Modeling and simulation of preclinical cardiac safety: towards an integrative framework

Despite an impressive battery of preclinical cardiac electrophysiology experimental models and the assessment of QT during clinical trials, the risk of Torsades de Pointes (TdP), a potentially lethal ventricular arrhythmia, remains among the common reasons for drug market withdrawal or lack of approval. Due to the low prevalence of TdP, development of statistical evidence that other clinical markers could be better predictors of TdP has proven challenging. Preclinical studies have provided a deeper understanding of torsadogenic mechanisms and potential pro-arrhythmic markers to assess. Translating these preclinical insights into a quantitative clinical risk assessment remains challenging because of (i) species differences in cardiac electrophysiology and drug pharmacokinetics; and (ii) the inability to measure clinically specific cardiac electrophysiology metrics, and therefore ascertain the full predictive value of earlier preclinical components of the risk assessment process. The integrative capacity of cardiac electrophysiology modeling to span time and length scales may provide a quantitative and predictive framework, to complement expert-based preclinical-to-clinical cardiac risk assessment process. In this review, we present salient elements of this risk assessment process and describe essential components of cardiac electrophysiology modeling, to propose that a progressive integration of mechanistic components into a common quantitative framework may help improve the predictability of drug-induced TdP risk.