title: Variability in high-throughput ion-channel screening data and consequences for cardiac safety assessment.
abstract: BACKGROUND
  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.
  
  
  CONCLUSIONS
  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.
authors: Global Safety Pharmacology, Global Safety Assessment, AstraZeneca, Alderley Park SK10 4TG, UK.
authors: Ryan C
authors: RC
authors: Elkins
authors: Mark R
authors: MR
authors: Davies
authors: Stephen J
authors: SJ
authors: Brough
authors: David J
authors: DJ
authors: Gavaghan
authors: Yi
authors: Y
authors: Cui
authors: Najah
authors: N
authors: Abi-Gerges
authors: Gary R
authors: GR
authors: Mirams
mesh_terms: D000200:Action Potentials / Q000187:drug effects; D002460:Cell Line; D003198:Computer Simulation; D004305:Dose-Response Relationship, Drug; D015195:Drug Design; D057166:High-Throughput Screening Assays / Q000379:methods*; D006801:Humans; D007473:Ion Channels / Q000187:drug effects* / Q000378:metabolism; D008962:Models, Theoretical; D032383:Myocytes, Cardiac / Q000187:drug effects / Q000378:metabolism; D018408:Patch-Clamp Techniques; D018675:Toxicity Tests
chemical_list: D007473:Ion Channels
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
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