AI in clinical trials: Current status, challenges, and future directions for emergency infectious disease clinical trials -Insights from the 2025 iCROWN Symposium.

IF 2.3 Q3 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Eriko Morino, Daisuke Tokita
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Abstract

Artificial intelligence (AI) has the potential to transform how drug development and clinical trials are conducted. The 2025 Infectious Disease Clinical Research Network with National Repository (iCROWN) Symposium held in Japan on January 26, 2026 brought together experts from academia, industry, and research ethics to discuss current applications, limitations, and ethical considerations of AI in clinical trials, with a particular focus on emergency infectious disease research. Presentations highlighted a wide range of use cases for generative AI, including protocol writing; generating and reviewing clinical trial documents such as the statistical analysis plan (SAP) and the clinical study report (CSR); patient matching; data monitoring; and query creation. These applications are expected to accelerate and streamline clinical trials while maintaining quality and reducing costs. Standardization of digital data flows in clinical trials further facilitates the adoption of AI. Drawing on the FDA-EMA guiding principles for good AI practice, discussions emphasized the importance of accountability, explainability, fairness, and generalizability, while addressing risks such as overreliance, bias, and deskilling. The symposium concluded that while AI may enable more efficient clinical trial deployment during future public health crises, its challenges must be recognized and addressed.

人工智能在临床试验中的应用:紧急传染病临床试验的现状、挑战和未来方向——来自2025年icown研讨会的见解。
人工智能(AI)有可能改变药物开发和临床试验的方式。2026年1月26日在日本举行的2025年传染病临床研究网络与国家知识库(iCROWN)研讨会汇集了来自学术界、工业界和研究伦理的专家,讨论人工智能在临床试验中的当前应用、局限性和伦理考虑,特别关注紧急传染病研究。演讲强调了生成式人工智能的广泛用例,包括协议编写;生成和审核临床试验文件,如统计分析计划(SAP)和临床研究报告(CSR);病人匹配;数据监控;以及查询创建。这些应用有望加速和简化临床试验,同时保持质量和降低成本。临床试验中数字数据流的标准化进一步促进了人工智能的采用。根据FDA-EMA关于良好人工智能实践的指导原则,讨论强调了问责制、可解释性、公平性和概括性的重要性,同时解决了过度依赖、偏见和去技能化等风险。专题讨论会的结论是,虽然人工智能可以在未来的公共卫生危机期间更有效地部署临床试验,但必须认识到并应对其挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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