将定量系统药理建模与机器学习和人工智能结合起来,用于药物开发:它的pAIns和gAIns
Núria Folguera-Blasco1, Florencia A T Boshier1, Aydar Uatay1
1Systems Medicine, Clinical Pharmacology and Safety Sciences, R and D BioPharmaceuticals, AstraZeneca, Cambridge, United Kingdom.
将定量系统药理 (QSP) 与人工智能 (AI) 和机器学习 (ML) 结合起来,为药物开发提供了显著的好处. 应对不确定性和偏见等潜在挑战对于成功实施和范式转变至关重要.
科学领域:
- 药理学和计算生物学
- 药物开发和发现
- 人工智能在医学中的应用
背景情况:
- 定量系统药理学 (QSP) 是药物开发中的一项成熟工具.
- 将QSP与AI和ML集成,提高了其适用性和潜力.
- 多维数据,包括现实世界的数据,提供了新的见解.
研究的目的:
- 探索QSP与AI/ML在药物开发中的共生整合.
- 以案例示例展示这种方法的好处和挑战.
- 通过从复杂的数据中解锁洞察力,突出突破的潜力.
主要方法:
- 应用一个共生QSP和AI/ML方法.
- 分析多维数据,包括真实世界的数据.
- 案例研究示例说明了整合和结果.
主要成果:
- 这种共生在药物开发中提供了显著的好处 ("gAIns").
- 潜在的挑战包括评估不确定性,偏见和错误.
- 案例示例展示了从数据中解锁新见解的潜力.
结论:
- 协生QSP和AI/ML方法可以推动药物开发的突破.
- 应对不确定性和偏见等挑战对于成功实施至关重要.
- 这种整合有可能催化该领域的范式转变.
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