Medway School of Pharmacy, Universities of Kent and Greenwich, Chatham, Kent ME4 4TB, UK.
Int J Pharm. 2010 Oct 15;398(1-2):28-32. doi: 10.1016/j.ijpharm.2010.07.014. Epub 2010 Jul 17.
A vehicle influences the concentration of penetrant within the membrane, affecting its diffusivity in the skin and rate of transport. Despite the huge amount of effort made for the understanding and modelling of the skin absorption of chemicals, a reliable estimation of the skin penetration potential from formulations remains a challenging objective. In this investigation, quantitative structure-activity relationship (QSAR) was employed to relate the skin permeation of compounds to the chemical properties of the mixture ingredients and the molecular structures of the penetrants. The skin permeability dataset consisted of permeability coefficients of 12 different penetrants each blended in 24 different solvent mixtures measured from finite-dose diffusion cell studies using porcine skin. Stepwise regression analysis resulted in a QSAR employing two penetrant descriptors and one solvent property. The penetrant descriptors were octanol/water partition coefficient, logP and the ninth order path molecular connectivity index, and the solvent property was the difference between boiling and melting points. The negative relationship between skin permeability coefficient and logP was attributed to the fact that most of the drugs in this particular dataset are extremely lipophilic in comparison with the compounds in the common skin permeability datasets used in QSAR. The findings show that compounds formulated in vehicles with small boiling and melting point gaps will be expected to have higher permeation through skin. The QSAR was validated internally, using a leave-many-out procedure, giving a mean absolute error of 0.396. The chemical space of the dataset was compared with that of the known skin permeability datasets and gaps were identified for future skin permeability measurements.
载体影响着膜内渗透物的浓度，从而影响其在皮肤中的扩散率和传输速度。尽管人们在理解和模拟化学物质的皮肤吸收方面付出了巨大的努力，但从制剂中可靠地估计皮肤渗透潜力仍然是一个具有挑战性的目标。在这项研究中，定量构效关系（QSAR）被用于将化合物的皮肤渗透与混合物成分的化学性质和渗透物的分子结构联系起来。皮肤渗透性数据集由 12 种不同渗透物的渗透系数组成，每种渗透物分别与 24 种不同溶剂混合物混合，使用猪皮从有限剂量扩散池研究中测量。逐步回归分析得出了一个 QSAR，其中包含两个渗透物描述符和一个溶剂性质。渗透物描述符是辛醇/水分配系数、logP 和第九阶路径分子连接性指数，而溶剂性质是沸点和熔点之间的差异。皮肤渗透系数与 logP 之间的负相关关系归因于这样一个事实，即在这个特定数据集的大多数药物与 QSAR 中常用的皮肤渗透性数据集的化合物相比，其脂溶性极强。研究结果表明，在沸点和熔点差异较小的载体中配制的化合物预计将具有更高的皮肤渗透性。QSAR 通过使用留一法进行了内部验证，得到的平均绝对误差为 0.396。数据集的化学空间与已知皮肤渗透性数据集的化学空间进行了比较，并确定了未来皮肤渗透性测量的差距。
