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Brown TN, Armitage JM, Egeghy P, Kircanski I, Arnot JA. Dermal permeation data and models for the prioritization and screening-level exposure assessment of organic chemicals. Environ Int 2016; 94:424-435. [PMID: 27282209 DOI: 10.1016/j.envint.2016.05.025] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/14/2016] [Revised: 05/20/2016] [Accepted: 05/24/2016] [Indexed: 05/20/2023]
Abstract
High-throughput screening (HTS) models are being developed and applied to prioritize chemicals for more comprehensive exposure and risk assessment. Dermal pathways are possible exposure routes to humans for thousands of chemicals found in personal care products and the indoor environment. HTS exposure models rely on skin permeability coefficient (KP; cm/h) models for exposure predictions. An initial database of approximately 1000 entries for empirically-based KP data was compiled from the literature and a subset of 480 data points for 245 organic chemicals derived from testing with human skin only and using only water as a vehicle was selected. The selected dataset includes chemicals with log octanol-water partition coefficients (KOW) ranging from -6.8 to 7.6 (median=1.8; 95% of the data range from -2.5 to 4.6) and molecular weight (MW) ranging from 18 to 765g/mol (median=180); only 3% >500g/mol. Approximately 53% of the chemicals in the database have functional groups which are ionizable in the pH range of 6 to 7.4, with 31% being appreciably ionized. The compiled log KP values ranged from -5.8 to 0.1cm/h (median=-2.6). The selected subset of the KP data was then used to evaluate eight representative KP models that can be readily applied for HTS assessments, i.e., parameterized with KOW and MW. The analysis indicates that a version of the SKINPERM model performs the best against the selected dataset. Comparisons of representative KP models against model input parameter property ranges (sensitivity analysis) and against chemical datasets requiring human health assessment were conducted to identify regions of chemical properties that should be tested to address uncertainty in KP models and HTS exposure assessments.
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Affiliation(s)
- Trevor N Brown
- ARC Arnot Research and Consulting Inc., 36 Sproat Avenue, Toronto, ON, Canada, M4M 1W4
| | - James M Armitage
- ARC Arnot Research and Consulting Inc., 36 Sproat Avenue, Toronto, ON, Canada, M4M 1W4; Department of Physical and Environmental Sciences, University of Toronto Scarborough, 1265 Military Trail, Toronto, ON, Canada, M1C 1A4
| | - Peter Egeghy
- U.S. Environmental Protection Agency, Office of Research and Development, National Exposure Research Laboratory, 109 T.W. Alexander Drive, Research Triangle Park, NC 27709, USA
| | - Ida Kircanski
- ARC Arnot Research and Consulting Inc., 36 Sproat Avenue, Toronto, ON, Canada, M4M 1W4; Department of Pharmacology and Toxicology, University of Toronto, 1 King's College Circle, Toronto, ON, Canada, M5S 1A8
| | - Jon A Arnot
- ARC Arnot Research and Consulting Inc., 36 Sproat Avenue, Toronto, ON, Canada, M4M 1W4; Department of Physical and Environmental Sciences, University of Toronto Scarborough, 1265 Military Trail, Toronto, ON, Canada, M1C 1A4; Department of Pharmacology and Toxicology, University of Toronto, 1 King's College Circle, Toronto, ON, Canada, M5S 1A8.
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