The role of artificial intelligence in clinical trials in adult and pediatric rheumatology

The development of clinical trials is limited by high costs and methodological complexities. In this context, artificial intelligence (AI) is emerging as a key instrument for their optimization. In the early phases of study design and recruiting, generative AI systems may help refine eligibility criteria and boost enrollment; in parallel, the integration of digital biomarkers and patient-reported outcomes may allow continuous remote monitoring and improved safety data collection. Moreover, machine learning models may be applied to effectively analyze longitudinal multimodal trial data. However, AI implementation in real-world settings must overcome significant challenges; regulatory authorities are updating guidance, and a successful integration of AI-based interventions will depend on the rigorous application of quality standards while preserving the central role of medical judgment. In this review, we provide a comprehensive overview of the clinical applications, ethical considerations, and regulatory aspects of implementing AI in clinical trials in adult and pediatric rheumatology.