Dixit Simran, Sharma Deepti, Sharma Navneet, Shukla Vikesh Kumar
Amity Institute of Pharmacy, Amity University, Noida, Uttar Pradesh, 201303, India.
Amity Indian Military College for Women, Amity University, Noida, Uttar Pradesh, 201303, India.
Rev Recent Clin Trials. 2025 May 29. doi: 10.2174/0115748871359356250523033831.
An essential tool for assessing the efficacy and safety of novel therapies and interventions is the clinical trial. They are crucial for understanding disease causes, treatment effectiveness, and patient care processes. However, traditional clinical trials often suffer from inefficiencies, high costs, and extended timelines. This review explores how artificial intelligence can revolutionize clinical trials by addressing these inefficiencies in trial design, patient recruitment, and data analysis. It also discusses the challenges and solutions for incorporating AI within existing regulatory frameworks. This review is based on a comprehensive analysis of the existing literature on artificial intelligence applications in clinical trials. It includes an evaluation of studies that assess the role of artificial intelligence in enhancing trial efficiency, optimizing patient recruitment, and improving data analysis. Special attention is given to regulatory considerations, with a focus on Food and Drug Administration (FDA) guidelines and their impact on artificial intelligence integration in clinical research. The successful integration of artificial intelligence into clinical trials has the potential to optimize procedures, enhance clinical judgment, and improve patient outcomes. Artificial intelligence can streamline patient stratification, accelerate trial timelines, and enhance data analysis accuracy. However, overcoming challenges related to interpretability, data privacy, and regulatory compliance is crucial. Collaboration between researchers, artificial intelligence developers, and regulatory bodies is essential to establish guidelines ensuring artificial intelligence innovations are safe and effective. Ultimately, artificial intelligence could transform clinical research and pave the way for more personalized healthcare solutions.
评估新型疗法和干预措施的疗效与安全性的一项重要工具是临床试验。临床试验对于理解疾病病因、治疗效果及患者护理流程至关重要。然而，传统临床试验往往存在效率低下、成本高昂和时间线延长的问题。本综述探讨了人工智能如何通过解决试验设计、患者招募和数据分析方面的这些低效问题来彻底改变临床试验。它还讨论了将人工智能纳入现有监管框架的挑战与解决方案。本综述基于对关于人工智能在临床试验中应用的现有文献的全面分析。它包括对评估人工智能在提高试验效率、优化患者招募和改进数据分析方面作用的研究的评估。特别关注监管方面的考虑因素，重点是美国食品药品监督管理局（FDA）的指南及其对临床研究中人工智能整合的影响。将人工智能成功整合到临床试验中有可能优化流程、增强临床判断并改善患者结局。人工智能可以简化患者分层、加快试验时间线并提高数据分析准确性。然而，克服与可解释性、数据隐私和监管合规性相关的挑战至关重要。研究人员、人工智能开发者和监管机构之间的合作对于制定确保人工智能创新安全有效的指南至关重要。最终，人工智能可能会改变临床研究，并为更个性化的医疗保健解决方案铺平道路。
