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Role of Physiologically Based Kinetic modelling in addressing environmental chemical mixtures - A review.

ABSTRACT: The role of Physiologically Based Kinetic (PBK) modelling in assessing mixture toxicology has been growing for the last three decades. It has been widely used to investigate and address interactions in mixtures. This review describes the current state-of-the-art of PBK models for chemical mixtures and to evaluate the applications of PBK modelling for mixtures with emphasis on their role in chemical risk assessment. A total of 35 mixture PBK models were included after searching web resources (Scopus, PubMed, Web of Science, and Google Scholar), screening for duplicates, and excluding articles based on eligibility criteria. Binary mixtures and volatile organic compounds accounted for two-thirds of the chemical mixtures identified. The most common exposure route and modelled system were found to be inhalation and rats respectively. Twenty two (22) models were for binary mixtures, 5 for ternary mixtures, 3 for quaternary mixtures, and 5 for complex mixtures. Both bottom-up and top-down PBK modelling approaches are described. Whereas bottom-up approaches are based on a series of binary interactions, top-down approaches are based on the lumping of mixture components. Competitive inhibition is the most common type of interaction among the various types of mixtures, and usually becomes a concern at concentrations higher than environmental exposure levels. It leads to reduced biotransformation that either means a decrease in the amount of toxic metabolite formation or an increase in toxic parent chemical accumulation. The consequence is either lower or higher toxicity compared to that estimated for the mixture based on the additivity principle. Therefore, PBK modelling can play a central role in predicting interactions in chemical mixture risk assessment.

SUBMITTER: Desalegn A

PROVIDER: S-EPMC6559215 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Role of Physiologically Based Kinetic modelling in addressing environmental chemical mixtures - A review.

Desalegn Anteneh A Bopp Stephanie S Asturiol David D Lamon Lara L Worth Andrew A Paini Alicia A

Computational toxicology (Amsterdam, Netherlands) 20190501

The role of Physiologically Based Kinetic (PBK) modelling in assessing mixture toxicology has been growing for the last three decades. It has been widely used to investigate and address interactions in mixtures. This review describes the current state-of-the-art of PBK models for chemical mixtures and to evaluate the applications of PBK modelling for mixtures with emphasis on their role in chemical risk assessment. A total of 35 mixture PBK models were included after searching web resources (Sco ...[more]

PMID: 31218267

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Project description:BackgroundHumans are routinely and concurrently exposed to multiple toxic chemicals, including various metals and organics, often at levels that can cause adverse and potentially synergistic effects. However, toxicokinetic modeling studies of exposures to these chemicals are typically performed on a single chemical basis. Furthermore, the attributes of available models for individual chemicals are commonly estimated specifically for the compound studied. As a result, the available models usually have parameters and even structures that are not consistent or compatible across the range of chemicals of concern. This fact precludes the systematic consideration of synergistic effects, and may also lead to inconsistencies in calculations of co-occurring exposures and corresponding risks. There is a need, therefore, for a consistent modeling framework that would allow the systematic study of cumulative risks from complex mixtures of contaminants.MethodsA Generalized Toxicokinetic Modeling system for Mixtures (GTMM) was developed and evaluated with case studies. The GTMM is physiologically-based and uses a consistent, chemical-independent physiological description for integrating widely varying toxicokinetic models. It is modular and can be directly "mapped" to individual toxicokinetic models, while maintaining physiological consistency across different chemicals. Interaction effects of complex mixtures can be directly incorporated into the GTMM.ConclusionsThe application of GTMM to different individual metals and metal compounds showed that it explains available observational data as well as replicates the results from models that have been optimized for individual chemicals. The GTMM also made it feasible to model toxicokinetics of complex, interacting mixtures of multiple metals and nonmetals in humans, based on available literature information. The GTMM provides a central component in the development of a "source-to-dose-to-effect" framework for modeling population health risks from environmental contaminants. As new data become available on interactions of multiple chemicals, the GTMM can be iteratively parameterized to improve mechanistic understanding of human health risks from exposures to complex mixtures of chemicals.

