Use of high throughput ion channel profiling and statistical modeling to predict off-target arrhythmia risk - One pharma's experience and perspective

Introduction: The use of high throughput patch clamp profiling to determine mixed ion channel-mediated arrhythmia risk was assessed using profiling data generated using proprietary internal and clinical reference compounds. We define the reproducibility of the platform and highlight inherent platform issues. The data generated was used to develop predictive models for cardiac arrhythmia risk, specifically Torsades de Pointes (TdP).

Methods: A retrospective analysis was performed using profiling data generated over a 3-year period, including patch clamp data from hERG, Ca_v1.2, and Na_v1.5 (peak/late), together with hERG binding.

Results: Assay reproducibility was robust over the 3-year period examined. High throughput hERG patch IC₅₀ values correlated well with GLP-hERG data (Pearson = 0.87). A disconnect between hERG binding and patch was observed for ∼10% compounds and trended with passive cellular permeability. hERG and Ca_v1.2 potency did not correlate for proprietary compounds, with more potent hERG compounds showing selectivity versus Ca_v1.2. For clinical compounds where hERG and Ca_v1.2 activity was more balanced, an analysis of TdP risk versus hERG/Ca_v1.2 ratio demonstrated low TdP probability when the hERG/Ca_v1.2 potency ratios were < 1. Modeling of clinical compound data revealed a lack of impact of the Na_v1.5 (late) current in predicting TdP. Moreover, models using hERG binding data (ROC AUC = 0.876) showed an improved ability to predict TdP risk versus hERG patch clamp (ROC AUC = 0.787).

Discussion: The data highlight the value of high throughput patch clamp data in the prediction of TdP risk, as well as some potential limitations with this approach.