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Predicting human skin absorption of chemicals: development of a novel quantitative structure activity relationship

Department of Toxicology, L'Oreal USA, Clark NJ, USA, wendyluo{at}alum.mit.edu

Sarah Medrek

Department of Chemical Engineering, Princeton University, Princeton, NJ, USA

Jatin Misra

Department of Chemical Engineering, Massachusetts Institute of Technology, MA, USA

Gerhard J Nohynek

L'Oreal Worldwide Safety Evaluation, Asnieres, France

The objective of this study was to construct and validate a quantitative structure-activity relationship model for skin absorption. Such models are valuable tools for screening and prioritization in safety and efficacy evaluation, and risk assessment of drugs and chemicals. A database of 340 chemicals with percutaneous absorption was assembled. Two models were derived from the training set consisting 306 chemicals (90/10 random split). In addition to the experimental K_ow values, over 300 2D and 3D atomic and molecular descriptors were analyzed using MDL's QsarIS computer program. Subsequently, the models were validated using both internal (leave-one-out) and external validation (test set) procedures. Using the stepwise regression analysis, three molecular descriptors were determined to have significant statistical correlation with K_p (R² = 0.8225): logK_ow, x0 (quantification of both molecular size and the degree of skeletal branching), and SsssCH (count of aromatic carbon groups). In conclusion, two models to estimate skin absorption were developed. When compared to other skin absorption QSAR models in the literature, our model incorporated more chemicals and explored a large number of descriptors. Additionally, our models are reasonably predictive and have met both internal and external statistical validations. Toxicology and Industrial Health 2007; 23: 39—45.

Key Words: skin permeability • skin absorption • quantitative structure activity relationship • QSAR • statistical validation • lipophilicity • molecular weight

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