Project description:Human biomonitoring (HBM) data can provide insight into co-exposure patterns resulting from exposure to multiple chemicals from various sources and over time. Therefore, such data are particularly valuable for assessing potential risks from combined exposure to multiple chemicals. One way to interpret HBM data is establishing safe levels in blood or urine, called Biomonitoring Equivalents (BE) or HBM health based guidance values (HBM-HBGV). These can be derived by converting established external reference values, such as tolerable daily intake (TDI) values. HBM-HBGV or BE values are so far agreed only for a very limited number of chemicals. These values can be established using physiologically based kinetic (PBK) modelling, usually requiring substance specific models and the collection of many input parameters which are often not available or difficult to find in the literature. The aim of this study was to investigate the suitability and limitations of generic PBK models in deriving BE values for several compounds with a view to facilitating the use of HBM data in the assessment of chemical mixtures at a screening level. The focus was on testing the methodology with two generic models, the IndusChemFate tool and High-Throughput Toxicokinetics package, for two different classes of compounds, phenols and phthalates. HBM data on Danish children and on Norwegian mothers and children were used to evaluate the quality of the predictions and to illustrate, by means of a case study, the overall approach of applying PBK models to chemical classes with HBM data in the context of chemical mixture risk assessment. Application of PBK models provides a better understanding and interpretation of HBM data. However, the study shows that establishing safety threshold levels in urine is a difficult and complex task. The approach might be more straightforward for more persistent chemicals that are analysed as parent compounds in blood but high uncertainties have to be considered around simulated metabolite concentrations in urine. Refining the models may reduce these uncertainties and improve predictions. Based on the experience gained with this study, the performance of the models for other chemicals could be investigated, to improve the accuracy of the simulations.

Project description:Pregnant women are usually excluded from clinical trials. Physiologically based pharmacokinetic (PBPK) modelling may provide a method to predict pharmacokinetics in pregnant women, without the need to perform extensive in vivo clinical trials. Here, we used mechanistic modelling to delineate the potential impact of drug transporters on darunavir pharmacokinetics and to identify current knowledge gaps that limit accurate PBPK modelling of darunavir/ritonavir (darunavir/r) exposure in pregnancy. Simcyp (version 13.2) was used for PBPK modelling, using physicochemical and in vitro pharmacokinetic parameters of darunavir and ritonavir from the literature. The Michaelis-Menten constant (K m) and the maximum rate of metabolite formation (V max) for cytochrome P450 3A4-mediated darunavir biotransformation and inhibition by ritonavir were determined experimentally, while the contributions of hepatocyte influx and efflux transporters were assessed by sensitivity analysis. The simulations were compared with previously published clinical pharmacokinetic data. We found that use of a well-stirred liver model overestimated darunavir exposure substantially. A permeability-limited liver model, including hepatic uptake and efflux transporters and an efficient enterohepatic circulation step, resulted in an acceptable description of darunavir/r exposure. For the 600/100 mg darunavir/r twice-daily dose and the 800/100 mg once-daily dose, the estimated pharmacokinetic parameters were within a 2-fold range of the reported data. The predicted decreases in the area under the concentration-time curve (AUC) values during pregnancy for the twice- and once-daily doses were 27 and 41%, respectively, which were in line with the observed decreases of 17-22 and 33%. In conclusion, our data support a clinically relevant role of hepatic transporters in darunavir pharmacokinetics. By including them in our model, we successfully approximated the increase in darunavir exposure mediated by ritonavir co-administration and the decrease in darunavir exposure observed during pregnancy.

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Role of Physiologically Based Kinetic modelling in addressing environmental chemical mixtures - A review.

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Role of Physiologically Based Kinetic modelling in addressing environmental chemical mixtures - A review.

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