Abstract: With changes in the medical model, restructuring of healthcare systems, and rapid development of digital technologies, clinical research is shifting from a paradigm centered on single projects and classical study designs toward a new paradigm emphasizing real-world settings, multisource data, interdisciplinary collaboration, and evidence translation. In contrast, current medical education still mainly focuses on disease knowledge, traditional epidemiology and biostatistics, and basic biomedical techniques, with insufficient training in research planning, systems thinking, teamwork, and translation. Internationally, platform-based, competency-oriented, and system-embedded training models have gradually emerged in clinical and translational science, learning health systems, implementation science, clinical informatics, precision medicine, and real-world research. In China, under the background of New Medical Education, training has begun to expand from traditional clinical research methods courses to comprehensive literacy, translational capacity, and interdisciplinary competence, but overall remains in a transitional stage from policy guidance and local exploration to systematic construction. In particular, the rapid emergence of generative artificial intelligence and AI agents in medical education, health care, and scientific research is accelerating changes in clinical research processes and organization, while also making the abilities to raise high-quality questions, generate original hypotheses, and maintain scientific judgment increasingly critical. This article reviews the current status of relevant education at home and abroad, analyzes major problems, and proposes suggestions for curriculum and training reform, to provide reference for the cultivation of clinical research talents in China.

Key words: clinical research new paradigm, medical education, translational science, real-world research, artificial intelligence