Traditional Chinese medicine (TCM) faces persistent gaps between evidence generation and clinical use. Building on Qian Xuesen's theory of open complex giant systems (OCGSs) and its qualitative-to-quantitative metasynthesis, we advance a complex-systems evidence framework tailored to TCM's hallmarks: a holistic perspective and pattern-based diagnosis and therapy. The framework integrates systems science, artificial intelligence, and allied disciplines to coordinate qualitative and quantitative approaches and to align macro-level effectiveness evaluation with micro-level mechanistic inquiry. It organizes multi-source evidence into a four-phase loop-production, differentiation, application, and validation: (1) standardizes evidence production; (2) conducts integrated evaluation along the disease-pattern-formula axis; (3) supports individualized effectiveness evaluation and decision-making; and (4) uses real-world feedback to verify and refine evidence. By linking clinical phenotypes, pathways, and outcomes into an evidence chain, the framework is intended to improve clinical decision quality and accelerate translational research. Beyond TCM, it offers a generalizable model for complex interventions acting on complex human systems, positioning TCM research for international scientific dialogue and modernization.
Wei et al. (Tue,) studied this question.
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