In silico modeling demonstrates that quantitative profiling of transmural and rate-dependent properties, specifically the occurrence of EADs, provides better prediction of drug-induced arrhythmogenic risk than hERG inhibition or QT prolongation alone.
Supports EAD profiling over QT metrics in preclinical screening; leaves open clinical translation for torsadogenic risk prediction.
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 I NaL is the major depolarizing current during the generation of drug-induced EAD in P cells, I CaL 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.
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Zhao et al. (2019) studied this question.
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