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Predicting skin permeability from complex chemical mixtures: incorporation of an expanded QSAR model.

Authors
Xu-G; Hughes-Oliver-JM; Brooks-JD; Baynes-RE
Source
SAR QSAR Environ Res 2013 Sep; 24(9):711-731
NIOSHTIC No.
20043958
Abstract
Quantitative structure-activity relationship (QSAR) models have been widely used to study the permeability of chemicals or solutes through skin. Among the various QSAR models, Abraham's linear free-energy relationship (LFER) model is often employed. However, when the experimental conditions are complex, it is not always appropriate to use Abraham's LFER model with a single set of regression coefficients. In this paper, we propose an expanded model in which one set of partial slopes is defined for each experimental condition, where conditions are defined according to solvent: water, synthetic oil, semi-synthetic oil, or soluble oil. This model not only accounts for experimental conditions but also improves the ability to conduct rigorous hypothesis testing. To more adequately evaluate the predictive power of the QSAR model, we modified the usual leave-one-out internal validation strategy to employ a leave-one-solute-out strategy and accordingly adjust the Q(2) LOO statistic. Skin permeability was shown to have the rank order: water > synthetic > semi-synthetic > soluble oil. In addition, fitted relationships between permeability and solute characteristics differ according to solvents. We demonstrated that the expanded model (r(2) = 0.70) improved both the model fit and the predictive power when compared with the simple model (r(2) = 0.21).
Keywords
Quantitative-analysis; Chemical-analysis; Analytical-models; Models; Skin; Skin-absorption; Solvents; Chemical-structure; Chemical-properties; Chemical-reactions; Pharmacodynamics; Chemical-kinetics; Analytical-processes; Analytical-chemistry; Molecular-structure; Mathematical-models; Synthetics; Synthetic-materials; Oils; Laboratory-testing; Author Keywords: Abraham's LFER model; adjusted Q2 LOO; expanded LFER model; leave-one-solute-out; QSAR
Contact
R.E. Baynes, Center for Chemical Toxicology Research and Pharmacokinetics, North Carolina State University College of Veterinary Medicine, Raleigh, NC 27606, USA
CODEN
SQERED
Publication Date
20130901
Document Type
Journal Article
Email Address
rebaynes@ncsu.edu
Funding Amount
875919
Funding Type
Grant
Fiscal Year
2013
NTIS Accession No.
NTIS Price
Identifying No.
Grant-Number-R01-OH-003669
Issue of Publication
9
ISSN
1062-936X
Priority Area
Disease and Injury: Allergic and Irritant Dermatitis
Source Name
SAR and QSAR in Environmental Research
State
NC; VA
Performing Organization
North Carolina State University, Raleigh, North Carolina
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