Transmural and rate-dependent profiling of drug-induced arrhythmogenic risks through in silico simulations of multichannel pharmacology

Abstract

In vitro human ether-à-go-go related gene (hERG) inhibition assay alone might provide insufficient information to discriminate “safe” from “dangerous” drugs. Here, effects of multichannel inhibition on cardiac electrophysiology were investigated using a family of cardiac cell models (Purkinje (P), endocardial (Endo), mid-myocardial (M) and epicardial (Epi)). We found that: (1) QT prolongation alone might not necessarily lead to early afterdepolarization (EAD) events, and it might be insufficient to predict arrhythmogenic liability; (2) the occurrence and onset of EAD events could be a candidate biomarker of drug-induced arrhythmogenicity; (3) M cells are more vulnerable to drug-induced arrhythmias, and can develop early afterdepolarization (EAD) at slower pacing rates; (4) the application of quinidine can cause EADs in all cell types, while INaL is the major depolarizing current during the generation of drug-induced EAD in P cells, ICaL is mostly responsible in other cell types; (5) drug-induced action potential (AP) alternans with beat-to-beat variations occur at high pacing rates in P cells. These results suggested that quantitative profiling of transmural and rate-dependent properties can be essential to evaluate drug-induced arrhythmogenic risks, and may provide mechanistic insights into drug-induced arrhythmias.

HPC framework for in-silico trials on 3D virtual human cardiac population to assess drug-induced arrhythmic risk

“…12. This was evidenced by heightened drug-induced transmural heterogeneities, as has been previously associated with multi-channel blocking drugs [47]. Enhanced transmural heterogeneities of focal APs provide an important arrhythmic risk, as observed in one of the subjects that presented an LBBB after the administration of 800 mg of HCQ.…”

Spatiotemporal patterns of early afterdepolarizations underlying abnormal T-wave morphologies in a tissue model of the Purkinje-ventricular system

“…At the Purkinje-ventricular junction (PVJ; Fig 1 ), an electric ratio factor (E R ) was introduced to phenomenologically account for asymmetrical electric and structural heterogeneities between the quasi-1D Purkinje fiber and the three-dimensional (3D) ventricular myocardium, where D Pv = E R *D v with E R = 3.13 to incur a PVJ conduction delay of 4.364ms that is consistent with earlier experimental findings [ 20 ]. I ion for different cell types (P, Endo, M and Epi) in our 1D PVS model were derived from previously published canine Purkinje [ 4 ] and ventricular [ 21 ] cell models based on experimental measurements of transmural electrophysiological heterogeneities in I NaL , I to1 , I Ks and I NaCa [ 22 ]. These models were developed to quantitatively represent key characteristics of intracellular Ca 2+ cycling and membrane ionic currents specific to each cell type using similar modeling and validation approaches [ 4 , 21 ].…”

Spatiotemporal Patterns of Early Afterdepolarizations Underlying Abnormal T-Wave Morphologies in a Tissue Model of the Purkinje-Ventricular System

“…A one-dimensional (1D) computer model of the canine PVS (~ 2 cm in length) was developed by electrically coupling mathematical models of Purkinje (P), endocardial (Endo), M and Epi cells [4,19] via gap junctions [20] (see the model schematic in Figure S1), and an electric ratio (ER) factor was introduced to account for the asymmetrical electric properties of the Purkinje-ventricular junction (PVJ). During normal antegrade excitation, the conduction delay across the PVJ (~ 4 ms) and electric conduction velocities in each tissue type were validated according to earlier experimental measurements [21,22] .…”

“…During normal antegrade excitation, the conduction delay across the PVJ (~ 4 ms) and electric conduction velocities in each tissue type were validated according to earlier experimental measurements [21,22] . Canine cardiac cell models (P, Endo, M and Epi) were derived from previously published Purkinje [4] and ventricular [23] cell models based on experimental measurements of intrinsic electrophysiological heterogeneities [19] . These models were developed to quantitatively represent key characteristics of intracellular Ca 2+ cycling and membrane ionic currents speci c to each cell type using similar modeling and validation approaches [4,23] .…”

“…These models were developed to quantitatively represent key characteristics of intracellular Ca 2+ cycling and membrane ionic currents speci c to each cell type using similar modeling and validation approaches [4,23] . Extracellular unipolar potentials (as pseudo ECG signals) were computed at a site 2.0 cm away from the epicardium along the strand axis [19] . Standard programming language C was used.…”