The hepatic elimination of chemical substances in pharmacokinetic models requires hepatic intrinsic clearance (CL) parameters for unbound drug in the liver, and these are regulated by the liver-to-plasma partition coefficients (K). Both Poulin and Theil and Rodgers and Rowland have proposed in silico expressions for K for a variety of chemicals. In this study, two sets of in silico K values for 14 model substances were assessed using experimentally reported in vivo steady-state K data and time-dependent virtual internal exposures in the liver and plasma modeled by forward dosimetry in rats. The K values for 14 chemicals independently calculated using the primary Poulin and Theil method in this study were significantly correlated with those obtained using the updated Rodgers and Rowland method and with reported in vivo steady-state K data in rats. When pharmacokinetic parameters were derived based on individual in vivo time-dependent data for diazepam, phenytoin, and nicotine in rats, the modeled liver and plasma concentrations after intravenous administration of the selected substrates in rats using two sets of in silico K values were mostly similar to the reported time-dependent in vivo internal exposures. Similar results for modeled liver and plasma concentrations were observed with input parameters estimated by machine-learning systems for hexobarbital, fingolimod, and pentazocine, with no reference to experimental pharmacokinetic data. These results suggest that the output values from rat pharmacokinetic models based on in silico K values derived from the primary Poulin and Theil model would be applicable for estimating toxicokinetics or internal exposure to substances.

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