标准研讨

基于大数据的动态可扩充式中药材和饮片质量等级评价方法:以三七为例*

  • 洪亮 ,
  • 钟如此 ,
  • 赵静 ,
  • 李绍平
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  • 1.澳门大学中药质量研究国家重点实验室,中国澳门 999078;
    2.澳门大学澳门中药检验中心,中国澳门 999078;
    3.澳门大学健康科学学院药学系,中国澳门 999078
第一作者 洪亮 Tel:(+853)65397106;E-mail:yc07543@um.edu.mo
钟如此 Tel:(+853)63955116;E-mail:yc47536@um.edu.mo
** 李绍平 Tel:(+853)88224692;E-mail:lishaoping@hotmail.com
赵静 Tel:(+853)88224873;E-mail:zhaojing.cpu@163.com

网络出版日期: 2025-10-13

基金资助

* 澳门科学技术发展基金项目(0075/2022/A、028/2022/ITP和0005/2024/AKP); 珠海市社会发展领域科技计划项目(2220004000117); 澳门大学科学研究基金项目(MYRG-GRG2023-00082-ICMS-UMDF和CPG2024-00011-ICMS)

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

摘要

目的: 质量等级划分是实现优质优价的基础,本研究旨在建立基于大数据的中药材和饮片质量等级评价策略与方法。方法: 通过收集Web of Science数据库中的文献数据和实验室测定数据,构建了三七质量数据库。采用总和评分法获得各样本数据的得分,随后运用核密度估计法来识别数据密集区域,并结合帕累托原则划分中药质量等级,以确保质量评级结果的客观性和准确性。结果: 共收集28篇文献,涵盖336条相关数据。据此,对实验室测定的11批三七样品进行了质量等级评价。结论: 本研究提出的基于大数据的质量评价策略,具有可扩展性、客观性强等特点,为中药材和饮片的质量控制和管理提供了科学、合理且可行的方法。

本文引用格式

洪亮 , 钟如此 , 赵静 , 李绍平 . 基于大数据的动态可扩充式中药材和饮片质量等级评价方法:以三七为例*[J]. 药物分析杂志, 2025 , 45(4) : 663 -670 . DOI: 10.16155/j.0254-1793.2024-1321

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.

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