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A multicenter assessment of single-cell models aligned to standard measures of cell health for prediction of acute hepatotoxicity

Overview of attention for article published in Archives of Toxicology, June 2016
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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 (82nd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (60th percentile)

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1 news outlet
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Citations

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124 Mendeley
Title
A multicenter assessment of single-cell models aligned to standard measures of cell health for prediction of acute hepatotoxicity
Published in
Archives of Toxicology, June 2016
DOI 10.1007/s00204-016-1745-4
Pubmed ID
Authors

Rowena L. Sison-Young, Volker M. Lauschke, Esther Johann, Eliane Alexandre, Sébastien Antherieu, Hélène Aerts, Helga H. J. Gerets, Gilles Labbe, Delphine Hoët, Martina Dorau, Christopher A. Schofield, Cerys A. Lovatt, Julie C. Holder, Simone H. Stahl, Lysiane Richert, Neil R. Kitteringham, Robert P. Jones, Mohamed Elmasry, Richard J. Weaver, Philip G. Hewitt, Magnus Ingelman-Sundberg, Chris E. Goldring, B. Kevin Park

Abstract

Assessing the potential of a new drug to cause drug-induced liver injury (DILI) is a challenge for the pharmaceutical industry. We therefore determined whether cell models currently used in safety assessment (HepG2, HepaRG, Upcyte and primary human hepatocytes in conjunction with basic but commonly used endpoints) are actually able to distinguish between novel chemical entities (NCEs) with respect to their potential to cause DILI. A panel of thirteen compounds (nine DILI implicated and four non-DILI implicated in man) were selected for our study, which was conducted, for the first time, across multiple laboratories. None of the cell models could distinguish faithfully between DILI and non-DILI compounds. Only when nominal in vitro concentrations were adjusted for in vivo exposure levels were primary human hepatocytes (PHH) found to be the most accurate cell model, closely followed by HepG2. From a practical perspective, this study revealed significant inter-laboratory variation in the response of PHH, HepG2 and Upcyte cells, but not HepaRG cells. This variation was also observed to be compound dependent. Interestingly, differences between donors (hepatocytes), clones (HepG2) and the effect of cryopreservation (HepaRG and hepatocytes) were less important than differences between the cell models per se. In summary, these results demonstrate that basic cell health endpoints will not predict hepatotoxic risk in simple hepatic cells in the absence of pharmacokinetic data and that a multicenter assessment of more sophisticated signals of molecular initiating events is required to determine whether these cells can be incorporated in early safety assessment.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 124 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 124 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 33 27%
Researcher 23 19%
Student > Bachelor 15 12%
Student > Master 12 10%
Student > Doctoral Student 5 4%
Other 10 8%
Unknown 26 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 32 26%
Pharmacology, Toxicology and Pharmaceutical Science 22 18%
Medicine and Dentistry 11 9%
Agricultural and Biological Sciences 9 7%
Engineering 9 7%
Other 16 13%
Unknown 25 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 13 February 2023.
All research outputs
#3,722,734
of 25,837,817 outputs
Outputs from Archives of Toxicology
#302
of 2,835 outputs
Outputs of similar age
#62,929
of 371,826 outputs
Outputs of similar age from Archives of Toxicology
#17
of 43 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,835 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.9. This one has done well, scoring higher than 88% 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 371,826 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 82% of its contemporaries.
We're also able to compare this research output to 43 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 60% of its contemporaries.