Determining Epidermal Disposition Kinetics for Use in an Integrated Nonanimal Approach to Skin Sensitization Risk Assessment

被引:19
|
作者
Davies, Michael [1 ]
Pendlington, Ruth U. [1 ]
Page, Leanne [2 ]
Roper, Clive S. [2 ]
Sanders, David J. [1 ]
Bourner, Clare [1 ]
Pease, Camilla K. [1 ]
MacKay, Cameron [1 ]
机构
[1] Unilever, Safety & Environm Assurance Ctr, Sharnbrook MK44 1LQ, Beds, England
[2] In Vitro Sci, Edinburgh EH33 2NE, Midlothian, Scotland
关键词
skin sensitization; in vitro; skin permeation; in silico; mathematical modeling; area under the curve; IN-VITRO; CONSUMER SAFETY; READ-ACROSS; REACTIVITY; CLASSIFICATION; FEASIBILITY;
D O I
10.1093/toxsci/kfq326
中图分类号
R99 [毒物学(毒理学)];
学科分类号
100405 ;
摘要
Development of risk assessment methods for skin sensitization in the absence of toxicological data generated in animals represents a major scientific and technical challenge. The first step in human skin sensitization induction is the transport of sensitizer from the applied dose on the skin surface to the epidermis, where innate immune activation occurs. Building on the previous development of a time course in vitro human skin permeation assay, new kinetic data for 10 sensitizers and 2 nonsensitizers are reported. Multicompartmental modeling has been applied to analyze the data and determine candidate dose parameters for use in integrated risk assessment methods: the area under the curve (AUC) and maximum concentration (Cm.) in the epidermis. A model with two skin compartments, representing the stratum corneum and viable skin (epidermis and dermis), was chosen following a formal model selection process. Estimates of the uncertainty, as well as average values of the epidermal disposition kinetics parameters, were made by fitting to the time course skin permeation data from individual skin donors. A potential reduced time course method is proposed based on two time points at 4 and 24 h, which gives results close to those from the full time course for the current data sets. The time course data presented in this work have been provided as a resource for development of predictive in silico skin permeation models.
引用
收藏
页码:308 / 318
页数:11
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