Research to develop a predicting system of mammalian subacute toxicity, (3). Construction of a predictive toxicokinetics model

Molecular Structure-Based Prediction of the Toxicokinetics of Inhaled Vapors in Humans

The objectives of the present study were: (1) to evaluate the adequacy of setting hepatic extraction ratio (E) equal to 0 or 1 in physiologically based toxicokinetic (PBTK) models to generate the theoretically plausible envelope of venous blood concentration (Cv) profiles, and (2) to couple this approach with molecular structure-based estimation of blood:air and tissue: blood partition coefficients (PCs) to predictthe Cv profiles of volatile organic chemicals (VOCs) in humans. Setting E= 0 or 1 in PBTK models provided simulations of Cv envelopes that contained the Cv values determined in humans exposed to low concentrations of dichloromethane(DCM), ethylbenzene (EBZ), toluene (TOL), m-xylene(XYL), trichloroethy-lene (TCE), and 1,1,1-trichloroethane(TRI). Following the validation of using E= 0 or 1 in conventional PBTK models to predict the theoretically plausible envelope of Cv, a quantitative structure-toxicokinetic relationship (QSTkR) model was constructed. The QSTkR model used molecular structure information as the sole input to predict the PCs and considered E= 0 or 1 to generate simulations of the envelope of Cv. The experimental data on Cv were in most cases within the envelopes simulated using QSTkR models for DCM, EBZ, TOL, and XYL, but were outside the envelopes for TCE and TRI. The discrepancy observed between the Cv envelopes obtained using PBTK and QSTkR models can be explained by the fact that blood:air PCs of some VOCs were under-predicted while using molecular structure information. The modeling framework presented in this article represents the first animal-replacement tool that can provide a priori predictions of the toxicokinetic profiles of VOCs prior to laboratory experiments.

Physiologically-based pharmacokinetic (PBPK) models in toxicity testing and risk assessment

Physiologically-based pharmacokinetic (PBPK) modeling offers a scientifically-sound framework for integrating mechanistic data on absorption, distribution, metabolism and elimination to predict the time-course of parent chemical, metabolite(s) or biomarkers in the exposed organism. A major advantage of PBPK models is their ability to forecast the impact of specific mechanistic processes and determinants on the tissue dose. In this regard, they facilitate integration of data obtained with in vitro and in silico methods, for making predictions of the tissue dosimetry in the whole animal, thus reducing and/or refining the use of animals in pharmacokinetic and toxicity studies. This chapter presents the principles and practice of PBPK modeling, as well as the application of these models in toxicity testing and health risk assessments.

QSARs for PBPK modelling of environmental contaminants

Physiologically-based pharmacokinetic (PBPK) models are increasingly finding use in risk assessment applications of data-rich compounds. However, it is a challenge to determine the chemical-specific parameters for these models, particularly in time- and resource-limiting situations. In this regard, SARs, QSARs and QPPRs are potentially useful for computing the chemical-specific input parameters of PBPK models. Based on the frequency of occurrence of molecular fragments (CH(3), CH(2), CH, C, C=C, H, benzene ring and H in benzene ring structure) and exposure conditions, the available QSAR-PBPK models facilitate the simulation of tissue and blood concentrations for some inhaled volatile organic chemicals. The application domain of existing QSARs for developing PBPK models is limited, due to lack of relevant data for diverse chemicals and mechanisms. Even though this approach is conceptually applicable to non-volatile and high molecular weight organics as well, it is more challenging to predict the other PBPK model parameters required for modelling the kinetics of these chemicals (particularly tissue diffusion coefficients, association constants for binding and oral absorption rates). As the level of our understanding of the mechanistic basis of toxicokinetic processes improves, QSARs to provide a priori predictions of key chemical-specific PBPK parameters can be developed to expedite the internal dose-based health risk assessments in data-poor situations.

Prediction of pharmacokinetics prior to in vivo studies. II. Generic physiologically based pharmacokinetic models of drug disposition

Many in vitro data on physicochemical properties and specific absorption, distribution, metabolism, and elimination (ADME) processes are already available at early stages of drug discovery. These data about new drug candidates could be integrated/connected in physiologically based pharmacokinetic (PBPK) models to estimate a priori the overall plasma and tissue kinetic behaviors under in vivo conditions. The objective of the present study was to illustrate that generic PBPK models integrating such data can be developed in drug discovery prior to any in vivo studies. This approach was illustrated with three example compounds, including two lipophilic bases (diazepam, propranolol) and one neutral more hydrophilic drug (ethoxybenzamide). Distribution and liver metabolism were the processes integrated in the generic rat PBPK models of disposition. Tissue:plasma partition coefficients (P(t:p)s) used for description of distribution were estimated from established tissue composition-based equations, which need only in vitro data on drug lipophilicity and plasma protein binding as sole input parameters. Furthermore, data on intrinsic clearance (CL(int)) determined in vitro with hepatocytes were scaled to the in vivo situation to estimate hepatic metabolic clearance. These prediction approaches were both incorporated in the PBPK models to enable automated estimation of distribution and liver metabolism for each drug studied. The generic PBPK models suggested can simulate a priori concentration-time profiles of plasma and several tissues after intravenous administrations to rat. The results indicate that most of the simulated concentration-time profiles of plasma and 10 tissues are in reasonable agreement with the corresponding experimental data determined in vivo (less than a factor of two). However, some more relevant deviations were observed for specific tissues (brain and gut for diazepam; liver and gut for ethoxybenzamide; lung for propranolol) because of important ADME processes were probably neglected in the PBPK models of these drugs. In this context, generic PBPK models were also used for mechanistic evaluations of pharmacokinetics for generating research hypotheses to understand these deviations. Overall, the present generic and integrative PBPK approach of drug disposition suggested as a tool for a priori simulations and mechanistic evaluations of pharmacokinetics has the potential to improve the selection and optimization of new drug candidates.

A Quantitative Structure-toxicokinetic Relationship Model for Highly Metabolised Chemicals

The aim of the present study was to develop a quantitative structure-toxicokinetic relationship (QSTkR) model for highly metabolised chemicals (HMCs). The proposed QSTkR model is essentially a physiologically based toxicokinetic (PBTK) model, in which the blood:air and tissue:blood partition coefficients (PCs) are predicted from the molecular structure of chemicals, and the liver blood flow rate (Q1) is used to describe hepatic clearance. Molecular structure-based prediction of the blood:air and tissue:blood PCs was performed from the n-octanol:water and water:air PCs of chemicals obtained with the conventional fragment constant methods. The validity of incorporating Q1 instead of metabolic rate constants, as the hepatic clearance factor, in PBTK models for HMCs (extraction ratio > 0.7) was verified by comparing the simulations of venous blood concentration (Cv) profiles obtained with both the QSTkR and PBTK model approaches for 1,1-dichloroethylehe, trichloroethylene and furan in the rat. Following the validation of this alternative approach for describing hepatic clearance of HMCs, a QSTkR model for dichloromethane was constructed. This model used molecular structure information as the sole input, and provided simulations of Cv for human exposure to low concentrations of dichloromethane. The QSTkR model simulations were similar to those obtained with the previously validated, conventional human PBTK model with experimentally determined PCs and metabolic rate constants (Vmax, Km and Kf) for dichloromethane. The present methodology is the first validated example of a mechanistically based prediction of the inhalation toxicokinetics of HMCs made solely from information on molecular structure.