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用于化学吸收建模的平行真皮子隔室。

Parallel dermal subcompartments for modeling chemical absorption.

作者信息

Bookout R L, Quinn D W, McDougal J N

机构信息

Air Force Institute of Technology, Wright-Patterson AFB, OH 45433, USA.

出版信息

SAR QSAR Environ Res. 1997;7(1-4):259-79. doi: 10.1080/10629369708039133.

DOI:10.1080/10629369708039133
PMID:9501509
Abstract

Understanding the absorption of chemicals through the skin is of importance to many fields of study. Biologically-based models can be used to simulate the absorption process and predict the rate of absorption and the amount of the chemical in various parts of the body and skin. When these models consist of physiological and biochemical parameters that can be measured, they can be extremely useful. When a model is appropriately validated, the results can be extrapolated across species to predict the effect of human exposure. In this paper we develop two new physiologically-based pharmacokinetic (PBPK) models which predict the concentration of Dibromomethane in the blood of rats after dermal vapor exposure. These two new models expand a previously developed homogeneous skin model by adding parallel skin subcompartments to represent skin appendages and layered subcompartments to represent the distinct layers of the skin. The predictions of these new models match the experimental data better than the original homogeneous model, as well as being more physiologically descriptive. Sensitivity analysis showed us which parameters were the most sensitive to change and thus revealing the parameters we should be most concerned with measuring. After being properly validated, these models could be a great improvement over previous models in the ability to extrapolate results for different species, doses, and durations.

摘要

了解化学物质通过皮肤的吸收对许多研究领域都很重要。基于生物学的模型可用于模拟吸收过程,并预测吸收速率以及化学物质在身体和皮肤各部位的含量。当这些模型由可测量的生理和生化参数组成时,它们会非常有用。当模型经过适当验证后,其结果可以跨物种外推,以预测人体暴露的影响。在本文中,我们开发了两个新的基于生理的药代动力学(PBPK)模型,用于预测大鼠经皮蒸汽暴露后血液中二溴甲烷的浓度。这两个新模型通过添加平行的皮肤子隔室来代表皮肤附属器,并添加分层子隔室来代表皮肤的不同层,从而扩展了先前开发的均质皮肤模型。这些新模型的预测比原始均质模型更符合实验数据,并且在生理描述上更详细。敏感性分析向我们展示了哪些参数对变化最敏感,从而揭示了我们最应关注测量的参数。经过适当验证后,这些模型在针对不同物种、剂量和暴露时间外推结果的能力方面,可能会比以前的模型有很大改进。

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