毒理学数字化:改善临床前至临床翻译
Brian R Berridge1, Szczepan W Baran2, Vivek Kumar3
1B2 Pathology Solutions LLC, Cary, NC, United States.
Frontiers in toxicology
|April 12, 2024
概括
使用传感器和人工智能的动物研究的数字化可以通过提供更容易获得,相关和高效的数据来改善药物安全性评估. 这提高了人类药物开发临床前模型的预测能力.
科学领域:
- 临床前药物开发阶段
- 监测动物福利和动物行为.
- 翻译安全评估的翻译.
背景情况:
- 药物发现面临着很高的消耗率,通常是由于在开发或营销后发现的安全责任.
- 目前的动物研究对于安全性评估至关重要,但存在翻译差距,无法预测对人类的毒性.
- 需要提高动物安全研究的有效性和翻译相关性.
研究的目的:
- 审查药物发现中的动物安全评估的现状.
- 讨论改善临床前安全评估的机会.
- 探索传感器技术,人工智能和动物行为分析的整合.
主要方法:
- 对动物安全评估当前实践的审查.
- 讨论数字化和整体监测方法.
- 探索用于连续监测动物的传感器技术.
- 人工智能 (AI) 用于数据分析的应用.
主要成果:
- 整体监测和数字化可以丰富动物研究结果.
- 持续监测提供了行为和生理学的纵向数据.
- 自动化措施可以减少评估中的人类偏见和主观性.
- 增强的数据集在计算上更容易获得,在翻译上更相关,更可复制和更有效.
结论:
- 整合传感器技术,人工智能和动物行为分析为改善药物安全性评估提供了重大潜力.
- 数字化动物研究可以为人类翻译提供更具预测性和可靠的数据.
- 为了重新发明传统的药物安全范式,必须采用多学科的方法.
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