Predicting cardiac proarrhythmic risk exclusively using automated patch-clamp data

Recent work by FDA and HESI CiPA working groups indicate that in vitro hERG, Na_v1.5 and Ca_v1.2 potency data in addition to dynamic hERG kinetic data is required to accurately predict proarrhythmic risk. Below we explore two key challenges in exclusively using automated patch-clamp for risk prediction:

1. Metrion has previously shown the ability to implement the difficult Milnes protocol on QPatch, but the challenges of producing full concentration response formats required for in silico models are unknown.
2. Estimating accurate potencies for Ca_v1.2 inhibitors such as verapamil that match manual patch-clamp values and allow prediction of Multiple Ion Channel Effect (MICE) profiles with reduced proarrhythmia risk.