There has been considerable recent interest in employing computer models to investigate the relationship between the structure of a molecule and its dermal penetration. Molecular permeation across the epidermis has previously been demonstrated to be determined by a number of physicochemical properties, for example, the lipophilicity, molecular weight and hydrogen bonding ability of the permeant. However little attention has been paid to modeling the combined effects of permeant properties in tandem with the properties of vehicles used to deliver those permeants or to whether data obtained using synthetic membranes can be correlated with those obtained using human epidermis. This work uses Principal Components Analysis (PCA) to demonstrate that, for studies of the diffusion of three model permeants (caffeine, methyl paraben and butyl paraben) through synthetic membranes, it is the properties of the oily vehicle in which they are applied that dominated the rates of permeation and flux. Simple robust and predictive descriptor-based quantitative structure–permeability relationship (QSPR) models have been developed to support these findings by utilizing physicochemical descriptors of the oily vehicles to quantify the differences in flux and permeation of the model compounds. Interestingly, PCA showed that, for the flux of co-applied model permeants through human epidermis, the permeation of the model permeants was better described by a balance between the physicochemical properties of the vehicle and the permeant rather than being dominated solely by the vehicle properties as in the case of synthetic model membranes. The important influence of permeant solubility in the vehicle along with the solvent uptake on overall permeant diffusion into the membrane was substantiated. These results confirm that care must be taken in interpreting permeation data when synthetic membranes are employed as surrogates for human epidermis; they also demonstrate the importance of considering not only the permeant properties but also those of both vehicle and membrane when arriving at any conclusions relating to permeation data.

中文翻译：

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多元分析方法来识别影响膜渗透的载体、渗透物和膜的关键分子特性


最近人们对利用计算机模型来研究分子结构与其皮肤渗透性之间的关系产生了很大的兴趣。先前已证明分子穿过表皮的渗透是由许多物理化学性质决定的，例如渗透物的亲脂性、分子量和氢键结合能力。然而，很少有人关注对渗透物特性与用于传递这些渗透物的载体特性的综合效应进行建模，或者使用合成膜获得的数据是否可以与使用人类表皮获得的数据相关。这项工作使用主成分分析 (PCA) 来证明，对于三种模型渗透剂（咖啡因、对羟基苯甲酸甲酯和对羟基苯甲酸丁酯）通过合成膜的扩散的研究，它们所应用的油性媒介物的特性起主导作用。渗透率和通量。已经开发出简单稳健且基于预测描述符的定量结构-渗透率关系 (QSPR) 模型，通过利用油性载体的物理化学描述符来量化模型化合物的通量和渗透差异，以支持这些发现。有趣的是，PCA表明，对于共同应用的模型渗透物穿过人体表皮的通量，模型渗透物的渗透可以通过媒介物和渗透物的物理化学性质之间的平衡来更好地描述，而不是仅仅由媒介物性质决定就像合成模型膜的情况一样。证实了渗透物在载体中的溶解度以及溶剂吸收对整个渗透物扩散到膜中的重要影响。 这些结果证实，当使用合成膜作为人类表皮的替代物时，在解释渗透数据时必须小心；他们还证明了在得出与渗透数据相关的任何结论时不仅要考虑渗透特性，还要考虑载体和膜的渗透特性的重要性。