从多层次in silico模型中得出的前节律失常预测的不确定性评估
Karolina Kopańska1, Pablo Rodríguez-Belenguer1,2, Jordi Llopis-Lorente3
1Research Programme on Biomedical Informatics (GRIB), Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Hospital del Mar Research Institute, Barcelona, Spain.
Archives of toxicology
|August 1, 2023
概括
在in silico药物安全模型中量化不确定性改善了对心脏风险的预测. 这种概率方法为心律失常生物标志物提供了值区间,增强了候选药物的评估.
科学领域:
- 计算毒理学计算毒理学
- 药理学 药理学是指药理学的学科.
- 生物物理学的生物物理.
背景情况:
- 在 silico 方法评估药物诱导的心律失常风险.
- 估计预测不确定性对于可靠的决策至关重要.
- 目前的模型通常依赖于药物特性单点估计.
研究的目的:
- 为多层次的前节律失常模型开发不确定性量化 (UQ) 方法.
- 在这些模型中识别出 aleatory 和 epistemic 不确定性的来源.
- 为候选药物提供更全面的风险评估.
主要方法:
- 开发了一种概率模拟方法,用价值分布取代单点输入.
- 通过模型传播IC50和电生理学参数的变化.
- 节律失调风险生物标志物的量化不确定性,例如90%再极化时的作用潜力持续时间 (APD90).
主要成果:
- 拟议的方法产生预测与相关的值间隔.
- 证明了输入变化对输出不确定性的影响.
- 在不同风险类别的12种已上市药物上成功测试.
结论:
- 概率模拟增强了形药物安全性评估的现实性.
- UQ为解释心律失常风险预测提供了必要的背景.
- 这种方法可以更全面地了解药物对人口心脏电生理学的影响.
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