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Journal of Solution Chemistry

, Volume 46, Issue 7, pp 1349–1363 | Cite as

Solvent Solubility Testing of Cosmetics-Relevant Chemicals: Methodology and Correlation of Water Solubility to In Silico Predictions

  • S. Grégoire
  • R. CubberleyEmail author
  • H. Duplan
  • J. Eilstein
  • D. Lange
  • N. Hewitt
  • C. Jacques-Jamin
  • M. Klaric
  • H. Rothe
  • C. Ellison
  • O. Vaillant
  • A. Schepky
Article
  • 222 Downloads

Abstract

Aqueous solubility is one of the main physicochemical parameters used to assess skin absorption. As solvents have great impact on skin absorption, knowledge of chemical solubility in appropriate solvents is key to correlate in vitro skin penetration with in vivo outcomes. For example, acetone:olive oil, ethanol and dimethyl sulfoxide are all relevant to in vitro and in vivo assays. Solubility information is also needed to identify the optimal solvent for skin penetration assays. Therefore, we have measured the solubilities of 54 chemicals related to cosmetics and the reference controls for skin sensitization and genotoxicity, in five different solvents: water, DMSO, ethanol, acetone:olive oil (4:1), 5% ethanol in 0.1 mol·L−1 phosphate buffered saline. The solubility protocol resulted in highly reproducible values, with greatest variability for poorly soluble chemicals, especially those in 0.1 mol·L−1 PBS, which may be due to the high salt content. There was good agreement between experimental and literature values for water solubility (mean difference < twofold). A better correlation of experimental values with in silico predictions was obtained using ACD/Labs software (mean difference < fourfold, R2 = 0.64) than WSKOW from EpiSuite (mean difference < eightfold, R2 = 0.48). Chemicals with a log10P > 2 generally exhibited a poor solubility in water but a much higher solubility in acetone:olive oil, ethanol and DMSO. These five solvents include pH effects, acceptor and donor hydrogen bonding and non-polar interactions. Thus, the solubility profile across these different solvents would help to characterize the chemicals related to their cutaneous absorption with different vehicles and their toxicity assessment.

Keywords

Solubility Measured Predicted Cosmetic ingredients Solvents Bioavailability 

Abbreviations

EPISuite™

EPI (estimation programs interface) suite™

PBS

Phosphate buffered saline

Notes

Acknowledgements

We would like to thank David Sanders from Unilever Sharnbrook, UK for all his help, including the analysis of the purity of the chemicals Unilever gifted to the project. David was also integral to the purification of some chemicals and shipment to the participating labs. We would also like to thank Unilever Sharnbrook, UK for the generous donation of seven of the radiolabelled chemicals. Finally, we would like to thank Julien Fernandez from Eurofins I ADME Bioanalysis, France, for all his help with the analytical data collation.

Funding

This work was sponsored by Cosmetics Europe.

Supplementary material

10953_2017_652_MOESM1_ESM.docx (23 kb)
Supplementary material 1 (DOCX 23 kb)

References

  1. 1.
    Jacques, C., Perdu, E., Jamin, E.L., Cravedi, J.P., Mavon, A., Duplan, H., Zalko, D.: Effect of skin metabolism on dermal delivery of testosterone: qualitative assessment using a new short-term skin model. Skin Pharmacol. Physiol. 27, 188–200 (2014)CrossRefGoogle Scholar
  2. 2.
    Gerstel, D., Jacques-Jamin, C., Schepky, A., Cubberley, R., Eilstein, J., Grégoire, S., Hewitt, N., Klaric, M., Rothe, H., Duplan, H.: Comparison of protocols for measuring cosmetic ingredient distribution in human and pig skin. Toxicol. In Vitro 34, 153–160 (2017)CrossRefGoogle Scholar
  3. 3.
    Rothe, H., Obringer, C., Manwaring, J., Avci, C., Wargniez, W., Eilstein, J., Hewitt, N., Cubberley, R., Duplan, H., Lange, D., Jacques-Jamin, C., Klaric, M., Schepky, A., Grégoire, S.: Comparison of protocols measuring diffusion and partition coefficients in the stratum corneum. J. Appl. Toxicol. (2017). doi: 10.1002/jat.3427 Google Scholar
  4. 4.
    http://www.cir-safety.org/. Accessed 25 Jun 2017
  5. 5.
    Dancik, Y., Miller, M.A., Jaworska, J., Kasting, G.B.: Design and performance of a spreadsheet-based model for estimating bioavailability of chemicals from dermal exposure. Adv. Drug Deliv. Rev. 65, 221–236 (2013)CrossRefGoogle Scholar
  6. 6.
    Selzer, D., Hahn, T., Naegel, A., Heisig, M., Kostka, K.H., Lehr, C.M., Neumann, D., Schaefer, U.F., Wittum, G.: Finite dose skin mass balance including the lateral part: comparison between experiment, pharmacokinetic modeling and diffusion models. J. Control. Release 165, 119–128 (2013)CrossRefGoogle Scholar
  7. 7.
    OECD: Test No. 105: Water Solubility, OECD Guidelines for the Testing of Chemicals, Section 1. OECD Publishing, Paris (1995). doi: 10.1787/9789264069589-en CrossRefGoogle Scholar
  8. 8.
    Bansal, S., DeStefano, A.: Key elements of bioanalytical method validation for small molecules. AAPS J. 9, E109–E114 (2007)CrossRefGoogle Scholar
  9. 9.
    ACD/Labs, Percepta Predictors—Aqueous Solubility, Version 12, Advanced Chemistry Development, Inc., Toronto. www.acdlabs.com (2014)
  10. 10.
    www.chemspider.com. Accessed 25 Jun 2017
  11. 11.
    www.chemicalbook.com. Accessed 25 Jun 2017
  12. 12.
    https://pubchem.ncbi.nlm.nih.gov/. Accessed 25 Jun 2017
  13. 13.
  14. 14.
    Palmer, D.S., Mitchell, J.B.: Is experimental data quality the limiting factor in predicting the aqueous solubility of druglike molecules? Mol. Pharm. 11, 2962–2972 (2014)CrossRefGoogle Scholar
  15. 15.
    Dearden, D., Worth, A.: In Silico Prediction of Physicochemical Properties. JRC Scientific and Technical Report. EUR 23051 EN—2007 (2007)Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  • S. Grégoire
    • 1
  • R. Cubberley
    • 2
    Email author
  • H. Duplan
    • 3
  • J. Eilstein
    • 1
  • D. Lange
    • 4
  • N. Hewitt
    • 5
  • C. Jacques-Jamin
    • 3
  • M. Klaric
    • 5
  • H. Rothe
    • 6
  • C. Ellison
    • 7
  • O. Vaillant
    • 8
  • A. Schepky
    • 4
  1. 1.L’Oreal Research and InnovationAulnay-Sous-BoisFrance
  2. 2.UnileverBedfordUK
  3. 3.Pierre Fabre Dermo-CosmétiqueToulouseFrance
  4. 4.Beiersdorf AGHamburgGermany
  5. 5.Cosmetics EuropeBrusselsBelgium
  6. 6.Procter and Gamble (Currently Coty)DarmstadtGermany
  7. 7.The Procter and Gamble CompanyCincinnatiUSA
  8. 8.Eurofins I ADME BioanalysisVergezeFrance

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