安全评价的PBPK和QST

IF 2.9 3区 医学 Q2 TOXICOLOGY
M. Siccardi
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引用次数: 0

摘要

基于生理的药代动力学(PBPK)模型与定量系统毒理学(QST)的整合代表了支持现代安全性评估的机制框架。虽然PBPK模型可以支持跨组织和物种的浓度模拟,但QST增加了一个动态层,可以捕获器官和系统水平上潜在毒性的生物过程。总之,这些方法通过将预测暴露与生物学相关的作用模式联系起来,使人们能够更全面地了解剂量-反应关系。当将体外或非临床数据转化为与人类相关的定量结果时,这一点尤其有价值。通过耦合动力学和动力学模型,可以根据机械方法和预测浓度来确定出发点,而不是依赖于经验阈值或安全系数。在本次会议中,我们将探讨PBPK-QST整合如何增强安全性评估的相关性和可重复性,支持减少动物使用,并与当前监管科学的趋势保持一致。该演讲还将反映模块化、开源建模生态系统如何在模型开发、资格认证和跨部门应用方面提高透明度和灵活性。总体而言,PBPK-QST框架通过提供定量和机制基础来预测毒性,提炼不确定性,并支持在药物和非药物环境下的循证决策,代表了下一代风险评估的战略性一步。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CEC03-04 PBPK and QST for safety assessments
The integration of physiologically based pharmacokinetic (PBPK) modeling with quantitative systems toxicology (QST) represents a mechanistic framework to support modern safety assessments. While PBPK models can support the simulation of concentrations across tissues and species, QST adds a dynamic layer that captures biological processes underlying toxicity at the organ and systems level.
Together, these approaches enable a more comprehensive understanding of dose–response relationships by linking predicted exposure to biologically relevant modes of action. This is particularly valuable when translating in vitro or nonclinical data into quantitative human-relevant outcomes. By coupling kinetic and dynamic models, it becomes possible to identify points of departure based on mechanistic approaches and supported by predicted concentrations, rather than relying on empirical thresholds or safety factors.
In this session, we will explore how PBPK-QST integration enhances the relevance and reproducibility of safety evaluations, supports the reduction of animal use, and aligns with current trends in regulatory science. The presentation will also reflect on how modular, open-source modeling ecosystems contribute to greater transparency and flexibility in model development, qualification, and application across sectors.
Overall, PBPK-QST frameworks represent a strategic step forward in next-generation risk assessment by providing a quantitative and mechanistic basis for predicting toxicity, refining uncertainty, and supporting evidence-based decisions in both pharmaceutical and non-pharmaceutical contexts.
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来源期刊
Toxicology letters
Toxicology letters 医学-毒理学
CiteScore
7.10
自引率
2.90%
发文量
897
审稿时长
33 days
期刊介绍: An international journal for the rapid publication of novel reports on a range of aspects of toxicology, especially mechanisms of toxicity.
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