Assessing the relevance of rodent data on chemical interactions for health risk assessment purposes: a case study with dichloromethane-toluene mixture.

Several descriptive studies have reported the occurrence of infra-additive and supra-additive toxic interactions in rodents given high doses of chemicals by routes different from anticipated human exposures. In order to assess the relevance of such rodent data on chemical interactions for humans, the route, species, and dose extrapolations need to be conducted on the basis of proven/hypothetical interaction mechanisms. The present study initially developed a physiologically based model of the toxicological interaction reported in rats receiving high oral doses of dichloromethane (DCM) and toluene (TOL). This predictive model was then used to asses the relevance of DCM-TOL interaction for humans exposed to threshold limit values (TLVs) of these chemicals, following the conduct of the various, essential extrapolations (i.e., rat to human, oral to inhalation, high dose to low dose). The interaction modeling approach involved (i) obtaining validated rat and human physiologically based pharmacokinetic (PBPK) models for TOL and DCM from the literature, and (ii) linking them via the modified Michaelis-Menten equation accounting for hypothetical mechanisms of interactions (no interaction, competitive inhibition, noncompetitive inhibition, and uncompetitive inhibition). Of the various interaction mechanisms investigated, the noncompetitive and uncompetitive metabolic inhibitions were found to adequately describe the reduction of carboxyhemoglobinemia (COHB) observed in rats during combined exposures (18.8 mmol/kg TOL, +6.2 mmol/kg DCM, po; 0.005 mmol/kg TOL, ip +5000 ppm DCM, 1 hr). The simulation model, based on noncompetitive and uncompetitive inhibition mechanisms, suggests that only < 10% reduction in the area under the COHB vs time curve (AUCCOHB) is likely to occur in humans exposed to the current TLVs of DCM and TOL (compared to AUCCOHB resulting from an 8-hr exposure to TLV of DCM alone). The present modeling approach, based on hypothetical mechanisms of interaction, then indicates that rodent data on DCM-TOL interaction are not relevant for humans, particularly with respect to the COHB effect. The application of this kind of a predictive modeling approach should be useful in screening the available reports on chemical interactions for identifying those of greater concern at relevant human exposure levels (RfD, RfC, TLV).