在预测毒理学中为量子力学辩护 - - 差不多100年太晚了?
Jakub Kostal1,2
1Designing Out Toxicity (DOT) Consulting LLC, 2121 Eisenhower Avenue, Alexandria, Virginia 22314, United States.
Chemical research in toxicology
|September 7, 2023
概括
量子力学 (QM) 对于药物发现至关重要,但在预测毒理学中未得到充分利用. 整合质量管理与人工智能可以推进无动物安全评估和毒理学预测.
科学领域:
- 计算化学计算化学
- 毒理学 毒理学 毒理学
- 药物发现 药物发现 药物发现
背景情况:
- 量子力学 (QM) 是化学和药物发现的标准,用于研究分子相互作用.
- 预测性毒理学尚未广泛采用QM,尽管它与新陈代谢和不良结果途径相关.
- 质量管理方法和计算能力的进步现在使实际的毒理学应用成为可能.
研究的目的:
- 倡导将QM整合到毒理学评估中.
- 突出质量管理对现有方法 (如化学安全的QSAR) 的补充作用.
- 通过QM和AI集成,提出在in silico毒理学方面的进展.
主要方法:
- 审查化学和毒理学中质量管理应用的现状.
- 分析在毒理学中采用质量管理的障碍,包括培训和基础设施.
- 展示了在危险评估中成功实施质量管理的例子.
主要成果:
- 质量管理提供了与传统毒理学方法直角的独特见解.
- 在危害评估中已经证明了成功的质量管理应用.
- 制药行业已经在药物发现中广泛使用QM.
结论:
- 质量管理应该是毒理学家的重要工具,增强预测能力.
- 整合质量管理与人工智能可以在毒理学和安全测试方面取得重大进展.
- 拥抱QM支持开发化学安全的无动物测试策略.
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