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一种新的经皮乙醇动力学建模方法。

A new approach to modeling transdermal ethanol kinetics.

机构信息

Department of Bioengineering, University of Washington, Seattle, Washington, USA.

出版信息

Physiol Rep. 2024 Oct;12(19):e70070. doi: 10.14814/phy2.70070.

Abstract

Measurement of ethanol above the skin surface (supradermal) is used to monitor blood alcohol concentrations (BAC) in both legal and consumer settings. Previously, the relationship between supradermal alcohol concentration (SAC) and BAC was described using partial and ordinary differential equations (PDE model: J. Appl. Physiol. 100: 649-55, 2006). Using a range of BAC profiles by varying absorption times and peak concentrations, the PDE model accurately predicted experimental measures of SAC. Recently, other mathematical models have relied on the PDE model. This paper proposes a new approach to modeling transdermal ethanol kinetics using a mass transfer coefficient and only ordinary differential equations (ODE model). Using a range of BAC profiles, the ODE model performed very similarly to the PDE model. The ODE model had slightly slower washout rates and slightly slower times to peak SAC and to zero SAC. Similar to the PDE model, a sensitivity analysis on the ODE model showed changes in solubility and diffusivity within the stratum corneum, stratum corneum thickness, and the volume of gas above the skin affected model performance. This new model will streamline integration into larger physiologic models, reduce computation time, and decrease the time to transform skin alcohol measurements to blood alcohol concentrations.

摘要

测量皮肤表面以上的乙醇(超皮)用于在法律和消费者环境中监测血液酒精浓度(BAC)。以前,使用偏微分方程(PDE 模型:J. Appl. Physiol. 100:649-55,2006)和常微分方程(ODE 模型)来描述超皮酒精浓度(SAC)与 BAC 之间的关系。通过改变吸收时间和峰值浓度来使用一系列 BAC 分布,PDE 模型准确地预测了 SAC 的实验测量值。最近,其他数学模型依赖于 PDE 模型。本文提出了一种使用质量转移系数和仅常微分方程(ODE 模型)来建模经皮乙醇动力学的新方法。使用一系列 BAC 分布,ODE 模型的性能与 PDE 模型非常相似。ODE 模型的洗脱率略慢,达到 SAC 峰值和达到 SAC 零的时间略长。与 PDE 模型一样,对 ODE 模型的敏感性分析表明,角质层、角质层厚度和皮肤上方气体体积中的溶解度和扩散率的变化会影响模型性能。这种新模型将简化为更大的生理模型的集成,减少计算时间,并减少将皮肤酒精测量值转换为血液酒精浓度的时间。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bac/11446835/02321b173764/PHY2-12-e70070-g006.jpg

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