Advances in intelligent mass spectrometry data processing technology for in vivo analysis of natural medicines

作     者：CHEN Simian DAI Binxin ZHANG Dandan YANG Yuexin ZHANG Hairong ZHANG Junyu LU Di WU Caisheng 

作者机构：Fujian Provincial Key Laboratory of Innovative Drug Target Research and State Key Laboratory of Cellular Stress BiologySchool of Pharmaceutical SciencesXiamen UniversityXiamen 361102China Xiamen Key Laboratory for Clinical Efficacy and Evidence-Based Research of Traditional Chinese MedicineXiamen UniversityXiamen 361102China 

出 版 物：《Chinese Journal of Natural Medicines》 (中国天然药物（英文版）)

年 卷 期：2024年第22卷第10期

页      面：900-913页

核心收录：

学科分类：1007[医学-药学(可授医学、理学学位)] 100704[医学-药物分析学] 10[医学] 

基　　金：supported by the National Natural Science Foundation of China(Nos.82222068,82141215 and 82173779) the Innovation Team and Talents Cultivation Program of National Administration of Traditional Chinese Medicine(No.ZYYCXTD-D-202206) the Science and Technology Project of Fujian Province(Nos.2022J02057,2021J02058 and 2021I0003) the S&T Program of Hebei Province(No.23372508D) 

主　　题：High-performance liquid chromatography–High-resolution mass spectrometry Data-acquisition Data-processing Artificial Intelligence Metabolomics 

摘      要：Natural medicines(NMs)are crucial for treating human *** characterizing their bioactive components in vivo has been a key focus and challenge in NM ***-performance liquid chromatography-high-resolution mass spectrometry(HPLC-HRMS)systems offer high sensitivity,resolution,and precision for conducting in vivo analysis of ***,due to the complexity of NMs,conventional data acquisition,mining,and processing techniques often fail to meet the practical needs of in vivo NM *** the past two decades,intelligent spectral data-processing techniques based on various principles and algorithms have been developed and applied for in vivo NM ***,improvements have been achieved in the overall analytical performance by relying on these techniques without the need to change the instrument *** improvements include enhanced instrument analysis sensitivity,expanded compound analysis coverage,intelligent identification,and characterization of nontargeted in vivo compounds,providing powerful technical means for studying the in vivo metabolism of NMs and screening for pharmacologically active *** review summarizes the research progress on in vivo analysis strategies for NMs using intelligent MS data processing techniques reported over the past two *** discusses differences in compound structures,variations among biological samples,and the application of artificial intelligence(AI)neural network ***,the review offers insights into the potential of in vivo tracking of NMs,including the screening of bioactive components and the identification of pharmacokinetic *** aim is to provide a reference for the integration and development of new technologies and strategies for future in vivo analysis of NMs.