Incorporating Parameter and Population Variability into PBPK Modeling
To identify the potential for a chemical to be of concern to sensitive populations, it is important for NAMs to characterize variations in metabolism that can affect toxicity within a population of interest. NIEHS scientists are incorporating the effects of genetic variability on ADME into pharmacokinetic models. These models can be used to predict a tissue concentration from an external exposure (forward dosimetry) or estimate an external exposure that would result in a plasma or tissue concentration equivalent to an effective concentration in an in vitro assay (reverse dosimetry). The models use inputs from ADMET Predictor software (Simulations Plus, Inc.) to characterize what enzymes might be involved in a chemical’s metabolism and the structure and proportions of metabolites produced. Work is ongoing to identify polymorphisms in the genes coding for enzymes that might affect metabolism, characterize the polymorphisms’ prevalence within populations, and incorporate this information into IVIVE and PBPK models. The OPERA QSAR modeling suite will then be used to predict a range of resulting toxicities for chemical metabolites.