Evidence map›Paper›PMID 40122800›Full record

ReviewChinese medicine2025

A new paradigm for drug discovery in the treatment of complex diseases: drug discovery and optimization.

Yu Yuan, Lulu Yu, Chenghao Bi, Liping Huang, Buda Su, Jiaxuan Nie, Zhiying Dou, Shenshen Yang, Yubo Li

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 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

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

19 citing papers in PubMed.

  1. Article
  2. Review
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  4. Review
  5. Article
  6. Review
  7. Article
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  9. Article
  10. Problems associated with the ATC system of drug classification.Naunyn-Schmiedeberg's archives of pharmacology · 2026
    Article
  11. Review
  12. Multifaceted mechanistic exploration ofFrontiers in cell and developmental biology · 2026
    Article
  13. Review
  14. Article
  15. Article
  16. Review
  17. Frontiers in pharmacology · 2025
    Article
  18. Review
  19. Review
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.

Yu Yuan *State Key Laboratory of Component-Based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, 301617, China.
Lulu Yu *State Key Laboratory of Component-Based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, 301617, China.
Chenghao Bi *State Key Laboratory of Component-Based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, 301617, China.
Liping HuangState Key Laboratory of Component-Based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, 301617, China.
Buda SuState Key Laboratory of Component-Based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, 301617, China.
Jiaxuan NieState Key Laboratory of Component-Based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, 301617, China.
Zhiying DouSchool of Traditional Chinese Medicine, Tianjin University of Chinese Medicine, Tianjin, 301617, China. zhiyingdou@163.com.
Shenshen YangState Key Laboratory of Component-Based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, 301617, China. shine2099@163.com.
Yubo LiState Key Laboratory of Component-Based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, 301617, China. yaowufenxi001@sina.com.ORCID http://orcid.org/0000-0003-0455-0969

Funding

National Natural Science Foundation of China 82141209National Natural Science Foundation of China 82474217the foundation of New 20 University Policies of Jinan 202333018
6 · The paper itself

Abstract

In the past, the drug research and development has predominantly followed a "single target, single disease" model. However, clinical data show that single-target drugs are difficult to interfere with the complete disease network, are prone to develop drug resistance and low safety in clinical use. The proposal of multi-target drug therapy (also known as "cocktail therapy") provides a new approach for drug discovery, which can affect the disease and reduce adverse reactions by regulating multiple targets. Natural products are an important source for multi-target innovative drug development, and more than half of approved small molecule drugs are related to natural products. However, there are many challenges in the development process of natural products, such as active drug screening, target identification and preclinical dosage optimization. Therefore, how to develop multi-target drugs with good drug resistance from natural products has always been a challenge. This article summarizes the applications and shortcomings of related technologies such as natural product bioactivity screening, clarify the mode of action of the drug (direct/indirect target), and preclinical dose optimization. Moreover, in response to the challenges faced by natural products in the development process and the trend of interdisciplinary and multi-technology integration, and a multi-target drug development strategy of "active substances - drug action mode - drug optimization" is proposed to solve the key challenges in the development of natural products from multiple dimensions and levels.

Indexed as

Drug discoveryDrug repurposingNatural products

Identifiers

PMID40122800
PMCPMC11931805

What OpenQuestion holds

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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 OpenQuestion graph.