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<p>Artificial intelligence (AI) is revolutionizing clinical trials in geriatric populations by addressing the unique challenges of aging-related diseases and patient heterogeneity. Advanced AI techniques, including machine learning, deep learning, and AI-driven digital health platforms, enable intelligent patient stratification, risk prediction, and real-time monitoring tailored to older adults. AI facilitates the design and execution of decentralized clinical trials, improving accessibility and compliance among older participants. Moreover, AI-powered digital twins and predictive models enhance safety assessments and treatment personalization, optimizing therapeutic outcomes. By integrating multi-omics data, electronic health records, and wearable device outputs, AI enables precise and dynamic decision-making throughout the trial lifecycle. This approach not only increases trial efficiency and accuracy but also supports ethical, patient-centered research practices. This review explores the transformative role of AI in geriatric clinical trials, outlining key advancements, practical challenges, and strategic directions for establishing AI as a catalyst for precision medicine in aging populations.</p>

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Embracing the Digital Revolution: How Artificial Intelligence is Transforming Clinical Trials in Older Participants

  • 期刊论文

  • 发表日期：

    2026年3月4日

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  • Yaru Wang,
  • Miao Miao,
  • Qingqing Wang,
  • Yuyin Yin,
  • Haijuan Zhao,
  • Shuang Zhao,
  • Han Yang,
  • Xin Wang

摘要

Artificial intelligence (AI) is revolutionizing clinical trials in geriatric populations by addressing the unique challenges of aging-related diseases and patient heterogeneity. Advanced AI techniques, including machine learning, deep learning, and AI-driven digital health platforms, enable intelligent patient stratification, risk prediction, and real-time monitoring tailored to older adults. AI facilitates the design and execution of decentralized clinical trials, improving accessibility and compliance among older participants. Moreover, AI-powered digital twins and predictive models enhance safety assessments and treatment personalization, optimizing therapeutic outcomes. By integrating multi-omics data, electronic health records, and wearable device outputs, AI enables precise and dynamic decision-making throughout the trial lifecycle. This approach not only increases trial efficiency and accuracy but also supports ethical, patient-centered research practices. This review explores the transformative role of AI in geriatric clinical trials, outlining key advancements, practical challenges, and strategic directions for establishing AI as a catalyst for precision medicine in aging populations.