In vitro-in silico-based prediction of inter-individual and inter-ethnic variations in the dose-dependent cardiotoxicity of R- and S-methadone in humans

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.

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).

Fig. 1

Schematic diagram of the PBK model of R- and S-methadone

Fig. 2

Blood concentration–time curves of R-methadone (a, b) and S-methadone (c, d) in human predicted with the PBK model (lines) and published in vivo data (dots) (Liu et al. 2007) after a repeated oral rac-methadone dose of 100 mg/day for 30 days. a and c present predictions obtained from the model using HLM kinetic data and b and d present predictions obtained from the model using rCYPs kinetic data. The top right insert is the predicted blood concentration of R- and S-methadone (lines) and in vivo data (dots) during the last 24 h upon the oral exposure

Fig. 3

Distribution of predicted unbound C_max of R- (a) and S-methadone (b) in the heart venous blood at steady-state after a repeated oral methadone enantiomer dose of 30 mg/day for 30 days in the Caucasian and the Chinese population. The scatter plots represent the predictions obtained using individual PBK models. Whisker plots represent the predictions obtained by the Monte Carlo (MC) simulation considering the variations in metabolism only, and variations in multiple factors. The whiskers represent the 1st and 99th percentile of defined populations

Fig. 4

Frequency distribution for unbound C_max of R-methadone (a, b) and S-methadone (c, d) in the heart venous blood at steady-state after a repeated oral methadone enantiomer dose of 30 mg/day for 30 days in Caucasian (a, c) and Chinese (b, d) individuals by the Monte Carlo simulation considering variations in multiple factors. The GM and P99 represent the geometric mean and the 99th percentile of the distribution

Fig. 5

Predicted dose–response curves for the cardiotoxicity of R-methadone (a, b) and S-(c, d) methadone in the average (solid lines) and the sensitive population (99th percentile of predicted C_max in heart venous blood) (dotted lines) of Caucasian (a, c) and Chinese (b, d) population. The dose–response curves for sensitive Caucasian and Chinese populations were obtained by applying the respective CSAFs (calculated based on variations in metabolism, bodyweight, oral fraction absorbed and fraction unbound in plasma.) to the dose–response curves of the average populations