人工智能在罕见疾病药监中的作用
Ashish Jain1, Zahabia Adenwala2
1Curis Inc, Lexington, MA, USA.
Expert opinion on drug safety
|March 1, 2025
概括
人工智能 (AI) 和机器学习 (ML) 可以解决罕见病药物安全方面的药物监测 (PV) 差距. 这些技术可以改善不良事件报告和风险检测,克服当前的局限性.
科学领域:
- 药物监督 药物监督 药物监督
- 人工智能的人工智能
- 机器学习 机器学习
- 罕见疾病 罕见疾病
背景情况:
- 传统的药物监测措施存在重大缺陷,特别是在治疗罕见疾病的孤儿药物中.
- 不有效的不良事件 (AE) 报告,低患者入学率和弱信号监测阻碍了罕见疾病安全评估.
研究的目的:
- 评估人工智能 (AI) 和机器学习 (ML) 在缓解罕见病治疗中药监测挑战方面的潜力.
- 探索AI和ML如何提高孤儿药物的安全监测.
主要方法:
- 使用PubMed和谷歌学者对AI,ML和PV研究的文献搜索.
- 分析罕见疾病安全评估中的障碍,以及潜在的AI/ML解决方案.
主要成果:
- 人工智能和机器学习可以通过整合各种数据源并提高风险检测灵敏度来自动化AE报告.
- 隐私和模型可解释性等技术和监管障碍存在于人工智能在光伏应用中的采用.
结论:
- 人工智能和机器学习为加强罕见疾病治疗监测提供了巨大的潜力.
- 适当整合AI/ML可以加速为罕见疾病开发新疗法.
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