Comments on prediction of the aqueous solubility using the general solubility equation (GSE) versus a genetic algorithm and a support vector machine model.

Journal: Pharmaceutical development and technology
Published Date:

Abstract

The general solubility equation (GSE) is the state-of-the-art method for estimating the aqueous solubilities of organic compounds. It is an extremely simple equation that expresses aqueous solubility as a function of only two inputs: the octanol-water partition coefficient calculated by readily available softwares like clogP and ACD/logP, and the commonly known melting point of the solute. Recently, Bahadori et al. proposed that their genetic algorithm support vector machine is a "better" predictor. This paper compares the use of the of Bahadori et al. model for the prediction of aqueous solubility to the existing GSE model.

Authors

  • Doaa Alantary
    a Department of Pharmaceutics, College of Pharmacy , University of Arizona , Tucson , AZ , USA.
  • Samuel Yalkowsky
    a Department of Pharmaceutics, College of Pharmacy , University of Arizona , Tucson , AZ , USA.