革新药物发现:将人工智能与定量系统相结合 药理学 药理学
Igor Goryanin1, Irina Goryanin2, Oleg Demin3
1University of Edinburgh, Edinburgh, UK; MMWR LTD, Edinburgh, UK.
人工智能 (AI) 可以通过改进模型构建和预测来增强定量系统药理学 (QSP). 挑战仍然存在,但人工智能集成有望推进精准医学和药物开发.
科学领域:
- 药理学 药理学是指药理学的学科.
- 计算生物学是一种计算生物学.
- 人工智能的人工智能是人工智能.
背景情况:
- 定量系统药理学 (QSP) 整合了生物,生理和药理学数据,用于药物开发.
- 人工智能 (AI) 在QSP模型生成,参数估计和预测能力方面提供了潜在的进步.
研究的目的:
- 批判性地评估AI在QSP中的整合.
- 突出新型人工智能驱动的方法和讨论当前的局限性.
- 概述未来在药物发现和开发中整合人工智能的战略.
主要方法:
- 对QSP中人工智能应用的当前文献的综述.
- 讨论人工智能驱动的数据库,云平台和QSP作为服务 (QSPaaS).
- 探索包括代孕模型,虚拟患者生成和数字双胞胎在内的新方法.
主要成果:
- 人工智能可以增强QSP模型生成,参数估计和预测能力.
- 由人工智能驱动的平台可以支持QSP模型开发和QSPaaS.
- 像代孕建模和数字双胞胎这样的新方法对AI-QSP集成有希望.
结论:
- 在QSP中,人工智能集成面临着诸如计算复杂性,可解释性和数据集成等挑战.
- 未来的整合战略应侧重于提高精准医学,监管接受度和机制性解释性.
- 人工智能具有巨大的潜力,可以通过先进的QSP来改变药物发现和开发.
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