分子通过皮肤深层传输的多尺度模型

IF 3.1 Q2 TOXICOLOGY
Nitu Verma , Kishore Gajula , Rakesh Gupta , Beena Rai
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引用次数: 1

摘要

需要精确的人体皮肤硅模型来获得分子在皮肤层上的摄取/释放,以补充体内/体外实验,从而更快地开发/测试化妆品和药物。我们的目标是通过将先前开发的皮肤表层多尺度建模框架扩展到更深的皮肤层,建立一个硅皮肤渗透模型,并将结果与43种化妆品相关分子在人体皮肤中的体外实验渗透数据进行比较。在这项研究中,我们扩展了一个多尺度的建模框架,用真实的非均质角质层(SC),包括可渗透的脂质和角质层网络,其次是均匀的活表皮和真皮层。脂质层分子的扩散系数采用分子动力学模拟方法确定,其他层的扩散系数和所有分配系数采用文献报道的相关性计算。然后将这些参数用于宏观模型,以预测药物通过更深的皮肤层的释放曲线。所获得的释放曲线与大多数分子的现有实验数据一致。该模型可以深入了解化妆品/药物的皮肤渗透,并作为进行针对性实验的省时高效的指导工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multiscale modeling of molecule transport through skin’s deeper layers

Accurate in-silico models of human skin are required to obtain the uptake/release of molecules across the skin layers to supplement the in-vivo/in-vitro experiments for faster development/testing of cosmetics and drugs. We aim to develop an in-silico skin permeation model by extending the multiscale modeling framework developed earlier for skin’s top layer to deeper layer and compared the outcomes with in-vitro experimental permeation data of 43 cosmetic-relevant molecules across human skin.

In this study, we have extended a multiscale modeling framework, with realistic heterogeneous stratum corneum (SC) comprising of network of permeable lipids and corneocytes, followed by homogeneous viable epidermis and dermis. The diffusion coefficients of molecules in lipid layer were determined using molecular dynamics simulations, whereas the diffusion coefficients in other layers and all the partition coefficients were calculated from correlations reported in literature. These parameters were then used in the macroscopic models to predict the release profiles of drugs through the deeper skin layers. The obtained release profiles were in good agreement with available experimental data for most of the molecules. The reported model could provide insight into cosmetics/drugs skin permeation and act as a time-saving and efficient guiding tool for performing targeted experiments.

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来源期刊
Computational Toxicology
Computational Toxicology Computer Science-Computer Science Applications
CiteScore
5.50
自引率
0.00%
发文量
53
审稿时长
56 days
期刊介绍: Computational Toxicology is an international journal publishing computational approaches that assist in the toxicological evaluation of new and existing chemical substances assisting in their safety assessment. -All effects relating to human health and environmental toxicity and fate -Prediction of toxicity, metabolism, fate and physico-chemical properties -The development of models from read-across, (Q)SARs, PBPK, QIVIVE, Multi-Scale Models -Big Data in toxicology: integration, management, analysis -Implementation of models through AOPs, IATA, TTC -Regulatory acceptance of models: evaluation, verification and validation -From metals, to small organic molecules to nanoparticles -Pharmaceuticals, pesticides, foods, cosmetics, fine chemicals -Bringing together the views of industry, regulators, academia, NGOs
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