QSARs for PBPK modelling of environmental contaminants

Abstract

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.

Modeling of interactions between xenobiotics and cytochrome P450 (CYP) enzymes

“…These QPPRs have either focused on modeling V max or K m and not both parameters for a given set of chemicals. Furthermore, these approaches appear to show the promise in modeling single enzyme substrates or a specific reaction and thus are of limited predictive ability (Peyret and Krishnan, 2011). …”

A roadmap for the development of alternative (non-animal) methods for systemic toxicity testing

“…QSAR algorithms for predicting metabolism parameters have only been developed for a limited number of chemicals, primarily volatile organic compounds that are substrates for CYP2E1 (Peyret and Krishnan, 2011). Thus, it would be necessary to perform in vitro assays of the dose-response (capacity and affinity) for metabolic clearance (Houston and Carlile, 1997;Kedderis, 1997;Kedderis et al, 1993;Kedderis and Held, 1996).…”

Informatics and Data Analytics to Support Exposome-Based Discovery for Public Health

“…Several research groups are developing generic PBPK models, either as standalone tools such as PK-Sim (70) and Indus-Chem (24) or incorporated within integrated computational platforms for exposure assessment such as MENTOR (Modeling ENvironment for TOtal Risk Studies) (15). The development of generic and validated PBPK models for many individual chemical exposures is supported by recent advances in quantitative structure–property relationships (QSPRs) (45, 48, 53). However, the integration, validation, and evaluation of these models into a multiple agent exposome profile are outstanding challenges.…”