Variability in high-throughput ion-channel screening data and consequences for cardiac safety assessment

Abstract

Introduction: Unwanted drug interactions with ionic currents in the heart can lead to an increased pro-arrhythmic risk to patients in the clinic. It is therefore a priority for safety pharmacology teams to detect block of cardiac ion channels, and new technologies have enabled the development of automated and high-throughput screening assays using cell lines. As a result of screening multiple ion-channels there is a need to integrate information, particularly for compounds affecting more than one current, and mathematical electrophysiology in-silico action potential models are beginning to be used for this.

Methods: We quantified the variability associated with concentration-effect curves fitted to recordings from high-throughput Molecular Devices IonWorks® Quattro™ screens when detecting block of I(Kr) (hERG), I(Na) (NaV1.5), I(CaL) (CaV1.2), I(Ks) (KCNQ1/minK) and I(to) (Kv4.3/KChIP2.2), and the Molecular Devices FLIPR® Tetra fluorescence screen for I(CaL) (CaV1.2), for control compounds used at AstraZeneca and GlaxoSmithKline. We examined how screening variability propagates through in-silico action potential models for whole cell electrical behaviour, and how confidence intervals on model predictions can be estimated with repeated simulations.

Results: There are significant levels of variability associated with high-throughput ion channel electrophysiology screens. This variability is of a similar magnitude for different cardiac ion currents and different compounds. Uncertainty in the Hill coefficients of reported concentration-effect curves is particularly high. Depending on a compound's ion channel blocking profile, the uncertainty introduced into whole-cell predictions can become significant.

Discussion: Our technique allows confidence intervals to be placed on computational model predictions that are based on high-throughput ion channel screens. This allows us to suggest when repeated screens should be performed to reduce uncertainty in a compound's action to acceptable levels, to allow a meaningful interpretation of the data.

Keywords: AP(D); AZ; Action Potential (Duration); Action potential; AstraZeneca; Cardiac safety; Compound screening; Concentration for 50% Inhibition; FLIPR; FLuorometric Imaging Plate Reader; GSK; GlaxoSmithKline; HTS; High Throughput Screening [assays]; High-throughput; I(CaL); I(Kr); I(Ks); I(Na); I(to); IC(50); L-type calcium current; Mathematical model; PDF; PPC; Population Patch Clamping; Probability Density Function; QT(c); QTinterval of the electrocardiogram (corrected for heart rate); TQT; TT06; Ten Tusscher and Panfilov (2006) human ventricular cell model; Thorough QT, human clinical QT prolongation trial; Uncertainty; Variability; [fast] transient outward potassium current; fast sodium current; minus log(10) of IC(50); pIC(50); rapid delayed rectifier potassium current; slow delayed rectifier potassium current.