Evaluation of three physiologically based pharmacokinetic (PBPK) modeling tools for emergency risk assessment after acute dichloromethane exposure

•In silico simulations of human data on acute inhalation exposure to dichloromethane.•Evaluation of three available physiologically based pharmacokinetic models.•Assessment of the models’ usefulness in supporting emergency risk assessment.•Generic models can be used for screening purposes.•A chemical-specific model is more appropriate for a detailed application. Physiologically based pharmacokinetic (PBPK) models may be useful in emergency risk assessment, after acute exposure to chemicals, such as dichloromethane (DCM). We evaluated the applicability of three PBPK models for human risk assessment following a single exposure to DCM: one model is specifically developed for DCM (Bos) and the two others are semi-generic ones (Mumtaz and Jongeneelen). We assessed the accuracy of the models’ predictions by simulating exposure data from a previous healthy volunteer study, in which six subjects had been exposed to DCM for 1h. The time-course of both the blood DCM concentration and percentage of carboxyhemoglobin (HbCO) were simulated. With all models, the shape of the simulated time course resembled the shape of the experimental data. For the end of the exposure, the predicted DCM blood concentration ranged between 1.52–4.19mg/L with the Bos model, 1.42–4.04mg/L with the Mumtaz model, and 1.81–4.31mg/L with the Jongeneelen model compared to 0.27–5.44mg/L in the experimental data. % HbCO could be predicted only with the Bos model. The maximum predicted % HbCO ranged between 3.1 and 4.2% compared to 0.4–2.3% in the experimental data. The % HbCO predictions were more in line with the experimental data after adjustment of the Bos model for the endogenous HbCO levels. The Bos Mumtaz and Jongeneelen PBPK models were able to simulate experimental DCM blood concentrations reasonably well. The Bos model appears to be useful for calculating HbCO concentrations in emergency risk assessment.