Anna Glinka1, Sebastian Polak2. 1. Department of Social Pharmacy, Faculty of Pharmacy, Jagiellonian University Medical College, Medyczna 9 Street, Krakow 30-688, Poland. Electronic address: anna.glinka@uj.edu.pl. 2. Department of Social Pharmacy, Faculty of Pharmacy, Jagiellonian University Medical College, Medyczna 9 Street, Krakow 30-688, Poland; Simcyp Limited (a Certara Company), Blades Enterprise Centre, John Street, S2 4SU Sheffield, UK.
Abstract
BACKGROUND: Many drugs (belonging to different chemical groups) have the potential for QT interval prolongation associated with ionic channel blockade in the cardiomyocyte membrane. Due to the fact that this phenomenon is linked to a higher risk of TdP, the ability to predict its scale is one of the most important outcomes of cardiotoxicity assessment of new agents. METHODS: With use of the Cardiac Safety Simulator (CSS), the effect of six antipsychotic drugs was predicted in silico. Separate simulations were carried out for each studied population taking the drug. The aim of this study was to predict both the mean values of delta QTc and the results range. To be able to observe individual variability after drug administration, each patient was randomly assigned to the individual drug concentration. Also, appropriate diversity in heart rate, plasma electrolytes concentrations, morphometric parameters of ventricular myocytes, and one common hERG polymorphism frequency in population were added. RESULTS: Analyzing the results of simulation with Student's t-test, in five of six cases, there were no statistically significant differences between observed and predicted mean values. The diversity of results in all populations studied, however, was not fully reconstructed. DISCUSSION: The model was able to accurately reproduce the average effect of the drug on the length when the phenomenon is associated purely with blocking of ionic channels. Nevertheless, the problem of variability in the population and its effect on the QT interval requires further study.
BACKGROUND: Many drugs (belonging to different chemical groups) have the potential for QT interval prolongation associated with ionic channel blockade in the cardiomyocyte membrane. Due to the fact that this phenomenon is linked to a higher risk of TdP, the ability to predict its scale is one of the most important outcomes of cardiotoxicity assessment of new agents. METHODS: With use of the Cardiac Safety Simulator (CSS), the effect of six antipsychotic drugs was predicted in silico. Separate simulations were carried out for each studied population taking the drug. The aim of this study was to predict both the mean values of delta QTc and the results range. To be able to observe individual variability after drug administration, each patient was randomly assigned to the individual drug concentration. Also, appropriate diversity in heart rate, plasma electrolytes concentrations, morphometric parameters of ventricular myocytes, and one common hERG polymorphism frequency in population were added. RESULTS: Analyzing the results of simulation with Student's t-test, in five of six cases, there were no statistically significant differences between observed and predicted mean values. The diversity of results in all populations studied, however, was not fully reconstructed. DISCUSSION: The model was able to accurately reproduce the average effect of the drug on the length when the phenomenon is associated purely with blocking of ionic channels. Nevertheless, the problem of variability in the population and its effect on the QT interval requires further study.
Authors: Sebastian Polak; Michael K Pugsley; Norman Stockbridge; Christine Garnett; Barbara Wiśniowska Journal: AAPS J Date: 2015-05-05 Impact factor: 4.009
Authors: Kamil Fijorek; Felix C Tanner; Barbara E Stähli; Grzegorz Gielerak; Pawel Krzesinski; Beata Uzieblo-Zyczkowska; Pawel Smurzynski; Adam Stanczyk; Katarzyna Stolarz-Skrzypek; Kalina Kawecka-Jaszcz; Marek Jastrzebski; Mateusz Podolec; Grzegorz Kopec; Barbara Stanula; Maryla Kocowska; Zofia Tylutki; Sebastian Polak Journal: J Cardiovasc Transl Res Date: 2014-03-28 Impact factor: 4.132
Authors: Peter Bloomingdale; Conrad Housand; Joshua F Apgar; Bjorn L Millard; Donald E Mager; John M Burke; Dhaval K Shah Journal: Curr Opin Toxicol Date: 2017-08-02
Authors: T A Collins; L Bergenholm; T Abdulla; Jwt Yates; N Evans; M J Chappell; J T Mettetal Journal: CPT Pharmacometrics Syst Pharmacol Date: 2015-03-11