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The human viral challenge model: accelerating the evaluation of respiratory antivirals, vaccines and novel diagnostics

Overview of attention for article published in Respiratory Research, June 2018
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

news
3 news outlets
blogs
1 blog
twitter
6 X users
wikipedia
7 Wikipedia pages

Citations

dimensions_citation
47 Dimensions

Readers on

mendeley
106 Mendeley
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Title
The human viral challenge model: accelerating the evaluation of respiratory antivirals, vaccines and novel diagnostics
Published in
Respiratory Research, June 2018
DOI 10.1186/s12931-018-0784-1
Pubmed ID
Authors

Rob Lambkin-Williams, Nicolas Noulin, Alex Mann, Andrew Catchpole, Anthony S. Gilbert

Abstract

The Human Viral Challenge (HVC) model has, for many decades, helped in the understanding of respiratory viruses and their role in disease pathogenesis. In a controlled setting using small numbers of volunteers removed from community exposure to other infections, this experimental model enables proof of concept work to be undertaken on novel therapeutics, including vaccines, immunomodulators and antivirals, as well as new diagnostics.Crucially, unlike conventional phase 1 studies, challenge studies include evaluable efficacy endpoints that then guide decisions on how to optimise subsequent field studies, as recommended by the FDA and thus licensing studies that follow. Such a strategy optimises the benefit of the studies and identifies possible threats early on, minimising the risk to subsequent volunteers but also maximising the benefit of scarce resources available to the research group investing in the research. Inspired by the principles of the 3Rs (Replacement, Reduction and Refinement) now commonly applied in the preclinical phase, HVC studies allow refinement and reduction of the subsequent development phase, accelerating progress towards further statistically powered phase 2b studies. The breadth of data generated from challenge studies allows for exploration of a wide range of variables and endpoints that can then be taken through to pivotal phase 3 studies.We describe the disease burden for acute respiratory viral infections for which current conventional development strategies have failed to produce therapeutics that meet clinical need. The Authors describe the HVC model's utility in increasing scientific understanding and in progressing promising therapeutics through development.The contribution of the model to the elucidation of the virus-host interaction, both regarding viral pathogenicity and the body's immunological response is discussed, along with its utility to assist in the development of novel diagnostics.Future applications of the model are also explored.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 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 %
Unknown 106 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 22 21%
Student > Master 11 10%
Student > Ph. D. Student 10 9%
Other 8 8%
Student > Bachelor 7 7%
Other 15 14%
Unknown 33 31%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 15 14%
Medicine and Dentistry 15 14%
Pharmacology, Toxicology and Pharmaceutical Science 9 8%
Immunology and Microbiology 8 8%
Agricultural and Biological Sciences 5 5%
Other 13 12%
Unknown 41 39%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 37. 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 24 November 2022.
All research outputs
#1,105,177
of 25,385,509 outputs
Outputs from Respiratory Research
#76
of 3,062 outputs
Outputs of similar age
#23,783
of 342,290 outputs
Outputs of similar age from Respiratory Research
#2
of 68 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,062 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.9. This one has done particularly well, scoring higher than 97% 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 342,290 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 93% of its contemporaries.
We're also able to compare this research output to 68 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 97% of its contemporaries.