药物基因组学中的人工智能和多基因组学:精准医学的新时代
Mike Zack1, Danil N Stupichev1, Alex J Moore1
1PGxAI Inc., Palo Alto, CA.
Mayo Clinic proceedings. Digital health
|August 29, 2025
概括
药物基因组学正在与多基因组学和人工智能 (AI) 一起发展. 这种融合为药物反应提供了更深入的见解,为个性化医疗和改善患者护理铺平了道路.
科学领域:
- 基因组医学
- 生物信息学
- 计算生物学
背景情况:
- 药物遗传学已经显示出临床益处, 但与复杂的药物反应作斗争.
- 患者的药物反应受到基因组,表观遗传和代谢因素的复杂网络的影响.
- 多基因组数据 (基因组,转录组,蛋白质组,代谢组) 提供了对患者生物学的全面了解.
研究的目的:
- 审查药物遗传学领域的技术进步,将多种药物数据与人工智能 (AI) 整合起来.
- 讨论人工智能驱动的多组分析在个性化医疗中的潜力.
- 突出临床翻译的挑战和未来方向.
主要方法:
- 集成高通量"omics"技术与先进的人工智能模型 (深度神经网络,图形神经网络).
- 使用多层数据层来全面了解患者特异性的生物学.
- 利用来自不同群体的现实数据来改进算法.
主要成果:
- 人工智能通过检测隐藏的模式,处理不完整的数据和启用模拟来增强多态.
- 这种协同作用提高了预测准确度,并为治疗结果提供了更深入的机制洞察力.
- 包括性数据集和特定人口算法对于减少健康差异至关重要.
结论:
- 多种经验融合与人工智能之间的协同作用对改变临床决策具有重大意义.
- 克服数据协调,可解释性和监管方面的挑战是广泛采用的关键.
- 最终的目标是将这些创新转化为日常的个性化医疗.
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