革命性的毒理风险评估:新方法 (NAM) 和精确毒理学的整合性进展
Qiu-Shuang Sheng1, Bin Liu2, Xiao Wang2
1Jilin Province Product Quality Supervision and Inspection Institute, Changchun, 130103, China. shengqiushuang@jlzjy.org.
Archives of toxicology
|September 2, 2025
概括
新方法 (NAM) 为传统的动物化学安全试验提供了先进的,与人类相关的替代方案. 这些方法,包括器官芯片和计算毒理学,提高了预测能力,但需要进一步开发才能获得监管机构的认可.
科学领域:
- 毒理学
- 生物技术
- 计算生物学
背景情况:
- 传统毒理学依赖于动物试验和简单的体外模型,面临成本,时间和人类相关性的限制.
- 两种物种之间的差异和简单模型阻碍了当前毒理学评估的预测准确性.
研究的目的:
- 审查化学安全评估中新方法的变革潜力.
- 突出器官芯片,多组学和计算毒理学的进步,以改善危险评估.
- 确定目前的瓶和监管采用和精确毒理学的未来战略.
主要方法:
- 对模拟人类器官生理和交叉通话的器官芯片 (OoC) 平台的审查.
- 整合多组技术 (基因组学,蛋白质组学,代谢组学) 以获得机械毒性见解.
- 应用计算毒理学,机器学习和QSAR建模来确定危险优先级.
主要成果:
- 包括OOC和计算方法在内的NAM为传统方法提供了相关且高效的替代方案.
- 进步提供了对毒性途径的增强机械洞察力,并提高了预测准确性.
- 目前的局限性包括模型复杂性,AI解释性,混合物毒性量化和监管滞后.
结论:
- 化学品安全评估代表了向更具预测性和道德性的化学品安全评估的模式转变.
- 解决模型复杂性,人工智能和监管框架的瓶对于广泛采用至关重要.
- 未来的方向包括概率风险评估,人工智能驱动的暴露学,以及准确毒理学跨学科合作.
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