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Human In Silico Drug Trials Demonstrate Higher Accuracy than Animal Models in Predicting Clinical Pro-Arrhythmic Cardiotoxicity

Overview of attention for article published in Frontiers in Physiology, September 2017
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

news
28 news outlets
blogs
5 blogs
twitter
28 X users
facebook
5 Facebook pages
wikipedia
1 Wikipedia page

Citations

dimensions_citation
234 Dimensions

Readers on

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266 Mendeley
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Title
Human In Silico Drug Trials Demonstrate Higher Accuracy than Animal Models in Predicting Clinical Pro-Arrhythmic Cardiotoxicity
Published in
Frontiers in Physiology, September 2017
DOI 10.3389/fphys.2017.00668
Pubmed ID
Authors

Elisa Passini, Oliver J. Britton, Hua R. Lu, Jutta Rohrbacher, An N. Hermans, David J. Gallacher, Robert J. H. Greig, Alfonso Bueno-Orovio, Blanca Rodriguez

Abstract

Early prediction of cardiotoxicity is critical for drug development. Current animal models raise ethical and translational questions, and have limited accuracy in clinical risk prediction. Human-based computer models constitute a fast, cheap and potentially effective alternative to experimental assays, also facilitating translation to human. Key challenges include consideration of inter-cellular variability in drug responses and integration of computational and experimental methods in safety pharmacology. Our aim is to evaluate the ability of in silico drug trials in populations of human action potential (AP) models to predict clinical risk of drug-induced arrhythmias based on ion channel information, and to compare simulation results against experimental assays commonly used for drug testing. A control population of 1,213 human ventricular AP models in agreement with experimental recordings was constructed. In silico drug trials were performed for 62 reference compounds at multiple concentrations, using pore-block drug models (IC50/Hill coefficient). Drug-induced changes in AP biomarkers were quantified, together with occurrence of repolarization/depolarization abnormalities. Simulation results were used to predict clinical risk based on reports of Torsade de Pointes arrhythmias, and further evaluated in a subset of compounds through comparison with electrocardiograms from rabbit wedge preparations and Ca(2+)-transient recordings in human induced pluripotent stem cell-derived cardiomyocytes (hiPS-CMs). Drug-induced changes in silico vary in magnitude depending on the specific ionic profile of each model in the population, thus allowing to identify cell sub-populations at higher risk of developing abnormal AP phenotypes. Models with low repolarization reserve (increased Ca(2+)/late Na(+) currents and Na(+)/Ca(2+)-exchanger, reduced Na(+)/K(+)-pump) are highly vulnerable to drug-induced repolarization abnormalities, while those with reduced inward current density (fast/late Na(+) and Ca(2+) currents) exhibit high susceptibility to depolarization abnormalities. Repolarization abnormalities in silico predict clinical risk for all compounds with 89% accuracy. Drug-induced changes in biomarkers are in overall agreement across different assays: in silico AP duration changes reflect the ones observed in rabbit QT interval and hiPS-CMs Ca(2+)-transient, and simulated upstroke velocity captures variations in rabbit QRS complex. Our results demonstrate that human in silico drug trials constitute a powerful methodology for prediction of clinical pro-arrhythmic cardiotoxicity, ready for integration in the existing drug safety assessment pipelines.

X Demographics

X Demographics

The data shown below were collected from the profiles of 28 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 266 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 266 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 48 18%
Student > Ph. D. Student 38 14%
Student > Bachelor 33 12%
Student > Master 21 8%
Other 17 6%
Other 45 17%
Unknown 64 24%
Readers by discipline Count As %
Engineering 40 15%
Pharmacology, Toxicology and Pharmaceutical Science 27 10%
Biochemistry, Genetics and Molecular Biology 25 9%
Computer Science 21 8%
Agricultural and Biological Sciences 18 7%
Other 48 18%
Unknown 87 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 258. 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 07 July 2023.
All research outputs
#144,385
of 25,959,914 outputs
Outputs from Frontiers in Physiology
#80
of 15,726 outputs
Outputs of similar age
#3,091
of 327,083 outputs
Outputs of similar age from Frontiers in Physiology
#3
of 286 outputs
Altmetric has tracked 25,959,914 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 15,726 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one has done particularly well, scoring higher than 99% 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 327,083 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 99% of its contemporaries.
We're also able to compare this research output to 286 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 98% of its contemporaries.