Pharmaceutical Research

, Volume 21, Issue 2, pp 237–244 | Cite as

A Quantitative Structure-Property Relationship for Predicting Drug Solubility in PEG 400/Water Cosolvent Systems

  • Erik Rytting
  • Kimberley A. Lentz
  • Xue-Qing Chen
  • Feng Qian
  • Srini Venkatesh
Article

Abstract

Purpose. A quantitative structure-property relationship (QSPR) was developed to predict drug solubility in binary mixtures of polyethylene glycol (PEG) 400 and water. The ability of the QSPR model to predict solubility was assessed and compared to the classic log-linear cosolvency model.

Methods. The solubility of 122 drugs, ranging in log P from -2.4 to 7.5, was determined in 0%, 25%, 50%, and 75% PEG (v/v in water) by the shake-flask method. Solubility data from 84 drugs were fit by linear regression using the following molecular descriptors: molecular weight, volume, radius of gyration, density, number of rotatable bonds, hydrogen-bond donors, and hydrogen-bond acceptors. The multiple linear regression model was optimized by a genetic algorithm guided selection method. The remaining 38 compounds were used to test the predictability of the model.

Results. QSPR-based models developed at each volume fraction with the training set compounds showed a reasonable correlation coefficient (r) of ∼0.9 and a root mean square (rms) error of <0.5 log unit. The model predicted solubility values of ∼78% of the testing set compounds within 1 log unit. The log-linear model was as effective as the QSPR-based model in predicting the testing set solubilities; however, many drugs, as expected, showed significant deviation from log-linearity.

Conclusions. The QSPR model requires only the chemical structure of the drug and has utility for guiding vehicle identification for early preclinical in vivo studies, especially when compound availability is limited and experimental data such as aqueous solubility and melting point are unknown. When experimental data are available, the log-linear model was verified to be a useful predictive tool.

