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Open-source approaches for the repurposing of existing or failed candidate drugs: learning from and applying the lessons across diseases

Overview of attention for article published in Drug Design, Development and Therapy, August 2013
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (91st percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

blogs
2 blogs
policy
1 policy source
twitter
1 X user

Citations

dimensions_citation
73 Dimensions

Readers on

mendeley
152 Mendeley
Title
Open-source approaches for the repurposing of existing or failed candidate drugs: learning from and applying the lessons across diseases
Published in
Drug Design, Development and Therapy, August 2013
DOI 10.2147/dddt.s46289
Pubmed ID
Authors

Minna Allarakhia

Abstract

Repurposing has the objective of targeting existing drugs and failed, abandoned, or yet-to-be-pursued clinical candidates to new disease areas. The open-source model permits for the sharing of data, resources, compounds, clinical molecules, small libraries, and screening platforms to cost-effectively advance old drugs and/or candidates into clinical re-development. Clearly, at the core of drug-repurposing activities is collaboration, in many cases progressing beyond the open sharing of resources, technology, and intellectual property, to the sharing of facilities and joint program development to foster drug-repurposing human-capacity development. A variety of initiatives under way for drug repurposing, including those targeting rare and neglected diseases, are discussed in this review and provide insight into the stakeholders engaged in drug-repurposing discovery, the models of collaboration used, the intellectual property-management policies crafted, and human capacity developed. In the case of neglected tropical diseases, it is suggested that the development of human capital be a central aspect of drug-repurposing programs. Open-source models can support human-capital development through collaborative data generation, open compound access, open and collaborative screening, preclinical and possibly clinical studies. Given the urgency of drug development for neglected tropical diseases, the review suggests elements from current repurposing programs be extended to the neglected tropical diseases arena.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 152 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Spain 1 <1%
Mexico 1 <1%
United States 1 <1%
Unknown 148 97%

Demographic breakdown

Readers by professional status Count As %
Student > Master 30 20%
Student > Ph. D. Student 22 14%
Researcher 21 14%
Student > Bachelor 16 11%
Other 8 5%
Other 22 14%
Unknown 33 22%
Readers by discipline Count As %
Medicine and Dentistry 24 16%
Pharmacology, Toxicology and Pharmaceutical Science 21 14%
Agricultural and Biological Sciences 20 13%
Biochemistry, Genetics and Molecular Biology 12 8%
Chemistry 10 7%
Other 29 19%
Unknown 36 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 16. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 July 2017.
All research outputs
#2,241,215
of 25,374,917 outputs
Outputs from Drug Design, Development and Therapy
#113
of 2,268 outputs
Outputs of similar age
#18,811
of 210,078 outputs
Outputs of similar age from Drug Design, Development and Therapy
#2
of 43 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,268 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.1. This one has done particularly well, scoring higher than 95% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 210,078 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 43 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.