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从复杂化学混合物中预测皮肤渗透性:定量结构渗透关系对所使用的皮肤模型生物学的依赖性。

Predicting skin permeability from complex chemical mixtures: dependency of quantitative structure permeation relationships on biology of skin model used.

机构信息

Center for Chemical Toxicology Research and Pharmacokinetics, North Carolina State University, Raleigh, North Carolina 27606, USA.

出版信息

Toxicol Sci. 2011 Jan;119(1):224-32. doi: 10.1093/toxsci/kfq317. Epub 2010 Oct 14.

Abstract

Dermal absorption of topically applied chemicals usually occurs from complex chemical mixtures; yet, most attempts to quantitate dermal permeability use data collected from single chemical exposure in aqueous solutions. The focus of this research was to develop quantitative structure permeation relationships (QSPR) for predicting chemical absorption from mixtures through skin using two levels of in vitro porcine skin biological systems. A total of 16 diverse chemicals were applied in 384 treatment mixture combinations in flow-through diffusion cells and 20 chemicals in 119 treatment combinations in isolated perfused porcine skin. Penetrating chemical flux into perfusate from diffusion cells was analyzed to estimate a normalized dermal absorptive flux, operationally an apparent permeability coefficient, and total perfusate area under the curve from perfused skin studies. These data were then fit to a modified dermal QSPR model of Abraham and Martin including a sixth term to account for mixture interactions based on physical chemical properties of the mixture components. Goodness of fit was assessed using correlation coefficients (r²), internal and external validation metrics (q²L00, q²L25%, q²EXT), and applicable chemical domain determinations. The best QSPR equations selected for each experimental biological system had r² values of 0.69-0.73, improving fits over the base equation without the mixture effects. Different mixture factors were needed for each model system. Significantly, the model of Abraham and Martin could also be reduced to four terms in each system; however, different terms could be deleted for each of the two biological systems. These findings suggest that a QSPR model for estimating percutaneous absorption as a function of chemical mixture composition is possible and that the nature of the QSPR model selected is dependent upon the biological level of the in vitro test system used, both findings having significant implications when dermal absorption data are used for in vivo risk assessments.

摘要

皮肤对局部应用化学物质的吸收通常来自复杂的化学混合物;然而,大多数定量评估皮肤渗透性的尝试都是使用在水溶液中单一化学物质暴露的数据。本研究的重点是开发定量结构渗透关系(QSPR),以使用两种体外猪皮生物系统预测混合物通过皮肤的化学吸收。总共将 16 种不同的化学物质应用于 384 种处理混合物组合的流通扩散细胞中,将 20 种化学物质应用于 119 种处理混合物组合的离体灌注猪皮中。从扩散细胞渗透到灌流液中的穿透化学物质通量用于分析归一化皮肤吸收通量,操作上是表观渗透系数,以及从灌注皮肤研究中获得的总灌流液曲线下面积。然后,这些数据拟合到包括基于混合物成分物理化学性质的第六项混合物相互作用的改良 Abraham 和 Martin 皮肤 QSPR 模型中。使用相关系数(r²)、内部和外部验证指标(q²L00、q²L25%、q²EXT)以及适用的化学域确定来评估拟合优度。为每个实验生物系统选择的最佳 QSPR 方程的 r²值为 0.69-0.73,与没有混合物效应的基础方程相比,拟合度有所提高。每个模型系统都需要不同的混合物因素。重要的是,Abraham 和 Martin 的模型也可以在每个系统中简化为四个术语;然而,对于这两个生物系统中的每一个,都可以删除不同的术语。这些发现表明,作为化学混合物成分函数估计经皮吸收的 QSPR 模型是可能的,并且选择的 QSPR 模型的性质取决于用于体外测试系统的生物学水平,当使用皮肤吸收数据进行体内风险评估时,这两个发现都具有重要意义。

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