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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Leveraging Big Data in Pediatric Development Programs: Proceedings From the 2016 American College of Clinical Pharmacology Annual Meeting Symposium
|
|---|---|
| Published in |
Clinical Pharmacology & Therapeutics, January 2018
|
| DOI | 10.1002/cpt.975 |
| Pubmed ID | |
| Authors |
Lily Mulugeta, Lynne Yao, Diane Mould, Brian Jacobs, Jeffrey Florian, Brian Smith, Vikram Sinha, Jeffrey S. Barrett |
| Abstract |
This article discusses the use of big data in pediatric drug development. The article covers key topics discussed at the ACCP annual meeting symposium in 2016 including the extent to which big data or real-world data can inform clinical trial design and substitute for efficacy and safety data typically obtained in clinical trials. The current states of use, opportunities, and challenges with the use of big data in future pediatric drug development are discussed. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 33% |
| France | 1 | 33% |
| United Kingdom | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 24 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 7 | 29% |
| Student > Ph. D. Student | 3 | 13% |
| Other | 2 | 8% |
| Student > Master | 2 | 8% |
| Student > Doctoral Student | 1 | 4% |
| Other | 4 | 17% |
| Unknown | 5 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Pharmacology, Toxicology and Pharmaceutical Science | 6 | 25% |
| Medicine and Dentistry | 3 | 13% |
| Biochemistry, Genetics and Molecular Biology | 2 | 8% |
| Computer Science | 2 | 8% |
| Environmental Science | 1 | 4% |
| Other | 3 | 13% |
| Unknown | 7 | 29% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 29 January 2018.
All research outputs
#16,075,712
of 24,458,924 outputs
Outputs from Clinical Pharmacology & Therapeutics
#3,449
of 4,370 outputs
Outputs of similar age
#266,996
of 452,658 outputs
Outputs of similar age from Clinical Pharmacology & Therapeutics
#48
of 69 outputs
Altmetric has tracked 24,458,924 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,370 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.8. This one is in the 19th percentile – i.e., 19% of its peers scored the same or lower than it.
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 452,658 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 69 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.