Solubility Prediction for Furosemide in Water-Cosolvent Mixtures Using the Minimum Number of Experiments

Abstract

The mole fraction solubility of a poorly water soluble loop diuretic, furosemide, was determined in aqueous binary mixtures of ethanol, propylene glycol, and glycerol from 0% to 100% cosolvent concentrations at 25 degrees C. Solubility predictions based on the minimum number of experimental data points were performed using the commonly used accurate cosolvency models: the three-suffix excess free energy (3xEFE), the mixture response surface (MRS), the combined nearly ideal binary solvent/Redlich-Kister (CNIBS/R-K), and the general single model (GSM). This prediction method was tested using three sets of solubility data for furosemide generated in this study and 11 data sets collected from the literature. The average percentage deviations (APDs) were 8.4 +/- 3.8, 13.6 +/- 7.3, 7.4 +/- 2.8, and 7.6 +/- 2.9, respectively, for 3xEFE, MRS, CNIBS/R-K, and GSM models. Using 3xEFE, CNIBS/R-K, and GSM models, which are theoretically related, a mean predicted solubility (MPS) approach was also proposed. The APD for this method was 7.3 +/- 2.3. The mean differences between MRS and the others were statistically significant (p < .001). The results showed that one can employ solubility prediction based on a minimum of five experimental data points, and the expected APD is less than 10%.