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Toxicol Sci. 2001 Sep;63(1):125-31.

A PBPK modeling-based approach to account for interactions in the health risk assessment of chemical mixtures.

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  • 1Groupe de recherche en toxicologie humaine (TOXHUM), Faculté de médecine, Université de Montréal, Case Postale 6128, Succursale centre-ville, Montréal, Québec H3C 3J7, Canada.


The objectives of the present study were: (1) to develop a risk assessment methodology for chemical mixtures that accounts for pharmacokinetic interactions among components, and (2) to apply this methodology to assess the health risk associated with occupational inhalation exposure to airborne mixtures of dichloromethane, benzene, toluene, ethylbenzene, and m-xylene. The basis of the proposed risk assessment methodology relates to the characterization of the change in tissue dose metrics (e.g., area under the concentration-time curve for parent chemical in tissues [AUCtissue], maximal concentration of parent chemical or metabolite [Cmax], quantity metabolized over a period of time) in humans, during mixed exposures using PBPK models. For systemic toxicants, an interaction-based hazard index was calculated using data on tissue dose of mixture constituents. Initially, the AUCtarget tissue (AUCtt) corresponding to guideline values (e.g., threshold limit value [TLV]) of individual chemicals were obtained. Then, the AUCtt for each chemical during mixed exposure was obtained using a mixture PBPK model that accounted for the binary and higher order interactions occurring within the mixture. An interaction-based hazard index was then calculated for each toxic effect by summing the ratio of AUCtt obtained during mixed exposure (predefined mixture) and single exposure (TLV). For the carcinogenic constituents of the mixture, an interaction-based response additivity approach was applied. This method consisted of adding the cancer risk for each constituent, calculated as the product of q*tissue dose and AUCtt. The AUCtt during mixture exposures was obtained using an interaction-based PBPK model. The approaches developed in the present study permit, for the first time, the consideration of the impact of multichemical pharmacokinetic interactions at a quantitative level in mixture risk assessments.

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