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

https://doi.org/10.1016/j.vascn.2014.07.002Get rights and content
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Abstract

Introduction

Detection 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.

Methods

Ion 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 1 Hz and running to steady state, for a range of concentrations.

Results

We 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 ≥ 5 ms 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.

Abbreviations

AP(D)
action potential (duration)
AZ
AstraZeneca
B&Q2
IonWorks Barracuda and second Quattro screening dataset
GLP
good laboratory practice
GSK
GlaxoSmithKline
IC50
concentration for 50% inhibition
ICaL
long-lasting-type calcium current
IKr
rapid delayed rectifier potassium current
IKs
slow delayed rectifier potassium current
INa
fast sodium current
Ito
transient outward potassium current
M&Q
manual hERG plus IonWorks Quattro screening dataset
pIC50
minus log10 of IC50
Q
IonWorks Quattro screening dataset
QT[c]
QT interval of the electrocardiogram [corrected for heart rate]
TQT
Thorough QT (or ECG) study, a human clinical trial

Keywords

High-throughput
Compound screening
Thorough QT
Cardiac safety
Methods
Action potential
Mathematical model

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