通过PBPK建模,贝叶斯推理和实验设计来提高皮肤透性预测
Abdullah Hamadeh1,2, Abdulkarim Najjar3, John Troutman4
1School of Pharmacy, University of Waterloo, Kitchener, ON N2G 1C5, Canada.
基于生理学的药理动力学 (PBPK) 模型提高了用于药物输送和化学风险评估的皮肤吸收的预测. 优化不同pH值和多种化合物的实验设计可以提高新型应用的模型准确性.
科学领域:
- 药理动力学和皮肤吸收模型
- 计算毒理学计算毒理学
- 药物输送系统 药物输送系统
背景情况:
- 基于生理学的药理动力学 (PBPK) 模型对于估计药物输送和皮肤病产品化学风险至关重要.
- 量化皮肤透性的机械决定因素是准确皮肤吸收预测的关键.
研究的目的:
- 呈现PBPK工作流程,用于量化皮肤透性决定因素.
- 使用机械模型预测皮肤吸收在新的背景下.
- 确定影响皮肤吸收模型强度的因素.
主要方法:
- 在开源框架内开发了一种最先进的机械皮肤吸收模型.
- 进行敏感性分析以确定关键的不确定参数.
- 采用贝叶斯马尔科夫链蒙特卡洛 (MCMC) 用于参数估计,使用体外透性数据.
- 通过模拟模型与更新的参数分布来生成外推.
主要成果:
- 确定了影响皮肤透性的特定化合物,特定个体和特定部位的参数.
- 当训练数据包括多个车辆pH值和每个受试者的化合物时,在导出透度中获得了最高的准确性和精度.
- 证明了PBPK模型在各种实验条件下预测皮肤吸收的实用性.
结论:
- 该研究为皮肤吸收的机械PBPK建模提供了一种工作流.
- 结合多个pH值和化合物的实验设计显著提高了模型的预测能力.
- 这项研究为实验设计提供了信息,用于在药物输送和风险评估中进行强大的皮肤吸收建模.
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