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Prediction of Surfactant Mildness for Rinse-off Formulations Using Preclinical Assays

McCardy, Nicole R
http://orcid.org/0000-0002-6841-5945
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1468512440

Abstract Details

2016, MS, University of Cincinnati, Pharmacy: Pharmaceutical Sciences.
Mixed surfactant and surfactant–polymer compositions have been reported to decrease surfactant deposition onto and into the skin relative to single surfactant compositions, potentially improving the mildness of the product. Previous workers in this area (see Moore et al., J Cosmet Sci 54:29–46 (2003) and subsequent publications), employed a procedure in which excised porcine skin was exposed to a surfactant solution containing radiolabeled sodium dodecyl sulfate ((14)C–SDS) for 5 hours. We have developed an improved (14)C–SDS deposition assay using excised human skin that reflects typical consumer exposure times for rinse–off products. Using the new protocol, we were able to see a significant decrease in (14)C–SDS deposition from an SDS⁄PEG 8000 composition applied to excised skin for either 2 minutes or 10 minutes, as compared with SDS only. Following this, a study was designed to determine whether data from a carefully designed array of preclinical assays could effectively predict the harshness of mixed surfactant and surfactant–polymer compositions on human skin, as measured by corneometry and visual dryness scores in a five–day forearm controlled application test (FCAT). The test compositions included surfactants commonly used in rinse–off applications including shampoos and shower gels. A total of seventeen compositions were tested. The preclinical methods included the recently–developed surfactant deposition assay, zein solubilization, stearic acid solubilization, micelle size, and critical micelle concentration (CMC). The changes–from–baseline (CFB) of the two primary clinical measures, corneometer reading and expert–assessed visual dryness score, were analyzed in terms of the preclinical assay results according to linear regression for bivariate analyses and partial least squares (PLS) for multivariate analyses. Cross–validation was performed within PLS via a leave–one–out algorithm in order to prevent overfitting of the clinical data. FCAT test results correlated significantly with surfactant deposition (corneometer: r2 = 0.631, visual dryness: r2 = 0.498), micelle size (corneometer: r 2 = 0.551, visual dryness: r 2 = 0.445) and zein solubilization (corneometer: r 2 = 0.480, visual dryness: r 2 = 0.145). A one–component PLS model using normalized and scaled data from three of the five preclinical assays — surfactant deposition, micelle size and zein solubilization — yielded the strongest correlations (corneometer: r 2 = 0.889, visual dryness: r 2 = 0.861). Milder formulations were associated with lower surfactant deposition, larger micelle size, and lower zein solubilization. The study results show that, within the composition range tested, preclinical assay data can be strongly correlated to clinical measures of skin dryness. The results support the hypothesis that micellar structure is more important to surfactant mildness than is CMC, with larger micelles leading to milder formulations.
Gerald Kasting, Ph.D. (Committee Chair)
Harshita Kumari, Ph.D. (Committee Member)
Ryan Thompson, B.S. (Committee Member)
63 p.
Pharmaceuticals
colloid science; surface chemistry; stratum corneum; skin science; surfactant mildness; multivariate statistical analysis

Recommended Citations

Citations

  • McCardy, N. R. (2016). Prediction of Surfactant Mildness for Rinse-off Formulations Using Preclinical Assays [Master's thesis, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1468512440

    APA Style (7th edition)

  • McCardy, Nicole. Prediction of Surfactant Mildness for Rinse-off Formulations Using Preclinical Assays. 2016. University of Cincinnati, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1468512440.

    MLA Style (8th edition)

  • McCardy, Nicole. "Prediction of Surfactant Mildness for Rinse-off Formulations Using Preclinical Assays." Master's thesis, University of Cincinnati, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1468512440

    Chicago Manual of Style (17th edition)

ucin1468512440
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© 2016, some rights reserved.Creative Commons License Prediction of Surfactant Mildness for Rinse-off Formulations Using Preclinical Assays by Nicole R McCardy is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. Based on a work at etd.ohiolink.edu.
This open access ETD is published by University of Cincinnati and OhioLINK.