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Cited by 288

The DOI matches its Crossref record; 121 of the 121 references it cites were found in a registry or an index.

In silico repositioning of approved drugs for rare and neglected diseases

Open access
Ekins, Sean, Williams, Antony J., Krasowski, Matthew D., Freundlich, Joel S.·2011·Drug Discovery Today

Abstract

One approach to speed up drug discovery is to examine new uses for existing approved drugs, so-called 'drug repositioning' or 'drug repurposing', which has become increasingly popular in recent years. Analysis of the literature reveals many examples of US Food and Drug Administration-approved drugs that are active against multiple targets (also termed promiscuity) that can also be used to therapeutic advantage for repositioning for other neglected and rare diseases. Using proof-of-principle examples, we suggest here that with current in silico technologies and databases of the structures and biological activities of chemical compounds (drugs) and related data, as well as close integration with in vitro screening data, improved opportunities for drug repurposing will emerge for neglected or rare/orphan diseases.

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Crossref · 10.1016/j.drudis.2011.02.016

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Metadata

Authors
Ekins, S., Williams, A. J., Krasowski, M. D., & Freundlich, J. S.
Venue
Drug Discovery Today
Publisher
Elsevier BV
Published
2011-04
Volume
16
Issue
7-8
Pages
298-310
ISSN
1359-6446 (ISSN-L)
OpenAlex
W2114445615
Cited by
288
References
121
FWCI
24.22
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: In silico repositioning of approved drugs for rare and neglected diseases. https://app.cochat.ai/papers/10.1016/j.drudis.2011.02.016
The paper
Ekins, S., Williams, A. J., Krasowski, M. D., & Freundlich, J. S. (2011). In silico repositioning of approved drugs for rare and neglected diseases. Drug Discovery Today. https://doi.org/10.1016/j.drudis.2011.02.016

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.