Evidence map›Paper›PMID 30123072›Full record

ReviewInternational journal of biological sciences2018

Review of Drug Repositioning Approaches and Resources.

Hanqing Xue, Jie Li, Haozhe Xie, Yadong Wang

Abstract readReview
In one paragraph

Review in International journal of biological sciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 264 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
264citing papers in PubMed, 3 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

264 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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  12. Repurposed drug prioritization pipeline for a multi-arm platform trial in clinical Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
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204 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

4 authors.

Hanqing XueSchool of Computer Science and Technology, Harbin Institute of Technology, 150001, Harbin, China.
Jie LiSchool of Computer Science and Technology, Harbin Institute of Technology, 150001, Harbin, China.
Haozhe XieSchool of Computer Science and Technology, Harbin Institute of Technology, 150001, Harbin, China.
Yadong WangSchool of Computer Science and Technology, Harbin Institute of Technology, 150001, Harbin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drug discovery is a time-consuming, high-investment, and high-risk process in traditional drug development. Drug repositioning has become a popular strategy in recent years. Different from traditional drug development strategies, the strategy is efficient, economical and riskless. There are usually three kinds of approaches: computational approaches, biological experimental approaches, and mixed approaches, all of which are widely used in drug repositioning. In this paper, we reviewed computational approaches and highlighted their characteristics to provide references for researchers to develop more powerful approaches. At the same time, the important findings obtained using these approaches are listed. Furthermore, we summarized 76 important resources about drug repositioning. Finally, challenges and opportunities in drug repositioning are discussed from multiple perspectives, including technology, commercial models, patents and investment.

Indexed as

Computational BiologyDrug DiscoveryDrug RepositioningHumans

Identifiers

PMID30123072
PMCPMC6097480

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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 OpenQuestion graph.