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AAPS PharmSciTech

, 20:10 | Cite as

Solubility Prediction of Drugs in Binary Solvent Mixtures at Various Temperatures Using a Minimum Number of Experimental Data Points

  • Sina Dadmand
  • Farzin Kamari
  • William E. AcreeJr.
  • Abolghasem JouybanEmail author
Research Article

Abstract

This study aimed to provide a rational experimental design to collect a minimum number of experimental data points for a drug dissolved in a given binary solvent mixture at various temperatures, and to describe a computational procedure to predict the solubility of the drugs in any solvent composition and temperature of interest. We gathered available solubility data sets from papers published from 2012 to 2016 (56 data sets, 3488 data points totally). The mean percentage deviations (MPD) used to check the accuracy of predictions was calculated by Eq. 10. Fifty-six datasets were analyzed using 8 training data points which the overall MPD was calculated to be 15.5% ± 15.1%, and for 52 datasets after excluding 5 outlier sets was 12.1% ± 8.9%. The paired t test was conducted to compare the MPD values obtained from the models trained by 7 and 8 training data points and the reduction in prediction overall MPD (from 17.7% to 15.5%) was statistically significant (p < 0.04). To further reduction in MPD values, the computations were also conducted using 9 training data points, which did not reveal any significant difference comparing to the predictions using 8 training data points (p > 0.88). This observation revealed that the model adequately trained using 8 data points and could be used as a practical strategy for predicting the solubility of drugs in binary solvent mixtures at various temperatures with acceptable prediction error and using minimum experimental efforts. These sorts of predictions are highly in demand in the pharmaceutical industry.

KEY WORDS

cosolvency Jouyban–Acree model minimum experimental data solubility prediction 

Notes

Acknowledgements

This report is a part of the results of S. Dadmand’s Pharm D thesis submitted to the Faculty of Pharmacy, Tabriz University of Medical Sciences, Tabriz, Iran.

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Copyright information

© American Association of Pharmaceutical Scientists 2018

Authors and Affiliations

  • Sina Dadmand
    • 1
  • Farzin Kamari
    • 2
  • William E. AcreeJr.
    • 3
  • Abolghasem Jouyban
    • 4
    • 5
    Email author
  1. 1.Drug Applied Research CenterTabriz University of Medical SciencesTabrizIran
  2. 2.Neurosciences Research Center (NSRC)Tabriz University of Medical SciencesTabrizIran
  3. 3.Department of ChemistryUniversity of North TexasDentonUSA
  4. 4.Pharmaceutical Analysis Research Center and Faculty of PharmacyTabriz University of Medical SciencesTabrizIran
  5. 5.Kimia Idea Pardaz Azarbayjan (KIPA) Science Based CompanyTabriz University of Medical SciencesTabrizIran

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