Safety pharmacology methods: Anticipating the transition from long QT (LQTS) to short QT syndromes (SQTS)?

hERG agonists pose challenges to web-based machine learning methods for prediction of drug-hERG channel interaction

Pharmacological blockade of the IKr channel (hERG) by diverse drugs in clinical use is associated with the Long QT Syndrome that can lead to life threatening arrhythmia. Various computational tools including machine learning models (MLM) for the prediction of hERG inhibition have been developed to facilitate the throughput screening of drugs in development and optimise thus the prediction of hERG liabilities. The use of MLM relies on large libraries of training compounds for the quantitative structure-activity relationship (QSAR) modelling of hERG inhibition. The focus on inhibition omits potential effects of hERG channel agonist molecules and their associated QT shortening risk. It is instructive, therefore, to consider how known hERG agonists are handled by MLM. Here, two highly developed online computational tools for the prediction of hERG liability, Pred-hERG and HergSPred were probed for their ability to detect hERG activator drug molecules as hERG interactors. In total, 73 hERG blockers were tested with both computational tools giving overall good predictions for hERG blockers with reported IC50s below Pred-hERG and HergSPred cut-off threshold for hERG inhibition. However, for compounds with reported IC50s above this threshold such as disopyramide or sotalol discrepancies were observed. HergSPred identified all 20 hERG agonists selected as interacting with the hERG channel. Further studies are warranted to improve online MLM prediction of hERG related cardiotoxicity, by explicitly taking into account channel agonism as well as inhibition.

Core battery safety pharmacology testing - An assessment of its utility in early drug development

Requirements for safety pharmacology testing have been in place since the issue of initial regulatory guidance over 20 years ago. An evaluation of such testing, supporting first clinical entry of 105 small molecule drug candidates over the last decade, showed that a "core battery" of in vitro electrophysiological (hERG), conscious non-rodent telemetry cardiovascular, rodent central nervous system (CNS) (modified Irwin's or functional observational battery [FOB] test) and respiratory function (plethysmography) studies was performed. Routine use of the latter 2 studies appears to have limited utility, with only 21% and 28% of studies, respectively, giving findings of which none were identified as of obvious concern to moving the affected drugs into the clinic. The use of a stand-alone hERG assay does not appear to be particular sensitive in predicting proarrythmic risk as a tool by itself. Telemetry study testing had utility especially for identifying effects on QTc interval (about 10% of studies), resulting on some occasions in a lower clinical starting dose and/or increased awareness for potential effects on the cardiovascular system in the Phase I study. Overall, this investigation provides information supporting an overhaul of the current "box ticking" core battery approach used for safety pharmacology testing. However, in order to achieve a more focused examination to investigate potential undesirable pharmacodynamic effects of a new candidate drug and also support 3Rs (Replacement, Reduction and Refinement) thinking in performing unnecessary studies, there will not only need to be a sea change by drug developers but also a change in current regulatory guidance.