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Big Data in Pharmaceutical R

Overview of attention for article published in Pharmaceutical Medicine, March 2015
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About this Attention Score

  • Among the highest-scoring outputs from this source (#45 of 144)
  • Good Attention Score compared to outputs of the same age (68th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (60th percentile)

Mentioned by

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5 X users

Citations

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28 Dimensions

Readers on

mendeley
106 Mendeley
citeulike
1 CiteULike
Title
Big Data in Pharmaceutical R&D: Creating a Sustainable R&D Engine
Published in
Pharmaceutical Medicine, March 2015
DOI 10.1007/s40290-015-0090-x
Pubmed ID
Authors

Peter Tormay

Abstract

Over the last 20 years, productivity in the pharmaceutical industry has been diminishing because of constantly increasing costs while output has overall been stagnant. Despite many efforts, productivity remains a challenge within the industry. At the same time, healthcare providers quite rightly require better value for money and clear evidence that new drugs are better than the current standard of care, making a complex situation even more complex. With the implementation of 'Big Data' initiatives trying to integrate data from disparate data sources and disciplines that are available in life science, the industry has identified a new frontier that might provide the insights needed to turn the ship around and allow the industry to return to sustainable growth.

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 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 106 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
United States 1 <1%
Canada 1 <1%
Unknown 103 97%

Demographic breakdown

Readers by professional status Count As %
Student > Master 24 23%
Researcher 16 15%
Student > Bachelor 13 12%
Student > Ph. D. Student 11 10%
Student > Doctoral Student 5 5%
Other 14 13%
Unknown 23 22%
Readers by discipline Count As %
Computer Science 16 15%
Business, Management and Accounting 11 10%
Engineering 10 9%
Medicine and Dentistry 10 9%
Biochemistry, Genetics and Molecular Biology 9 8%
Other 21 20%
Unknown 29 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 28 April 2015.
All research outputs
#6,931,653
of 22,800,560 outputs
Outputs from Pharmaceutical Medicine
#45
of 144 outputs
Outputs of similar age
#81,545
of 262,851 outputs
Outputs of similar age from Pharmaceutical Medicine
#2
of 5 outputs
Altmetric has tracked 22,800,560 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 144 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.0. This one has gotten more attention than average, scoring higher than 68% 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 262,851 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.