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Predicting Skin Permeability from Complex Chemical Mixtures: Dependency of Quantitative Structure Permeation Relationships on Biology of Skin Model Used

机译:从复杂的化学混合物预测皮肤渗透性:定量结构渗透关系对所用皮肤模型生物学的依赖性

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摘要

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 (qLOO2, qL25%2, qEXT2), 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.
机译:局部应用化学品的皮肤吸收通常来自复杂的化学混合物。但是,大多数量化皮肤渗透性的尝试都使用从水溶液中单次化学暴露收集的数据。这项研究的重点是开发定量结构渗透关系(QSPR),以使用两种水平的体外猪皮肤生物学系统预测混合物从皮肤吸收的化学物质。在流通的扩散池中,将384种治疗混合物中的16种不同化学物质分别应用到分离的灌注猪皮肤中的119种治疗混合物中的20种化学物质中。分析了从扩散池渗透到灌注液中的化学通量,以估计来自灌注皮肤研究的曲线下的归一化真皮吸收通量,表观渗透系数和总灌注液面积。然后,将这些数据拟合到亚伯拉罕和马丁的经过修改的皮肤QSPR模型,其中包括第六个术语,以根据混合物成分的物理化学性质解释混合物之间的相互作用。使用相关系数(r 2 ),内部和外部验证指标( q LOO 2 q L25% 2 q EXT 2 )和适用的化学域确定。为每个实验生物系统选择​​的最佳QSPR方程的r 2 值为0.69–0.73,在没有混合效应的情况下提高了基本方程的拟合度。每个模型系统都需要不同的混合因子。值得注意的是,每个系统中亚伯拉罕和马丁的模型也可以简化为四个项。但是,可以为两个生物系统中的每一个删除不同的术语。这些发现表明,用于估计经皮吸收与化学混合物组成的函数关系的QSPR模型是可能的,并且所选择的QSPR模型的性质取决于所用体外测试系统的生物学水平,这两种发现在皮肤上均具有重要意义。吸收数据用于体内风险评估。

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