经典名方是中医药宝库中的瑰宝，也是中医药科学价值的具体体现，现今国家颁布了一系列管理规定及技术指导原则，以鼓励经典名方制剂的研发。在研发过程中，关键质量属性（critical quality attributes，CQAs）作为反映经典名方质量与疗效的特征属性，是经方制剂研发的重点与核心。目前，经典名方关键质量属性研究主要采用“特征图谱、指标性成分含量与出膏率相结合”的评价模式，但若要全面反映经典名方制剂质量，某些影响经典名方安全性与有效性的潜在CQAs及其重要影响因素值得深入探究。通过从经方研发的“药材、饮片、基准样品、制剂”4个环节分析其中值得关注的“物理、化学、生物或微生物”3个层面的CQAs及其重要影响因素，以期为经典名方的创新研发、质量控制及临床应用提供参考，促进经典名方的高品质传承和高质量发展。

The classical famous prescriptions are the treasure of traditional Chinese medicine and the concrete embodiment of the scientific value of traditional Chinese medicine. At present, the state has promulgated a series of management regulations and technical guidelines to encourage the research and development of classical famous prescriptions. In the process of research, the critical quality attributes (CQAs), as the characteristic attributes reflecting the quality and efficacy of classical famous prescriptions, are the focus and core of the research and development of classical prescriptions. At present, researches on CQAs of classic famous prescriptions mainly adopt the evaluation model of “characteristic spectrum, index component content and extract rate”. However, some potential CQAs and important influencing factors that affect the safety and effectiveness of classic famous prescriptions deserve further exploration to fully reflect the quality of classic famous prescriptions. In order to provide reference for the innovative research and development, quality control and clinical application of classic prescription, promote high-quality inheritance and development of classic prescription, the critical quality attributes of “physical, chemical, biological or microbial” and their important influencing factors in the process of classical famous prescription development from four levels of “Chinese herbal medicine, decoction, reference sample and preparation” were analyzed in this article.

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国家自然科学基金青年基金（81803742）；四川省科技计划重点研发项目（2020YFS0567）；四川省科技厅四川省科技计划项目（2021YJ0251）；四川省中医药管理局中医药科研专项（2021MS109）；成都中医药大学杏林学者青年学者专项（QNXZ2019031）；成都中医药大学杏林学者青基人才专项（QJRC2022027）；四川新绿色药业博士后科研专项（301022019）