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Drug repositioning for personalized medicine

Overview of attention for article published in Genome Medicine, March 2012
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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 (95th percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

news
2 news outlets
blogs
1 blog
twitter
4 X users
googleplus
1 Google+ user

Citations

dimensions_citation
192 Dimensions

Readers on

mendeley
348 Mendeley
citeulike
2 CiteULike
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Title
Drug repositioning for personalized medicine
Published in
Genome Medicine, March 2012
DOI 10.1186/gm326
Pubmed ID
Authors

Yvonne Y Li, Steven JM Jones

Abstract

Human diseases can be caused by complex mechanisms involving aberrations in numerous proteins and pathways. With recent advances in genomics, elucidating the molecular basis of disease on a personalized level has become an attainable goal. In many cases, relevant molecular targets will be identified for which approved drugs already exist, and the potential repositioning of these drugs to a new indication can be investigated. Repositioning is an accelerated route for drug discovery because existing drugs have established clinical and pharmacokinetic data. Personalized medicine and repositioning both aim to improve the productivity of current drug discovery pipelines, which expend enormous time and cost to develop new drugs, only to have them fail in clinical trials because of lack of efficacy or toxicity. Here, we discuss the current state of research in these two fields, focusing on recent large-scale efforts to systematically find repositioning candidates and elucidate individual disease mechanisms in cancer. We also discuss scenarios in which personalized drug repositioning could be particularly rewarding, such as for diseases that are rare or have specific mutations, as well as current challenges in this field. With an increasing number of drugs being approved for rare cancer subtypes, personalized medicine and repositioning approaches are poised to significantly alter the way we diagnose diseases, infer treatments and develop new drugs.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users 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 348 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 1%
Brazil 3 <1%
France 2 <1%
Germany 2 <1%
United Kingdom 2 <1%
Netherlands 1 <1%
Pakistan 1 <1%
Switzerland 1 <1%
Spain 1 <1%
Other 1 <1%
Unknown 329 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 64 18%
Student > Ph. D. Student 51 15%
Student > Master 51 15%
Student > Bachelor 50 14%
Student > Postgraduate 15 4%
Other 50 14%
Unknown 67 19%
Readers by discipline Count As %
Agricultural and Biological Sciences 51 15%
Biochemistry, Genetics and Molecular Biology 45 13%
Medicine and Dentistry 45 13%
Pharmacology, Toxicology and Pharmaceutical Science 31 9%
Computer Science 27 8%
Other 68 20%
Unknown 81 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 29. 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 15 March 2022.
All research outputs
#1,367,251
of 25,826,146 outputs
Outputs from Genome Medicine
#278
of 1,618 outputs
Outputs of similar age
#7,004
of 173,545 outputs
Outputs of similar age from Genome Medicine
#2
of 25 outputs
Altmetric has tracked 25,826,146 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,618 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.5. This one has done well, scoring higher than 82% 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 173,545 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 95% of its contemporaries.
We're also able to compare this research output to 25 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 92% of its contemporaries.