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The Oncopig Cancer Model as a Complementary Tool for Phenotypic Drug Discovery

Overview of attention for article published in Frontiers in Pharmacology, December 2017
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  • Good Attention Score compared to outputs of the same age and source (71st percentile)

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Title
The Oncopig Cancer Model as a Complementary Tool for Phenotypic Drug Discovery
Published in
Frontiers in Pharmacology, December 2017
DOI 10.3389/fphar.2017.00894
Pubmed ID
Authors

Natalia V. Segatto, Mariana H. Remião, Kyle M. Schachtschneider, Fabiana K. Seixas, Lawrence B. Schook, Tiago Collares

Abstract

The screening of potential therapeutic compounds using phenotypic drug discovery (PDD) is being embraced once again by researchers and pharmaceutical companies as an approach to enhance the development of new effective therapeutics. Before the genomics and molecular biology era and the consecutive emergence of targeted-drug discovery approaches, PDD was the most common platform used for drug discovery. PDD, also known as phenotypic screening, consists of screening potential compounds in either in vitro cellular or in vivo animal models to identify compounds resulting in a desirable phenotypic change. Using this approach, the biological targets of the compounds are not taken into consideration. Suitable animal models are crucial for the continued validation and discovery of new drugs, as compounds displaying promising results in phenotypic in vitro cell-based and in vivo small animal model screenings often fail in clinical trials. Indeed, this is mainly a result of differential anatomy, physiology, metabolism, immunology, and genetics between humans and currently used pre-clinical small animal models. In contrast, pigs are more predictive of therapeutic treatment outcomes in humans than rodents. In addition, pigs provide an ideal platform to study cancer due to their similarities with humans at the anatomical, physiological, metabolic, and genetic levels. Here we provide a mini-review on the reemergence of PDD in drug development, highlighting the potential of porcine cancer models for improving pre-clinical drug discovery and testing. We also present precision medicine based genetically defined swine cancer models developed to date and their potential as biomedical models.

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 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 29 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 14%
Professor 4 14%
Student > Bachelor 3 10%
Student > Ph. D. Student 3 10%
Student > Master 3 10%
Other 6 21%
Unknown 6 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 9 31%
Medicine and Dentistry 4 14%
Agricultural and Biological Sciences 2 7%
Pharmacology, Toxicology and Pharmaceutical Science 1 3%
Psychology 1 3%
Other 1 3%
Unknown 11 38%
Attention Score in Context

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 27 November 2018.
All research outputs
#13,574,541
of 23,009,818 outputs
Outputs from Frontiers in Pharmacology
#4,142
of 16,315 outputs
Outputs of similar age
#216,796
of 439,575 outputs
Outputs of similar age from Frontiers in Pharmacology
#73
of 259 outputs
Altmetric has tracked 23,009,818 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 16,315 research outputs from this source. They receive a mean Attention Score of 5.0. This one has gotten more attention than average, scoring higher than 73% 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 439,575 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 259 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.