions can still be made with a similar accuracy using the solubility data of the drug in any other solvent or solvent mixture. The accuracy in prediction of the solubility in a mixed solvent can be greatly improved (average error of 70 %), if the measured solubility data in one pure solvent is used. Also, the standard deviation in log KOW of 89 drugs, whose values range from -3.7 to 5.25, is found to be 1.14 from the revised COSMO-SAC model. Our results show that the COSMO-SAC model can provide reliable predictions of properties of pharmaceuticals and is a useful tool for drug discovery.

Original languageEnglish
Pages (from-to)936-945
Number of pages10
JournalJournal of Chemical and Engineering Data
Volume56
Issue number4
DOIs
StatePublished - 14 Apr 2011

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