Abstract
New approach methodologies predicting human cardiotoxicity are of interest to support or even replace in vivo-based drug safety testing. The present study presents an in vitro–in silico approach to predict the effect of inter-individual and inter-ethnic kinetic variations in the cardiotoxicity of R- and S-methadone in the Caucasian and the Chinese population. In vitro cardiotoxicity data, and metabolic data obtained from two approaches, using either individual human liver microsomes or recombinant cytochrome P450 enzymes (rCYPs), were integrated with physiologically based kinetic (PBK) models and Monte Carlo simulations to predict inter-individual and inter-ethnic variations in methadone-induced cardiotoxicity. Chemical specific adjustment factors were defined and used to derive dose–response curves for the sensitive individuals. Our simulations indicated that Chinese are more sensitive towards methadone-induced cardiotoxicity with Margin of Safety values being generally two-fold lower than those for Caucasians for both methadone enantiomers. Individual PBK models using microsomes and PBK models using rCYPs combined with Monte Carlo simulations predicted similar inter-individual and inter-ethnic variations in methadone-induced cardiotoxicity. The present study illustrates how inter-individual and inter-ethnic variations in cardiotoxicity can be predicted by combining in vitro toxicity and metabolic data, PBK modelling and Monte Carlo simulations. The novel methodology can be used to enhance cardiac safety evaluations and risk assessment of chemicals.
Original language | English |
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Pages (from-to) | 2361-2380 |
Number of pages | 20 |
Journal | Archives of Toxicology |
Volume | 96 |
Issue number | 8 |
DOIs | |
Publication status | Published - Aug 2022 |
Keywords
- Human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM)
- Inter-individual differences
- Methadone
- Monte Carlo simulation
- New approach methodologies (NAM)
- Physiologically based kinetic (PBK) modelling
- Quantitative in vitro to in vivo extrapolation (QIVIVE)