Standard Deliberation

Dynamic and expandable quality grade evaluation method for Chinese herbal medicines and decoction pieces based on big data: Notoginseng Radix et Rhizoma as an example*

  • HONG Liang ,
  • ZHONG Ru-ci ,
  • ZHAO Jing ,
  • LI Shao-ping
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  • 1. State Key Laboratory of Quality Research in Chinese Medicine, University of Macau, Macao 999078, China;
    2. Macao Centre for Testing of Chinese Medicine, University of Macau, Macao 999078, China;
    3. Department of Pharmaceutical sciences, Faculty of Health Sciences, University of Macau, Macao 999078, China

Online published: 2025-10-13

Abstract

Objective: To establish a strategy and method for evaluating the quality grade of Chinese herbal medicines and decoction pieces based on big data, aiming to achieve high quality and good price. Methods: Data from literature sources in the Web of Science database and laboratory measurements were collected to construct a quality database of Notoginseng Radix et Rhizoma. The sum scoring method was used to obtain the scores of each sample data. Then, the kernel density estimation method was used to identify data-intensive area. Additionally, the Pareto principle was employed to ensure the objectivity and accuracy of the quality grading results. Results: A total of 28 literatures were collected, covering 336 relevant data. Based on this, the quality grades of 11 batches of Notoginseng Radix et Rhizoma samples from the laboratory were evaluated. Conclusion: The big data-based quality evaluation strategy proposes in this study features scalability and strong objectivity, providing a scientific, rational, and feasible method for the quality control and management of Chinese herbal medicines and decoction pieces.

Cite this article

HONG Liang , ZHONG Ru-ci , ZHAO Jing , LI Shao-ping . Dynamic and expandable quality grade evaluation method for Chinese herbal medicines and decoction pieces based on big data: Notoginseng Radix et Rhizoma as an example*[J]. Chinese Journal of Pharmaceutical Analysis, 2025 , 45(4) : 663 -670 . DOI: 10.16155/j.0254-1793.2024-1321

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