Evidence map›Paper›PMID 39800680›Full record

ReviewChinese medicine2025

Network pharmacology: a crucial approach in traditional Chinese medicine research.

Yiyan Zhai, Liu Liu, Fanqin Zhang, Xiaodong Chen, Haojia Wang, Jiying Zhou, Keyan Chai, Jiangying Liu, Huiling Lei, Peiying Lu and 3 more

Abstract readReview
In one paragraph

Review in Chinese medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 120 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
120citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

120 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Multidimensional therapeutic advantages ofFrontiers in endocrinology · 2026
    Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
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  11. Article
  12. Review
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  14. Luteolin alleviates inflammation by inhibiting the PI3K-Akt-FOXO3a pathway.Naunyn-Schmiedeberg's archives of pharmacology · 2026
    Article
  15. Review
  16. Review
  17. Article
  18. Article
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  20. Review

60 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Yiyan ZhaiSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China.
Liu LiuSchool of Chinese Medicine, Beijing University of Chinese Medicine, Beijing, 100029, China.
Fanqin ZhangSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China.
Xiaodong ChenSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China.
Haojia WangSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China.
Jiying ZhouSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China.
Keyan ChaiSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China.
Jiangying LiuSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China.
Huiling LeiSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China.
Peiying LuSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China.
Meiling GuoSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China.
Jincheng GuoSchool of Chinese Medicine, Beijing University of Chinese Medicine, Beijing, 100029, China. guojincheng@bucm.edu.cn.
Jiarui WuSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China. exogamy@163.com.ORCID http://orcid.org/0000-0002-1617-6110

Funding

China National Traditional Chinese Medicine Inheritance and Innovation Team Sub-project ZYYCXTD-C-202005-10Natural Science Foundation of China 82074284State Administration of Traditional Chinese Medicine of the People's Republic of China zyyzdxk-2023257
6 · The paper itself

Abstract

Network pharmacology plays a pivotal role in systems biology, bridging the gap between traditional Chinese medicine (TCM) theory and contemporary pharmacological research. Network pharmacology enables researchers to construct multilayered networks that systematically elucidate TCM's multi-component, multi-target mechanisms of action. This review summarizes key databases commonly used in network pharmacology, including those focused on herbs, components, diseases, and dedicated platforms for network pharmacology analysis. Additionally, we explore the growing use of network pharmacology in TCM, citing literature from Web of Science, PubMed, and CNKI over the past two decades with keywords like "network pharmacology", "TCM network pharmacology", and "herb network pharmacology". The application of network pharmacology in TCM is widespread, covering areas such as identifying the material basis of TCM efficacy, unraveling mechanisms of action, and evaluating toxicity, safety, and novel drug development. However, challenges remain, such as the lack of standardized data collection across databases and insufficient consideration of processed herbs in research. Questions also persist regarding the reliability of study outcomes. This review aims to offer valuable insights and reference points to guide future research in precision TCM network pharmacology.

Indexed as

Current state of researchDatabaseNetwork pharmacologyPrecision network pharmacologyTraditional Chinese medicine

Identifiers

PMID39800680
PMCPMC11725223

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.