cosolvent in silico PEG 400 prediction QSPR model solubility 

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references

  1. 1.
    S. Venkatesh and R. A. Lipper. Role of the development scientist in compound lead selection and optimization. J. Pharm. Sci. 89:145-154 (2000).Google Scholar
  2. 2.
    S. Sweetana and M. J. Akers. Solubility principles and practices for parenteral drug dosage form development. PDA J. Pharm. Sci. Technol. 50:330-342 (1996).Google Scholar
  3. 3.
    S. H. Yalkowsky. Solubilization by cosolvents. In S. H. Yalkowsky (ed.), Solubility and Solubilization in Aqueous Media, Oxford University Press, New York, 1999 pp. 180-235.Google Scholar
  4. 4.
    Final Report on the Safety Assessment of Polyethylene Glycols. (PEGs)-6,-8,-32,-75,-150,-14M,-20M. J. Am. Coll. Toxicol. 12:429-457 (1993).Google Scholar
  5. 5.
    A. Jouyban-Gharamaleki, L. Valaee, M. Barzegar-Jalali, B. J. Clark, and W. E. Acree, Jr. Comparison of various cosolvency models for calculating solute solubility in water-cosolvent mixtures. Int. J. Pharm. 177:93-101 (1999).Google Scholar
  6. 6.
    N. A. Williams and G. L. Amidon. Excess free energy approach to the estimation of solubility in mixed solvent systems I: theory. J. Pharm. Sci. 73:9-13 (1984).Google Scholar
  7. 7.
    A. Martin, A. N. Paruta, and A. Adjei. Extended Hildebrand solubility approach: methylxanthines in mixed solvents. J. Pharm. Sci. 70:1115-1120 (1981).Google Scholar
  8. 8.
    S. H. Yalkowsky, G. L. Flynn, and G. L. Amidon. Solubility of nonelectrolytes in polar solvents. J. Pharm. Sci. 61:983-984 (1972).Google Scholar
  9. 9.
    A. Li and S. H. Yalkowsky. Predicting cosolvency. 1. Solubility ratio and solute logKow. Ind. Eng. Chem. Res. 37:4470-4475 (1998).Google Scholar
  10. 10.
    S. H. Yalkowsky and T. J. Roseman. Solubilization of drugs by cosolvents. In S. H. Yalkowsky (ed.), Techniques of Solubilization of Drugs., Marcel Dekker, New York, 1981, pp. 91-134.Google Scholar
  11. 11.
    S. H. Yalkowsky, S. C. Valvani, and G. L. Amidon. Solubility of nonelectrolytes in polar solvents IV: nonpolar drugs in mixed solvents. J. Pharm. Sci. 65:1488-1494 (1976).Google Scholar
  12. 12.
    J. W. Millard, F. A. Alvarez-Núñnez, and S. H. Yalkowsky. Solubilization by cosolvents: Establishing useful constants for the log-linear model. Int. J. Pharm. 245:153-166 (2002).Google Scholar
  13. 13.
    X-Q. Chen, S. J. Cho, Y. Li, and S. Venkatesh. Prediction of aqueous solubility of organic compounds using a quantitative structure-property relationship. J. Pharm. Sci. 91:1838-1852 (2002).Google Scholar
  14. 14.
    D. J. W. Grant and T. Higuchi. Solubility, intermolecular forces, and thermodynamics. In Solubility Behavior of Organic Compounds, John Wiley & Sons, New York, 1990, pp. 12-88.Google Scholar
  15. 15.
    S. J. Cho and M. A. Hermsmeier. Genetic algorithm guided selection: variable selection and subset selection. J. Chem. Inf. Comput. Sci. 42:927-936 (2002).Google Scholar
  16. 16.
    T. R. Stouch, J. R. Kenyon, S. R. Johnson, X. Q. Chen, A. Doweyko, and Y. Li. In silico ADME/Tox: why models fail. J. Comput. Aided Mol. Des. 17:83-92 (2003).Google Scholar
  17. 17.
    I. V. Tetko. V. Y Tanchuk, T. N. Kasheva, and A. E. P. Villa. Estimation of aqueous solubility of chemical compounds using E-state indices. J. Chem. Inf. Comput. Sci. 41:1488-1493 (2001).Google Scholar
  18. 18.
    B. E. Mitchell and P. C. Jurs. Prediction of aqueous solubility of organic compounds from molecular structure. J. Chem. Inf. Comput. Sci. 38:489-496 (1998).Google Scholar
  19. 19.
    E. Khalil, S. Najjar, and A. Sallam. Aqueous solubility of diclofenac diethylamine in the presence of pharmaceutical additives: a comparative study with diclofenac sodium. Drug Dev. Ind. Pharm. 26:375-381 (2000).Google Scholar
  20. 20.
    T. A. Hagen and G. L. Flynn. Solubility of hydrocortisone in organic and aqueous media: evidence for regular solution behavior in apolar solvents. J. Pharm. Sci. 72:409-414 (1983).Google Scholar
  21. 21.
    J. T. Rubino and S. H. Yalkowsky. Cosolvency and deviations from log-linear solubilization. Pharm. Res. 4:231-236 (1987).Google Scholar
  22. 22.
    J. T. Rubino and E. K. Obeng. Influence of solute structure on deviations from the log-linear solubility equation in propylene glycol:water mixtures. J. Pharm. Sci. 80:479-483 (1991).Google Scholar
  23. 23.
    R. Tarantino, E. Bishop, F. C. Chen, K. Iqbal, and A. W. Malick. N-methyl-2-pyrrolidone as a cosolvent: relationship of cosolvent effect with solute polarity and the presence of proton-donating groups on model drug compounds. J. Pharm. Sci. 83:1213-1216 (1994).Google Scholar
  24. 24.
    S. K. Burley and G. A. Petsko. Weakly polar interactions in proteins. Adv. Protein Chem. 39:125-189 (1988).Google Scholar

Copyright information

© Plenum Publishing Corporation 2004

Authors and Affiliations

  • Erik Rytting
    • 1
  • Kimberley A. Lentz
    • 1
  • Xue-Qing Chen
    • 2
  • Feng Qian
    • 2
  • Srini Venkatesh
    • 1
  1. 1.Discovery Pharmaceutics, Preclinical Candidate OptimizationBristol-Myers Squibb Pharmaceutical Research InstituteWallingford
  2. 2.Discovery Pharmaceutics, Preclinical Candidate OptimizationBristol-Myers Squibb Pharmaceutical Research InstituteLawrenceville

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