title: QTc modification after risperidone administration--insight into the mechanism of action with use of the modeling and simulation at the population level approach.
abstract: BACKGROUND
  Ensuring the safety of therapy is both expensive and time-consuming process, which may be supported by modeling and simulation.
  
  
  OBJECTIVE
  The objective of this study was to gain insight into the effect of risperidone administration on QT interval by in silico evaluation of the effect in the individuals with different metabolic status of CYP2D6.
  
  
  METHODS
  Evaluation was performed through the combination of empirical and mechanistic modeling with the use of the Cardiac Safety Simulator platform allowing for simulation of electrophysiological consequences of drug administration at the population level. The performance of the proposed approach was evaluated by in silico mimicking of the clinical trial conducted by Novalbos.
  
  
  RESULTS
  The simulation results depict differences in ΔQT correlated with change in metabolic activity, but not as significant as observed clinically. For poor metabolizers (PMs), ΔQTc was 8.0 and 5.1 ms, for Fridericia's and Bezett's correction, respectively, in comparison to 13.9 in Novalbos's study. For intermediate metabolizers (IMs), there was 9.3 and 7.3 ms versus 4 ms observed clinically, for ultrarapid metabolizers (UMs) -4.0 and 1 ms versus 0.60 ms, for EMs -5.9 and 7.7 ms versus 6.1 ms.
  
  
  CONCLUSIONS
  Simulated results underestimate changes observed in the PMs and overestimate the results for the IMs and UMs groups. EM individuals were properly predicted. The results of various QTc studies vary considerably and it is not clear which factors have a decisive influence. Nevertheless, presented differences are still more consistent with clinical results than results obtained clinically by other researchers.
authors.affiliation: a Department of Social Pharmacy, Faculty of Pharmacy, Jagiellonian University Medical College , Krakow , Poland and.
authors.forename: Anna
authors.initials: A
authors.lastname: Glinka
authors.forename: Sebastian
authors.initials: S
authors.lastname: Polak
mesh_terms: D000293:Adolescent; D000328:Adult; D014150:Antipsychotic Agents / Q000009:adverse effects* / Q000493:pharmacokinetics; D003198:Computer Simulation; D019389:Cytochrome P-450 CYP2D6 / Q000235:genetics / Q000378:metabolism; D004562:Electrocardiography / Q000187:drug effects*; D005260:Female; D006339:Heart Rate / Q000187:drug effects; D006801:Humans; D007473:Ion Channels / Q000187:drug effects; D008297:Male; D009206:Myocardium / Q000378:metabolism; D032383:Myocytes, Cardiac / Q000187:drug effects; D000068882:Paliperidone Palmitate / Q000494:pharmacology; D021281:Quantitative Structure-Activity Relationship; D018967:Risperidone / Q000009:adverse effects* / Q000493:pharmacokinetics; D014882:Water-Electrolyte Balance / Q000187:drug effects; D055815:Young Adult
chemical_list: D014150:Antipsychotic Agents; D007473:Ion Channels; D019389:Cytochrome P-450 CYP2D6; D018967:Risperidone; D000068882:Paliperidone Palmitate
keywords: CYP2D6; drug safety; in silico; torsades