Prediction of drug-related cardiac adverse effects in humans--A: creation of a database of effects and identification of factors affecting their occurrence.

This is the first of two reports that describes the compilation of a database of drug-related cardiac adverse effects (AEs) that was used to construct quantitative structure-activity relationship (QSAR) models to predict these AEs, to identify properties of pharmaceuticals correlated with the AEs, and to identify plausible mechanisms of action (MOAs) causing the AEs. This database of 396,985 cardiac AE reports was linked to 1632 approved drugs and their chemical structures, 1851 clinical indications (CIs), 997 therapeutic targets (TTs), 432 pharmacological MOAs, and 21,180 affinity coefficients (ACs) for the MOA receptors. AEs were obtained from the Food and Drug Administration's (FDA's) Spontaneous Reporting System (SRS) and Adverse Event Reporting System (AERS) and publicly available medical literature. Drug TTs were obtained from Integrity; drug MOAs and ACs were predicted by BioEpisteme. Significant cardiac AEs and patient exposures were estimated based on the proportional reporting ratios (PRRs) for each drug and each AE endpoint as a percentage of the total AEs. Cardiac AE endpoints were bundled based on toxicological mechanism and concordance of drug-related findings. Results revealed that significant cardiac AEs formed 9 clusters affecting Purkinje nerve fibers (arrhythmia, bradycardia, conduction disorder, electrocardiogram, palpitations, QT prolongation, rate rhythm composite, tachycardia, and Torsades de pointes), and 5 clusters affecting the heart muscle (coronary artery disorders, heart failure, myocardial disorders, myocardial infarction, and valve disorders). Based on the observation that each drug had one TT and up to 9 off-target MOAs, cardiac AEs were highly correlated with drugs affecting cardiovascular and cardioneurological functions and certain MOAs (e.g., alpha- and beta-adeno, dopamine, and hydroxytryptomine receptors).