Traditional Chinese medicine （TCM）， as a complex system of substances， has long faced the challenges of an unclear material basis and obscure mechanisms of action， which has hindered its modernization and internationalization. To address these challenges， the “Herbalome” project was launched in 2007. This initiative aims to systematically reveal the material composition， structure， and biological functions of TCM through the integration of multidisciplinary technologies， thereby elucidating the synergistic mechanisms of multi-component and multi-target interactions. This paper reviews key methodological and technological advancements in the field of herbal material science. Specifically， regarding the composition and structural identification of herbal compounds， the integration of liquid chromatography-mass spectrometry with two-dimensional chromatography and intelligent data mining strategies has enabled high-throughput characterization of the complex chemical constituents of TCMs， as well as the discovery of novel compounds. Furthermore， advancements in multidimensional high-performance preparative chromatography and the development of novel multidimensional multi-channel separation and purification devices have overcome bottlenecks in the large-scale systematic preparation of TCM compounds. Additionally， nuclear magnetic resonance technology， enhanced by artificial intelligence techniques， such as intelligent heteronuclear single quantum coherence （HSQC） recognition and deep learning models， has significantly improved the efficiency and accuracy of structural identification. In the study of the biological effects of herbal substances， target-oriented and phenotype-oriented pharmacological technologies， such as cellular label-free integrative pharmacology， thermal proteome profiling， and affinity mass spectrometry， have facilitated the discovery of targets and the elucidation of mechanisms for bioactive components in TCM. Moreover， TCM databases and computational simulation techniques， including virtual screening， molecular dynamics， and artificial intelligence prediction models， have supported the construction and simulation of complex “multi-component and multi-target” interaction networks. Structural biology techniques， particularly cryo-electron microscopy， have provided atomic-level insights into the interactions between TCM bioactive components and target proteins， advancing our understanding of structure-activity relationships and multi-target mechanisms. In conclusion， the synergistic advancement of various techniques， including separation analysis， bioeffect evaluation， and computational modelling， is driving a paradigm shift in herbal material science from “experience-dependent” to “data-driven” approaches. The ongoing emergence and integration of novel technologies will continue to reveal unexplored areas within traditional Chinese medicine， systematically elucidate its multi-component， multi-target synergistic mechanisms， and enable the in-depth discovery of novel structures， targets， and biological effects. This progress will provide innovation insights to support the inheritance and innovation of traditional Chinese medicine as well as modern drug discovery.
LIU et al. (2026) studied this question.