Evidence map›Paper›PMID 23346189›Full record

ArticleEvidence-based complementary and alternative medicine : eCAM2012

Traditional chinese medicine-based network pharmacology could lead to new multicompound drug discovery.

Jian Li, Cheng Lu, Miao Jiang, Xuyan Niu, Hongtao Guo, Li Li, Zhaoxiang Bian, Na Lin, Aiping Lu

Abstract read
In one paragraph

Article in Evidence-based complementary and alternative medicine : eCAM, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed
–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

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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

52 citing papers in PubMed.

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  9. Protective Effect ofDrug design, development and therapy · 2022
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  16. Nardosinone Alleviates Parkinson's Disease Symptoms in Mice by Regulating Dopamine D2 Receptor.Evidence-based complementary and alternative medicine : eCAM · 2021
    Article
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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

9 authors.

Jian LiSchool of Basic Medical Sciences, Beijing University of Chinese Medicine, Beijing 100029, China.
Cheng Lu
Miao Jiang
Xuyan Niu
Hongtao Guo
Li Li
Zhaoxiang Bian
Na Lin
Aiping Lu

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Current strategies for drug discovery have reached a bottleneck where the paradigm is generally "one gene, one drug, one disease." However, using holistic and systemic views, network pharmacology may be the next paradigm in drug discovery. Based on network pharmacology, a combinational drug with two or more compounds could offer beneficial synergistic effects for complex diseases. Interestingly, traditional chinese medicine (TCM) has been practicing holistic views for over 3,000 years, and its distinguished feature is using herbal formulas to treat diseases based on the unique pattern classification. Though TCM herbal formulas are acknowledged as a great source for drug discovery, no drug discovery strategies compatible with the multidimensional complexities of TCM herbal formulas have been developed. In this paper, we highlighted some novel paradigms in TCM-based network pharmacology and new drug discovery. A multiple compound drug can be discovered by merging herbal formula-based pharmacological networks with TCM pattern-based disease molecular networks. Herbal formulas would be a source for multiple compound drug candidates, and the TCM pattern in the disease would be an indication for a new drug.

Identifiers

PMID23346189
PMCPMC3541710

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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 OpenQuestion graph.