Anna Sher

Simulation of multiple ion channel block provides improved early prediction of compounds' clinical torsadogenic risk

Aims The level of inhibition of the human Ether-à-go-go-related gene (hERG) channel is one of the earliest preclinical markers used to predict the risk of a compound causing Torsade-de-Pointes (TdP) arrhythmias. While avoiding the use of drugs with maximum therapeutic concentrations within 30-fold of their hERG inhibitory concentration 50% (IC50) values has been suggested, there are drugs that are exceptions to this rule: hERG inhibitors that do not cause TdP, and drugs that can cause TdP but are not strong hERG inhibitors. In this study, we investigate whether a simulated evaluation of multi-channel effects could be used to improve this early prediction of TdP risk. Methods and results We collected multiple ion channel data (hERG, Na, l-type Ca) on 31 drugs associated with varied risks of TdP. To integrate the information on multi-channel block, we have performed simulations with a variety of mathematical models of cardiac cells (for rabbit, dog, and human ventricular myocyte models). Drug action is modelled using IC50 values, and therapeutic drug concentrations to calculate the proportion of blocked channels and the channel conductances are modified accordingly. Various pacing protocols are simulated, and classification analysis is performed to evaluate the predictive power of the models for TdP risk. We find that simulation of action potential duration prolongation, at therapeutic concentrations, provides improved prediction of the TdP risk associated with a compound, above that provided by existing markers. Conclusion The suggested calculations improve the reliability of early cardiac safety assessments, beyond those based solely on a hERG block effect.

Multistability property in cardiac ionic models of mammalian and human ventricular cells

The underlying mechanisms of irregular cardiac rhythms are still poorly understood. Many experimental and modeling studies are aimed at identifying factors which cause cardiac arrhythmias. However, a lack of understanding of heart rhythm dynamical properties makes it difficult to uncover precise mechanisms of electrical instabilities, and hence to predict the onset of heart rhythm disorders. We review and compare the existing methods of studying cardiac dynamics, including restitution protocol (S1-S2), dynamic restitution protocol and multistability test protocol (S1-CI-S2). We focus on cardiac cell dynamics to elucidate regularities of heart rhythm. We demonstrate the advantages of our newly proposed systematic approach of analysis of cardiac cell dynamics using mammalian Luo Rudy 1991 and human ventricular Ten Tusscher 2006 single cell models under healthy and diseased conditions such as altered K(+) or Ca(2+) related currents. We investigate the role of ionic properties and the shape of an action potential on the nonlinear dynamics of electrical processes in periodically stimulated cardiac cells. We show the existence of multistability property for human ventricular cells. Moreover, the multistability is proposed to be an intrinsic property of cardiac cells, and is also suggested to be one of the mechanisms which could underlie the sudden triggering of life-threatening ventricular arrhythmias in the human heart.

High-throughput cardiac science on the Grid

Cardiac electrophysiology is a mature discipline, with the first model of a cardiac cell action potential having been developed in 1962. Current models range from single ion channels, through very complex models of individual cardiac cells, to geometrically and anatomically detailed models of the electrical activity in whole ventricles. A critical issue for model developers is how to choose parameters that allow the model to faithfully reproduce observed physiological effects without over-fitting. In this paper, we discuss the use of a parametric modelling toolkit, called Nimrod, that makes it possible both to explore model behaviour as parameters are changed and also to tune parameters by optimizing model output. Importantly, Nimrod leverages computers on the Grid, accelerating experiments by using available high-performance platforms. We illustrate the use of Nimrod with two case studies, one at the cardiac tissue level and one at the cellular level.

Functional significance of Na+/Ca2+ exchangers co-localization with ryanodine receptors.

Abstract:  Co‐localization of Na+/Ca2+ exchangers (NCX) with ryanodine receptors (RyRs) is debated. We incorporate local NCX current in a biophysically detailed model of L‐type Ca2+ channels (LCCs) and RyRs and study the effect of NCX on the regulation of Ca2+‐induced Ca2+ release and the shape of the action potential. In canine ventricular cells, under pathological conditions, e.g., impaired LCCs, local NCXs become an enhancer of sarcoplasmic reticulum release. Under such conditions incorporation of local NCXs is critical to accurately capture mechanisms of excitation–contraction coupling.

Incorporating Local Ca2 + Dynamics into Single Cell Ventricular Models

Understanding physiological mechanisms underlying the activity of the heart is of great medical importance. Mathematical modeling and numerical simulation have become a widely accepted method of unraveling the underlying mechanism of the heart. Calcium (Ca2 +) dynamics regulate the excitation-contraction coupling in heart muscle cells and hence are among the key players in maintaining normal activity of the heart. Many existing ventricular single cell models lack the biophysically detailed description of the Ca2 +dynamics. In this paper we examine how we can improve existing ventricular cell models by replacing their description of Ca2 +dynamics with the local Ca2 +control models. When replacing the existing Ca2 +dynamics in a given cell model with a different Ca2 +description, the parameters of the Ca2 +subsystem need to be re-fitted. Moreover, the search through the plausible parameter space is computationally very intensive. Thus, the Grid enabled Nimrod/O software tools are used for optimizing the cell parameters. Nimrod/O provides a convenient, user-friendly framework for this as exemplified by the incorporation of local Ca2 +dynamics into the ventricular single cell Noble 1998 model.

A Local Sensitivity Analysis Method for Developing Biological Models with Identifiable Parameters: Application to L-type Calcium Channel Modelling

Computational cardiac models provide important insights into the underlying mechanisms of heart function. Parameter estimation in these models is an ongoing challenge with many existing models being overparameterised. Sensitivity analysis presents a key tool for exploring the parameter identifiability. While existing methods provide insight into the significance of the parameters, they are unable to identify redundant parameters in an efficient manner. We present a new singular value decomposition based algorithm for determining parameter identifiability in cardiac models. Using this local sensitivity approach, we investigate the Mahajan 2008 rabbit ventricular myocyte L-type calcium current model. We identify non-significant and redundant parameters and improve the Ical model by reducing it to a minimum one that is validated to have only identifiable parameters. The newly proposed approach provides a new method for model validation and evaluation of the predictive power of cardiac models.

A global sensitivity tool for cardiac cell modeling: Application to ionic current balance and hypertrophic signaling

Cardiovascular diseases are the major cause of death in the developed countries. Identifying key cellular processes involved in generation of the electrical signal and in regulation of signal transduction pathways is essential for unraveling the underlying mechanisms of heart rhythm behavior. Computational cardiac models provide important insights into cardiovascular function and disease. Sensitivity analysis presents a key tool for exploring the large parameter space of such models, in order to determine the key factors determining and controlling the underlying physiological processes. We developed a new global sensitivity analysis tool which implements the Morris method, a global sensitivity screening algorithm, onto a Nimrod platform, which is a distributed resources software toolkit. The newly developed tool has been validated using the model of IP3-calcineurin signal transduction pathway model which has 30 parameters. The key driving factors of the IP3 transient behaviour have been calculated and confirmed to agree with previously published data. We next demonstrated the use of this method as an assessment tool for characterizing the structure of cardiac ionic models. In three latest human ventricular myocyte models, we examined the contribution of transmembrane currents to the shape of the electrical signal (i.e. on the action potential duration). The resulting profiles of the ionic current balance demonstrated the highly nonlinear nature of cardiac ionic models and identified key players in different models. Such profiling suggests new avenues for development of methodologies to predict drug action effects in cardiac cells.