Artificial Intelligence vs. Evidence-Based Clinical Trials in Humans: A Paradigm Shift in Clinical Research

Abstract

Prospective interventional clinical studies in humans remain the cornerstone of evidence-based medicine, guiding clinical decision-making and regulatory approvals. However, with the rapid advancement of Artificial Intelligence (AI) and the conceptual emergence of Artificial General Intelligence (AGI), the medical community is beginning to explore whether these technologies can augment or even replace traditional clinical trials. This manuscript critically examines the capabilities of AI and AGI in simulating, predicting, and evaluating clinical interventions. We discuss the methodological, ethical, and regulatory considerations of such a paradigm shift. While AI shows promise in retrospective analyses, clinical decision support, and trial optimization, replacing prospective interventional trials remains beyond current technological and ethical limits. Though theoretically more capable, AGI introduces concerns of explainability, bias propagation, and validation challenges. The future of clinical trials may lie in hybrid models that integrate AI with traditional methodologies, enhancing efficiency without compromising scientific rigor.

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