Development of a human physiologically based pharmacokinetic (PBPK) model for phthalate (DEHP) and its metabolites: a bottom up modeling approach

Identificador:  imarina:4683713

Handle: https://hdl.handle.net/20.500.11797/imarina4683713

Autors:  Sharma, Raju Prasad; Schuhmacher, Marta; Kumar, Vikas

Resum:
DEHP exposure to human comes from different sources such as food, diet, cosmetics, toys, medical products, and food wraps. Recently, DEHP was categorized as non-persistent endocrine disrupting compounds (EDCs) by the world health organization (WHO). Rat experimental studies showed that phthalate and its metabolite(s) can cause hepatic, developmental and reproductive toxicity. In human, DEHP rapidly metabolizes into a toxic metabolite MEHP. This MEHP further metabolizes into the different chemical forms of 5OH-MEHP, 5oxo-MEHP, 5cx-MEPP and phthalic acid. A simple DEHP pharmacokinetics model has been developed, but with a limited number of metabolites. A chemical like DEHP which extensively metabolised indicate the need of a detail metabolic kinetics study. A physiological based pharmacokinetics (PBPK) model of the DEHP considering all the major metabolites in human, has not been developed yet. The objective of this study is to develop a detailed human PBPK model for the DEHP and its major metabolites by using a bottom-up modelling approach with the integration of a in vitro metabolic data. This approach uses an in-vitro-in-vivo extrapolation (IVIVE) and a quantitative structure-activity relationship (QSAR) method for the parameterization of the model. Monte Carlo simulations were performed to estimate the impact of parametric uncertainty onto the model predictions. First, the model was calibrated using the control human kinetic study that represents the time course of DEHP metabolites concentration in both the blood and the urine. Then, the model was evaluated against the published independent data on different dosing scenarios. The results of model predictions for the DEHP metabolites in both the blood and the urine were well within the range of experimentally observed data. The model also captured the similar trend of time course profile to the observed data, shows model good predictability power. The current developed PBPK model can futher be used for the prediction of the time course of chemical concentrations for the different exposure scenarios not only in the blood and the urine but also in the other compartments. Moreover, this model can also be used to explore different biomonitoring studies for the human health risk assessment and might be useful for integrative toxicological study in improving exposure-target tissue dose-response relationship.