Department of Engineering, Harvey Mudd College, Claremont, California 91711.
Department of Engineering, Harvey Mudd College, Claremont, California 91711.
J Pharm Sci. 2018 Feb;107(2):612-623. doi: 10.1016/j.xphs.2017.09.015. Epub 2017 Oct 6.
While predictive models of transdermal transport have the potential to reduce human and animal testing, microscopic stratum corneum (SC) model output is highly dependent on idealized SC geometry, transport pathway (transcellular vs. intercellular), and penetrant transport parameters (e.g., compound diffusivity in lipids). Most microscopic models are limited to a simple rectangular brick-and-mortar SC geometry and do not account for variability across delivery sites, hydration levels, and populations. In addition, these models rely on transport parameters obtained from pure theory, parameter fitting to match in vivo experiments, and time-intensive diffusion experiments for each compound. In this work, we develop a microscopic finite element model that allows us to probe model sensitivity to variations in geometry, transport pathway, and hydration level. Given the dearth of experimentally-validated transport data and the wide range in theoretically-predicted transport parameters, we examine the model's response to a variety of transport parameters reported in the literature. Results show that model predictions are strongly dependent on all aforementioned variations, resulting in order-of-magnitude differences in lag times and permeabilities for distinct structure, hydration, and parameter combinations. This work demonstrates that universally predictive models cannot fully succeed without employing experimentally verified transport parameters and individualized SC structures.
虽然透皮传输预测模型具有减少人体和动物测试的潜力,但微观角质层 (SC) 模型的输出高度依赖于理想化的 SC 几何形状、传输途径(细胞内与细胞间)以及渗透物传输参数(例如,脂质中的化合物扩散系数)。大多数微观模型仅限于简单的矩形砖--mortar SC 几何形状,并且不考虑不同给药部位、水合水平和人群的可变性。此外,这些模型依赖于从纯理论中获得的传输参数、参数拟合以匹配体内实验以及针对每种化合物进行耗时的扩散实验。在这项工作中,我们开发了一种微观有限元模型,使我们能够探究模型对几何形状、传输途径和水合水平变化的敏感性。鉴于缺乏经过实验验证的传输数据以及理论预测传输参数的广泛范围,我们检查了模型对文献中报道的各种传输参数的响应。结果表明,模型预测强烈依赖于所有上述变化,导致不同结构、水合和参数组合的滞后时间和渗透率存在数量级差异。这项工作表明,没有使用经过实验验证的传输参数和个体化 SC 结构,普遍可预测的模型不可能完全成功。