{"title":"Unveiling secrets of traditional Chinese medicine: Cutting-edge techniques in component analysis","authors":"Tingting Zhou","doi":"10.1016/j.chmed.2025.05.006","DOIUrl":null,"url":null,"abstract":"<div><div>Chemical component analysis is a critical challenge in Chinese herbal medicine research, involving the qualitative and quantitative identification of complex constituents in traditional Chinese medicine (TCM). However, traditional analytical methods are insufficient for efficient and comprehensive analysis of complex composition of TCM. Limitations exist in sample preparation, instrumental technology, data processing, and activity-related quality marker research. Recent advancements have significantly improved analytical precision, enabling more comprehensive profiling of TCM components. New pretreatment methods improve extraction efficiency and detection sensitivity, while novel instrumental technologies, such as mass spectrometry imaging, preserve spatial information lost in homogenization. AI enhances data interpretation, improving accuracy and efficiency. Online activity analysis links chemical composition with bioactivity, overcoming the limitations of purely chemical profiling and enabling a more comprehensive evaluation of TCM efficacy. This perspective provides an overview of the development trends in component analysis, aiming to advance the field and support TCM modernization.</div></div>","PeriodicalId":9916,"journal":{"name":"Chinese Herbal Medicines","volume":"17 3","pages":"Pages 484-487"},"PeriodicalIF":4.7000,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Chinese Herbal Medicines","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1674638425000619","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MEDICINAL","Score":null,"Total":0}
引用次数: 0
Abstract
Chemical component analysis is a critical challenge in Chinese herbal medicine research, involving the qualitative and quantitative identification of complex constituents in traditional Chinese medicine (TCM). However, traditional analytical methods are insufficient for efficient and comprehensive analysis of complex composition of TCM. Limitations exist in sample preparation, instrumental technology, data processing, and activity-related quality marker research. Recent advancements have significantly improved analytical precision, enabling more comprehensive profiling of TCM components. New pretreatment methods improve extraction efficiency and detection sensitivity, while novel instrumental technologies, such as mass spectrometry imaging, preserve spatial information lost in homogenization. AI enhances data interpretation, improving accuracy and efficiency. Online activity analysis links chemical composition with bioactivity, overcoming the limitations of purely chemical profiling and enabling a more comprehensive evaluation of TCM efficacy. This perspective provides an overview of the development trends in component analysis, aiming to advance the field and support TCM modernization.
期刊介绍:
Chinese Herbal Medicines is intended to disseminate the latest developments and research progress in traditional and herbal medical sciences to researchers, practitioners, academics and administrators worldwide in the field of traditional and herbal medicines. The journal's international coverage ensures that research and progress from all regions of the world are widely included.
CHM is a core journal of Chinese science and technology. The journal entered into the ESCI database in 2017, and then was included in PMC, Scopus and other important international search systems. In 2019, CHM was successfully selected for the “China Science and Technology Journal Excellence Action Plan” project, which has markedly improved its international influence and industry popularity. CHM obtained the first impact factor of 3.8 in Journal Citation Reports (JCR) in 2023.