Preclinical cardiac safety assessment of pharmaceutical compounds using an integrated systems-based computer model of the heart.

Blockade of the delayed rectifier potassium channel current, I(Kr), has been associated with drug-induced QT prolongation in the electrocardiogram and life-threatening cardiac arrhythmias. However, it is increasingly clear that compound-induced interactions with multiple cardiac ion channels may significantly affect QT prolongation that would result from inhibition of only I(Kr) [Redfern, W.S., Carlsson, L., et al., 2003. Relationships between preclinical cardiac electrophysiology, clinical QT interval prolongation and torsade de pointes for a broad range of drugs: evidence for a provisional safety margin in drug development. Cardiovasc. Res. 58(1), 32-45]. Such an assessment may not be feasible in vitro, due to multi-factorial processes that are also time-dependent and highly non-linear. Limited preclinical data, I(Kr) hERG assay and canine Purkinje fiber (PF) action potentials (APs) [Gintant, G.A., Limberis, J.T., McDermott, J.S., Wegner, C.D., Cox, B.F., 2001. The canine Purkinje fiber: an in vitro model system for acquired long QT syndrome and drug-induced arrhythmogenesis. J. Cardiovasc. Pharmacol. 37(5), 607-618], were used for two test compounds in a systems-based modeling platform of cardiac electrophysiology [Muzikant, A.L., Penland, R.C., 2002. Models for profiling the potential QT prolongation risk of drugs. Curr. Opin. Drug. Discov. Dev. 5(1), 127-35] to: (i) convert a canine myocyte model to a PF model by training functional current parameters to the AP data; (ii) reverse engineer the compounds' effects on five channel currents other than I(Kr), predicting significant IC(50) values for I(Na+), sustained and I(Ca2+), L-type , which were subsequently experimentally validated; (iii) use the predicted (I(Na+), sustained and I(Ca2+), L-type) and measured (I(Kr)) IC(50) values to simulate dose-dependent effects of the compounds on APs in endocardial, mid-myocardial, and epicardiac ventricular cells; and (iv) integrate the three types of cellular responses into a tissue-level spatial model, which quantifiably predicted no potential for the test compounds to induce either QT prolongation or increased transmural dispersion of repolarization in a dose-dependent and reverse rate-dependent fashion, despite their inhibition of I(Kr) in vitro.

Models for profiling the potential QT prolongation risk of drugs.

The appearance of QT prolongation and arrhythmic events associated with a compound undergoing clinical trials can greatly hamper drug development programs. Assessing the risk of a compound during preclinical studies to cause this cardiotoxicity is thus critically important to the pharmaceutical industry. A wide variety of preclinical approaches exist to evaluate potential QT issues, including in vitro, in vivo and in silico (i.e., computer simulation) methods. We present an evaluation of recent reports implementing these techniques, with an emphasis on the linkage between drug-induced cardiac action potential changes and QT prolongation both in vitro and in silico. We conclude with a strategy that integrates in silico modeling with in vitro and in vivo experimentation to create a compelling package for assessing potential proarrhythmic risk of a compound.

Using in silico biology to facilitate drug development.

G protein-coupled receptor (GPCR) mediation of cardiac excitability is often overlooked in predicting the likelihood that a compound will alter repolarization. While the areas of GPCR signal transduction and electrophysiology are rich in data, experiments combining the two are difficult. In silico modelling facilitates the integration of all relevant data in both areas to explore the hypothesis that critical associations may exist between the different GPCR signalling mechanisms and cardiac excitability and repolarization. An example of this linkage is suggested by the observation that a mutation of the gene encoding HERG, the pore-forming subunit of the rapidly activating delayed rectifier K+ current (I(Kr)), leads to a form of long QT syndrome in which affected individuals are vulnerable to stress-induced arrhythmia following beta-adrenergic stimulation. Using Physiome's In Silico Cell, we constructed a model integrating the signalling mechanisms of second messengers cAMP and protein kinase A with I(Kr) in a cardiac myocyte. We analysed the model to identify the second messengers that most strongly influence I(Kr) behaviour. Our conclusions indicate that the dynamics of regulation are multifactorial, and that Physiome's approach to in silico modelling helps elucidate the subtle control mechanisms at play.