Quality control of traditional Chinese medicines (TCM) has progressively evolved from empirical identification and component testing toward multicomponent and holistic control. With advances in modern pharmaceutical quality science, analytical technologies, manufacturing methods, and data environment, the central question is shifting from “what can be measured” to “what truly matters to product quality and therefore needs to be assured.” Centered on critical quality attributes (CQA), this article proposes a methodological framework that starts from clinical positioning and product understanding and proceeds through “a product quality profile-candidate quality attributes-CQA identification-investigation of materials, processes, and intermediate materials-identification of critical material attributes (CMAs)/critical process parameters (CPPs)-quality formation laws-quality state evaluation-continuous lifecycle confirmation”. CQA criticality should be supported by product-specific quality risks and corresponding evidence. CMAs and CPPs should be identified through whole-process investigation guided by CQAs, and whole-process investigation should serve targeted control rather than expansion of control items. The article further discusses the non-compensatory boundary of holistic evaluation, reliable measurement, complementary retrospective and prospective studies, and the role of real-world manufacturing data in continual confirmation. A shift from a component-oriented to a quality attribute-oriented approach does not negate established analytical technologies or quality standards. Rather, it relocates the starting point of quality research from “what can be found and measured” to “what truly matters, why it matters, how it is formed, and how it can be continuously assured.” This paradigm transformation requires further validation and refinement across different types of traditional Chinese medicine products and real-world commercial manufacturing data.

traditional Chinese medicine  /  quality attribute  /  critical quality attribute  /  whole-process control  /  quality state evaluation  /  regulatory science