ABSTRACTPredicting how pharmaceuticals may affect heart rhythm is a crucial step in drug-development, and requires a deep understanding of a compound’s action on ion channels.In vitrohERG-channel current recordings are an important step in evaluating the pro-arrhythmic potential of small molecules, and are now routinely performed using automated high-throughput patch clamp platforms. These machines can execute traditional voltage clamp protocols aimed at specific gating processes, but the array of protocols needed to fully characterise a current is typically too long to be applied in a single cell. Shorter high-information protocols have recently been introduced which have this capability, but they are not typically compatible with high-throughput platforms. We present a new high-information 15 s protocol to characterise hERG (Kv11.1) kinetics, suitable for both manual and high-throughput systems. We demonstrate its use on the Nanion SyncroPatch 384PE, a 384 well automated patch clamp platform, by applying it to CHO cells stably expressing hERG1a. From these recordings we construct 124 cell-specific variants/parameterisations of a hERG model at 25 °C. A further 8 independent protocols are run in each cell, and are used to validate the model predictions. We then combine the experimental recordings using a hierarchical Bayesian model, which we use to quantify the uncertainty in the model parameters, and their variability from cell to cell, which we use to suggest reasons for the variability. This study demonstrates a robust method to measure and quantify uncertainty, and shows that it is possible and practical to use high-throughput systems to capture full hERG channel kinetics quantitatively and rapidly.Statement of SignificanceWe present a method for high-throughput characterisation of hERG potassium channel kinetics, via fitting a mathematical model to results of over one hundred single cell patch clamp measurements collected simultaneously on an automated voltage clamp platform. The automated patch clamp data are used to parameterise a mathematical ion channel model fully, opening a new era of automated and rapid development of mathematical models from quick and cheap experiments. The method also allows ample data for independent validation of the models and enables us to study experimental variability and propose its origins. In future the method can be applied to characterise changes to hERG currents in different conditions, for instance at different temperatures (see Part II of the study) or under mutations or the action of pharmaceuticals; and should be easily adapted to study many other currents.
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