Evidence map›Paper›PMID 25087753›Full record

ArticleJournal of pharmacological and toxicological methods

Prediction of Thorough QT study results using action potential simulations based on ion channel screens.

Gary R Mirams, Mark R Davies, Stephen J Brough, Matthew H Bridgland-Taylor, Yi Cui, David J Gavaghan, Najah Abi-Gerges

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Article in Journal of pharmacological and toxicological methods. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers.

0numbers the graph read from it
0cells of the map it votes in
54citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

54 citing papers in PubMed.

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  18. Calibration of ionic and cellular cardiac electrophysiology models.Wiley interdisciplinary reviews. Systems biology and medicine · 2020
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  19. When Does the ICJournal of chemical information and modeling · 2020
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  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Gary R MiramsComputational Biology, Dept. of Computer Science, University of Oxford, Oxford OX1 3QD, UK. Electronic address: gary.mirams@cs.ox.ac.uk.
Mark R DaviesClinical Informatics, R&D Information, AstraZeneca, Alderley Park, SK10 4TG, UK.
Stephen J BroughScreening & Compound Profiling, GlaxoSmithKline, Stevenage SG1 2NY, UK.
Matthew H Bridgland-TaylorDiscovery Sciences, AstraZeneca, Alderley Park, SK10 4TG, UK.
Yi CuiSafety Evaluation and Risk Management, Global Clinical Safety, GlaxoSmithKline, Middlesex UB11 1BT, UK.
David J GavaghanComputational Biology, Dept. of Computer Science, University of Oxford, Oxford OX1 3QD, UK.
Najah Abi-GergesTranslational Safety Department, Drug Safety & Metabolism, AstraZeneca, Alderley Park, SK10 4TG, UK.

Funding

National Centre for the Replacement, Refinement and Reduction of Animals in Research NC/K001337/1Wellcome Trust 101222Wellcome Trust 101222/Z/13/Z
6 · The paper itself

Abstract

introductionDetection of drug-induced pro-arrhythmic risk is a primary concern for pharmaceutical companies and regulators. Increased risk is linked to prolongation of the QT interval on the body surface ECG. Recent studies have shown that multiple ion channel interactions can be required to predict changes in ventricular repolarisation and therefore QT intervals. In this study we attempt to predict the result of the human clinical Thorough QT (TQT) study, using multiple ion channel screening which is available early in drug development.

methodsIon current reduction was measured, in the presence of marketed drugs which have had a TQT study, for channels encoded by hERG, CaV1.2, NaV1.5, KCNQ1/MinK, and Kv4.3/KChIP2.2. The screen was performed on two platforms - IonWorks Quattro (all 5 channels, 34 compounds), and IonWorks Barracuda (hERG & CaV1.2, 26 compounds). Concentration-effect curves were fitted to the resulting data, and used to calculate a percentage reduction in each current at a given concentration. Action potential simulations were then performed using the ten Tusscher and Panfilov (2006), Grandi et al. (2010) and O'Hara et al. (2011) human ventricular action potential models, pacing at 1Hz and running to steady state, for a range of concentrations.

resultsWe compared simulated action potential duration predictions with the QT prolongation observed in the TQT studies. At the estimated concentrations, simulations tended to underestimate any observed QT prolongation. When considering a wider range of concentrations, and conventional patch clamp rather than screening data for hERG, prolongation of ≥5ms was predicted with up to 79% sensitivity and 100% specificity. DISCUSSION: This study provides a proof-of-principle for the prediction of human TQT study results using data available early in drug development. We highlight a number of areas that need refinement to improve the method's predictive power, but the results suggest that such approaches will provide a useful tool in cardiac safety assessment.

Indexed as

Action PotentialsDose-Response Relationship, DrugDrug Evaluation, PreclinicalElectrocardiographyHumansIon ChannelsLong QT SyndromeIon ChannelsAction potentialCardiac safetyCompound screeningHigh-throughputMathematical modelMethodsThorough QT

Identifiers

PMID25087753
PMCPMC4266452

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.