Model-driven optimal experimental design for calibrating cardiac electrophysiology models.

BACKGROUND AND OBJECTIVE: Models of the cardiomyocyte action potential have contributed immensely to the understanding of heart function, pathophysiology, and the origin of heart rhythm disturbances. However, action potential models are highly nonlinear, making them difficult to parameterise and limiting to describing 'average cell' dynamics, when cell-specific models would be ideal to uncover inter-cell variability but are too experimentally challenging to be achieved. Here, we focus on automatically designing experimental protocols that allow us to better identify cell-specific maximum conductance values for each major current type. METHODS AND RESULTS: We developed an approach that applies optimal experimental designs to patch-clamp experiments, including both voltage-clamp and current-clamp experiments. We assessed the models calibrated to these new optimal designs by comparing them to the models calibrated to some of the commonly used designs in the literature. We showed that optimal designs are not only overall shorter in duration but also able to perform better than many of the existing experiment designs in terms of identifying model parameters and hence model predictive power. CONCLUSIONS: For cardiac cellular electrophysiology, this approach will allow researchers to define their hypothesis of the dynamics of the system and automatically design experimental protocols that will result in theoretically optimal designs.

Assessment of an In Silico Mechanistic Model for Proarrhythmia Risk Prediction Under the CiPA Initiative.

The International Council on Harmonization (ICH) S7B and E14 regulatory guidelines are sensitive but not specific for predicting which drugs are pro-arrhythmic. In response, the Comprehensive In Vitro Proarrhythmia Assay (CiPA) was proposed that integrates multi-ion channel pharmacology data in vitro into a human cardiomyocyte model in silico for proarrhythmia risk assessment. Previously, we reported the model optimization and proarrhythmia metric selection based on CiPA training drugs. In this study, we report the application of the prespecified model and metric to independent CiPA validation drugs. Over two validation datasets, the CiPA model performance meets all pre-specified measures for ranking and classifying validation drugs, and outperforms alternatives, despite some in vitro data differences between the two datasets due to different experimental conditions and quality control procedures. This suggests that the current CiPA model/metric may be fit for regulatory use, and standardization of experimental protocols and quality control criteria could increase the model prediction accuracy even further.

A web portal for in-silico action potential predictions.

INTRODUCTION: Multiple cardiac ion channels are prone to block by pharmaceutical compounds, and this can have large implications for cardiac safety. The effect of a compound on individual ion currents can now be measured in automated patch clamp screening assays. In-silico action potential models are proposed as one way of predicting the integrated compound effects on whole-cell electrophysiology, to provide an improved indication of pro-arrhythmic risk. METHODS: We have developed open source software to run cardiac electrophysiology simulations to predict the overall effect of compounds that block IKr, ICaL, INa, IKs, IK1 and Ito to varying degrees, using a choice of mathematical electrophysiology models. To enable safety pharmacology teams to run and evaluate these simulations easily, we have also developed an open source web portal interface to this simulator. RESULTS: The web portal can be found at https://chaste.cs.ox.ac.uk/ActionPotential. Users can enter details of compound affinities for ion channels in the form of IC50 or pIC50 values, run simulations, store the results for later retrieval, view summary graphs of the results, and export data to a spreadsheet format. DISCUSSION: This web portal provides a simple interface to reference versions of mathematical models, and well-tested state-of-the-art equation solvers. It provides safety teams easy access to the emerging technology of cardiac electrophysiology simulations for use in the drug-discovery process.

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

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 1Hz 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 ≥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.

Application of cardiac electrophysiology simulations to pro-arrhythmic safety testing.

Concerns over cardiac side effects are the largest single cause of compound attrition during pharmaceutical drug development. For a number of years, biophysically detailed mathematical models of cardiac electrical activity have been used to explore how a compound, interfering with specific ion-channel function, may explain effects at the cell-, tissue- and organ-scales. With the advent of high-throughput screening of multiple ion channels in the wet-lab, and improvements in computational modelling of their effects on cardiac cell activity, more reliable prediction of pro-arrhythmic risk is becoming possible at the earliest stages of drug development. In this paper, we review the current use of biophysically detailed mathematical models of cardiac myocyte electrical activity in drug safety testing, and suggest future directions to employ the full potential of this approach.

Application of human stem cell-derived cardiomyocytes in safety pharmacology requires caution beyond hERG.

Human embryonic stem cell-derived cardiomyocytes (hESC-CM) have been proposed as a new model for safety pharmacology. So far, a thorough description of their basic electrophysiology and extensive testing, and mechanistic explanations, of their overall pro-arrhythmic ability is lacking. Under standardized conditions, we have evaluated the sensitivity of hESC-CM to proarrhythmic provocations by blockade of hERG and other channels. Using voltage patch clamp, some ion current densities (pA/pF) in hESC-CM were comparable to adult CM: I(Kr) (-12.5 ± 6.9), I(Ks) (0.65 ± 0.12), I(Na,peak) (-72 ± 21), I(Na,late) (-1.10 ± 0.36), and I(Ca,L) (-4.3 ± 0.6). I(f) density was larger (-10 ± 1.1) and I(K1) not existent or very small (-2.67 ± 0.3). The low I(K1) density was corroborated by low KCNJ2 mRNA levels. Effects of pro-arrhythmic compounds on action potential (AP) parameters and provocation of early afterdepolarizations (EADs) revealed that Chromanol293B (100 µmol/l) and Bay K8644 (1 µmol/l) both significantly prolonged APD(90). ATX-II (<1 µmol/l ) and BaCl(2) (10 µmol/l ) had no effect on APD. The only compound that triggered EADs was hERG blocker Cisapride. Computer simulations and AP clamp showed that the immature AP of hESC-CM prevents proper functioning of I(Na)-channels, and result in lower peak/maximal currents of several other channels, compared to the adult situation. Lack of functional I(K1) channels and shifted I(Na) channel activation cause a rather immature electrophysiological phenotype in hESC-CM, and thereby limits the potential of this model to respond accurately to pro-arrhythmic triggers other than hERG block. Maturation of the electrical phenotype is a prerequiste for future implementation of the model in arrhythmogenic safety testing.

Is it time for in silico simulation of drug cardiac side effects?

Cardiac simulation is used to integrate information on drug action to predict side effects on the whole heart. Could simulation begin to replace animal models?