精确心血管医学:改变创新模式
Masanori Aikawa1,2,3, Abhijeet R Sonawane1,2, Sarvesh Chelvanambi1
1Center for Interdisciplinary Cardiovascular Sciences, Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States.
Frontiers in science
|December 11, 2025
概括
由于异质性,心血管疾病 (CVD) 仍然是导致死亡的主要原因. 使用人工智能和系统生物学的整合精确医学为有效的心血管疾病治疗和改善全球健康结果提供了新的希望.
科学领域:
- 心血管医学 心血管医学
- 生物医学研究生物医学研究
- 精准医学是一门精准的医学.
背景情况:
- 心血管疾病 (CVD) 是全球主要的死亡原因,尽管治疗方面取得了进展.
- 心血管疾病的多层次异质性,从分子机制到临床表现,是一个重大挑战.
- 由基因组和暴露组因素影响的个体变异性,需要基于精度的方法.
研究的目的:
- 探索新技术如何解决心血管疾病治疗中的挑战.
- 突出整合精准医学的潜力,以改善全球健康结果.
- 讨论系统生物学和网络医学在推进心血管研究中的作用.
主要方法:
- 人工智能 (AI) 应用于大型数据集,包括临床信息和多组数据 (基因组学,转录组学,蛋白质组学,代谢组学).
- 利用系统生物学和网络医学来阐明复杂的疾病机制.
- 采用新的计算方法,将发现转化为疗法,克服药物开发障碍.
主要成果:
- 人工智能和多组学分析可以揭示疾病机制,识别新生物标志物,并精确确定心血管疾病的潜在药物标.
- 计算方法有助于开发新疗法,并解决已确定目标的"可药性".
- 综合精准医学方法显示出更有效的心血管治疗的前景.
结论:
- 转向心血管医学基于精度的范式,需要加强跨学科的合作和数据科学的整合.
- 学术界和工业界之间的新伙伴关系对于将研究转化为临床实践至关重要.
- 全球政策和领导力对于资金,数据基础设施,监管框架以及患者获得创新疗法的公平准入至关重要.
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