Uncertainty quantification reveals the importance of data variability and experimental design considerations for in silico proarrhythmia risk assessment

The Comprehensive in vitro Proarrhythmia Assay (CiPA) is a global initiative intended to improve drug proarrhythmia risk assessment using a new paradigm of mechanistic assays. Under the CiPA paradigm, the relative risk of drug-induced Torsade de Pointes (TdP) is assessed using an in silico model of the human ventricular action potential (AP) that integrates in vitro pharmacology data from multiple ion channels. Thus, modeling predictions of cardiac risk liability will depend critically on the variability in pharmacology data, and uncertainty quantification (UQ) must comprise an essential component of the in silico assay. This study explores UQ methods that may be incorporated into the CiPA framework. Recently, we proposed a promising in silico TdP risk metric (qNet), which is derived from AP simulations and allows separation of a set of CiPA training compounds into Low, Intermediate, and High TdP risk categories. The purpose of this study was to use UQ to evaluate the robustness of TdP risk separation by qNet. Uncertainty in the model parameters used to describe drug binding and ionic current block was estimated using the non-parametric bootstrap method and a Bayesian inference approach. Uncertainty was then propagated through AP simulations to quantify uncertainty in qNet for each drug. UQ revealed lower uncertainty and more accurate TdP risk stratification by qNet when simulations were run at concentrations below 5× the maximum therapeutic exposure (Cmax). However, when drug effects were extrapolated above 10× Cmax, UQ showed that qNet could no longer clearly separate drugs by TdP risk. This was because for most of the pharmacology data, the amount of current block measured was <60%, preventing reliable estimation of IC50-values. The results of this study demonstrate that the accuracy of TdP risk prediction depends both on the intrinsic variability in ion channel pharmacology data as well as on experimental design considerations that preclude an accurate determination of drug IC50-values in vitro. Thus, we demonstrate that UQ provides valuable information about in silico modeling predictions that can inform future proarrhythmic risk evaluation of drugs under the CiPA paradigm

Nonclinical cardiovascular safety of pitolisant: comparing International Conference on Harmonization S7B and Comprehensive in vitro Pro-arrhythmia Assay initiative studies

Background and purpose: We evaluated the concordance of results from two sets of nonclinical cardiovascular safety studies on pitolisant. Experimental approach: Nonclinical studies envisaged both in the ICH S7B guideline and Comprehensive in vitro Proarrhythmia Assay (CiPA) initiative were undertaken. CiPA-initiative studies included in vitro ion channels and stem cell-derived human ventricular myocyte studies as well as in silico modelling of results to simulate human ventricular electrophysiology. ICH S7B-recommended studies included in vitro hERG studies, in vivo dog study with follow-up investigations in rabbit Purkinje fibres and in vivo studies in the Carlsson rabbit proarrhythmia model. Key results: Both sets of nonclinical studies consistently excluded pitolisant from having clinically relevant QT-liability or proarrhythmic potential. CiPA studies revealed pitolisant to have modest calcium channel blocking and late I Na reducing activities at high concentrations, which resulted in reduction of dofetilide-induced early after-depolarisations (EADs) by pitolisantin ICH S7B studies. Studies in stem cell-derived human cardiomyocytes with dofetilide or E-4031 given alone and in combination with pitolisant confirmed these properties. In silico modelling confirmed that the measured ion channel effects are consistent with results from both the stem cell-derived cardiomyocyte and rabbit Purkinje fibre studies and categorised pitolisant as a drug with low torsadogenic potential. The results from the two sets of nonclinical studies correlated well with two clinical QT studies. Conclusions and implications: Our experience supports the CiPA initiative but suggests that sponsors should consider investigating drug effects on EADs and the use of proarrhythmia models when the results from CiPA studies are ambiguous

UK-68,798, A Class III Antiarrhythmic Drug with Antifibrillatory Properties

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74787/1/j.1527-3466.1992.tb00244.x.pd

Re-Evaluation of the Action Potential Upstroke Velocity as a Measure of the Na+ Current in Cardiac Myocytes at Physiological Conditions

Background: The SCN5A encoded sodium current (INa) generates the action potential (AP) upstroke and is a major determinant of AP characteristics and AP propagation in cardiac myocytes. Unfortunately, in cardiac myocytes, investigation of kinetic properties of INa with near-physiological ion concentrations and temperature is technically challenging due to the large amplitude and rapidly activating nature of INa, which may seriously hamper the quality of voltage control over the membrane. We hypothesized that the alternating voltage clamp-current clamp (VC/CC) technique might provide an alternative to traditional voltage clamp (VC) technique for the determination of INa properties under physiological conditions. Principal Findings: We studied INa under close-to-physiological conditions by VC technique in SCN5A cDNA-transfected HEK cells or by alternating VC/CC technique in both SCN5A cDNA-transfected HEK cells and rabbit left ventricular myocytes. In these experiments, peak INa during a depolarizing VC step or maximal upstroke velocity, dV/dtmax, during VC/CC served as an indicator of available INa. In HEK cells, biophysical properties of INa, including current density, voltage dependent (in)activation, development of inactivation, and recovery from inactivation, were highly similar in VC and VC/CC experiments. As an application of the VC/CC technique we studied INa in left ventricular myocytes isolated from control or failing rabbit hearts

Calibration of ionic and cellular cardiac electrophysiology models

© 2020 The Authors. WIREs Systems Biology and Medicine published by Wiley Periodicals, Inc. Cardiac electrophysiology models are among the most mature and well-studied mathematical models of biological systems. This maturity is bringing new challenges as models are being used increasingly to make quantitative rather than qualitative predictions. As such, calibrating the parameters within ion current and action potential (AP) models to experimental data sets is a crucial step in constructing a predictive model. This review highlights some of the fundamental concepts in cardiac model calibration and is intended to be readily understood by computational and mathematical modelers working in other fields of biology. We discuss the classic and latest approaches to calibration in the electrophysiology field, at both the ion channel and cellular AP scales. We end with a discussion of the many challenges that work to date has raised and the need for reproducible descriptions of the calibration process to enable models to be recalibrated to new data sets and built upon for new studies. This article is categorized under: Analytical and Computational Methods > Computational Methods Physiology > Mammalian Physiology in Health and Disease Models of Systems Properties and Processes > Cellular Models

Have the Findings from Clinical Risk Prediction and Trials Any Key Messages for Safety Pharmacology?

Anti-arrhythmic drugs are a mainstay in the management of symptoms related to arrhythmias, and are adjuncts in prevention and treatment of life-threatening ventricular arrhythmias. However, they also have the potential for pro-arrhythmia and thus the prediction of arrhythmia predisposition and drug response are critical issues. Clinical trials are the latter stages in the safety testing and efficacy process prior to market release, and as such serve as a critical safeguard. In this review, we look at some of the lessons to be learned from approaches to arrhythmia prediction in patients, clinical trials of drugs used in the treatment of arrhythmias, and the implications for the design of pre-clinical safety pharmacology testing.This work was supported by the British Heart Foundation (FS/12/11/29289 and RG/15/15/31742 and facilitated by the NIHR Biomedical Research Centre at Barts