Construction and evaluation of an open-source database for inhalation-based physiologically based kinetic modeling of selected categories for industrial chemicals.

Abstract

A physiologically based kinetic (PBK) model is used for predicting chemical concentrations of toxicological concern in target tissues. Such models are important for understanding toxicokinetics. However, it is challenging to obtain chemical-specific empirical parameter values used for PBK modeling. Thus, developing methods predicting these values is necessary. Herein, we researched PBK models of inhalation exposure to industrial chemicals and developed a database of parameters of approximately 200 chemicals in humans and rodents. Next, the chemicals in the database were classified into three categories (I, IIA, and IIB) based on the intermolecular interactions for humans and rats. Quantitative relationships between blood/air and tissue/blood partition coefficients and physicochemical parameters were derived for the chemicals in each category. Regression analyses of blood/air and fat/blood partition coefficients against Henry's law constant and log D at pH 7.4 for chemicals in category IIA for humans, in which van der Waals and dipole-dipole interactions were involved, yielded 0.88 and 0.54 coefficients of determination, respectively. Moreover, these methods worked for other categories and species. The metabolic parameters maximal velocity (Vmax) and Michaelis-Menten constant (Km) of the chemicals that are primarily metabolized by cytochrome P450 were calculated for humans and rats. Multiple regression analyses of logs Vmax and Km against the occurrence frequency of molecular fragments showed good correlations, respectively. The aforementioned models predicted values close to the reported values for test chemicals within the applicability domains. Our approach could also be applied to other chemicals within the domains that are not included in the database.