Physiologically Based Modeling of Pharmacokinetic Interactions in Chemical Mixtures

Haddad, Sami; Tardif, Robert; Boyd, Jonathan; Krishnan, Kannan

doi:10.1002/9780470686263.ch4

Cited by 5 publications

(13 citation statements)

References 52 publications

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“…For the purpose of the current study, these models were modified according to Haddad et al (2010) in order to simulate simultaneous (Lipscomb and Poet, 2008) was used and assumed to be comparable across subpopulations, given the lack of data suggesting otherwise. e Same as for adults.…”

Section: Pbpk Modelsmentioning

confidence: 99%

“…However, toxicological guidelines are determined on the basis of data that are generally obtained in studies that consider singlechemical exposures (Haddad et al, 2010). The possible consequences to human health of exposure to multiple chemicals have yielded a growing concern in the public and scientific community (Lampa et al, 2014;Boobis et al, 2011;Meek et al, 2011;Mumtaz et al, 2004Mumtaz et al, , 2007.…”

mentioning

confidence: 99%

“…In some cases, this approach allowed the proposition of threshold concentrations in the media for metabolic interactions (Dobrev et al, 2001(Dobrev et al, , 2002. Accounting for metabolic interactions in a PBPK model requires modification of differential equations representing metabolism in order to reflect every binary interaction occurring between all components of a given mixture (Haddad et al, 2010). For distinct chemicals that are substrates of the same biotransformation enzymes, such as volatile organic compounds (VOC) with regard to cytochrome P-450 (CYP) 2E1 (Ronis et al, 1996), such interactions are often presumed to occur via competitive inhibition of their metabolism (Haddad et al, 2010).…”

mentioning

confidence: 99%

“…Accounting for metabolic interactions in a PBPK model requires modification of differential equations representing metabolism in order to reflect every binary interaction occurring between all components of a given mixture (Haddad et al, 2010). For distinct chemicals that are substrates of the same biotransformation enzymes, such as volatile organic compounds (VOC) with regard to cytochrome P-450 (CYP) 2E1 (Ronis et al, 1996), such interactions are often presumed to occur via competitive inhibition of their metabolism (Haddad et al, 2010). This type of interaction results from two chemicals (i.e., two substrates or one substrate and one strict inhibitor) competing for the same active site of the enzyme.…”

mentioning

confidence: 99%

See 3 more Smart Citations

Assessing Human Variability in Kinetics for Exposures to Multiple Environmental Chemicals: A Physiologically Based Pharmacokinetic Modeling Case Study with Dichloromethane, Benzene, Toluene, Ethylbenzene, andm-Xylene

Valcke

Haddad

2015

Journal of Toxicology and Environmental Health, Part A

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The objective of this study was to compare the magnitude of interindividual variability in internal dose for inhalation exposure to single versus multiple chemicals. Physiologically based pharmacokinetic models for adults (AD), neonates (NEO), toddlers (TODD), and pregnant women (PW) were used to simulate inhalation exposure to "low" (RfC-like) or "high" (AEGL-like) air concentrations of benzene (Bz) or dichloromethane (DCM), along with various levels of toluene alone or toluene with ethylbenzene and xylene. Monte Carlo simulations were performed and distributions of relevant internal dose metrics of either Bz or DCM were computed. Area under the blood concentration of parent compound versus time curve (AUC)-based variability in AD, TODD, and PW rose for Bz when concomitant "low" exposure to mixtures of increasing complexities occurred (coefficient of variation (CV) = 16-24%, vs. 12-15% for Bz alone), but remained unchanged considering DCM. Conversely, AUC-based CV in NEO fell (15 to 5% for Bz; 12 to 6% for DCM). Comparable trends were observed considering production of metabolites (AMET), except for NEO's CYP2E1-mediated metabolites of Bz, where an increased CV was observed (20 to 71%). For "high" exposure scenarios, Cmax-based variability of Bz and DCM remained unchanged in AD and PW, but decreased in NEO (CV= 11-16% to 2-6%) and TODD (CV= 12-13% to 7-9%). Conversely, AMET-based variability for both substrates rose in every subpopulation. This study analyzed for the first time the impact of multiple exposures on interindividual variability in toxicokinetics. Evidence indicates that this impact depends upon chemical concentrations and biochemical properties, as well as the subpopulation and internal dose metrics considered.

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Section: Pbpk Modelsmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Assessing Human Variability in Kinetics for Exposures to Multiple Environmental Chemicals: A Physiologically Based Pharmacokinetic Modeling Case Study with Dichloromethane, Benzene, Toluene, Ethylbenzene, andm-Xylene

Valcke

Haddad

2015

Journal of Toxicology and Environmental Health, Part A

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“…Such interactions may affect the relationship between the exposed dose and the dose delivered to the target site and thereby the resulting adverse effects. 18,19 The work presented here is intended to explore the possibilities and limitations in using such models for risk assessment by a specific case study of tebuconazole, including exploring the influence of inhibition between R(−) and S(+) enantiomers of this compound.By performing low-dose computational simulations in humans, PBTK modeling can provide information not otherwise available. Interspecies differences can be simulated by developing models for the same chemical in different species, for example, rats and humans, and using interspecies extrapolation of parameters from one species to another when necessary and feasible.…”

mentioning

confidence: 99%

Physicologically Based Toxicokinetic Models of Tebuconazole and Application in Human Risk Assessment

Jónsdóttir

Reffstrup

Petersen

et al. 2016

Chem. Res. Toxicol.

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A series of physiologically based toxicokinetic (PBTK) models for tebuconazole were developed in four species, rat, rabbit, rhesus monkey, and human. The developed models were analyzed with respect to the application of the models in higher tier human risk assessment, and the prospect of using such models in risk assessment of cumulative and aggregate exposure is discussed. Relatively simple and biologically sound models were developed using available experimental data as parameters for describing the physiology of the species, as well as the absorption, distribution, metabolism, and elimination (ADME) of tebuconazole. The developed models were validated on in vivo half-life data for rabbit with good results, and on plasma and tissue concentration-time course data of tebuconazole after i.v. administration in rabbit. In most cases, the predicted concentration levels were seen to be within a factor of 2 compared to the experimental data, which is the threshold set for the use of PBTK simulation results in risk assessment. An exception to this was seen for one of the target organs, namely, the liver, for which tebuconazole concentration was significantly underestimated, a trend also seen in model simulations for the liver after other nonoral exposure scenarios. Possible reasons for this are discussed in the article. Realistic dietary and dermal exposure scenarios were derived based on available exposure estimates, and the human version of the PBTK model was used to simulate the internal levels of tebuconazole and metabolites in the human body for these scenarios. By a variant of the models where the R(-)- and S(+)-enantiomers were treated as two components in a binary mixture, it was illustrated that the inhibition between the two tebuconazole enantiomers did not affect the simulation results for these realistic exposure scenarios. The developed models have potential as an important tool in risk assessment.

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An assessment of the impact of multi‐route co‐exposures on human variability in toxicokinetics: A case study with binary and quaternary mixtures of volatile drinking water contaminants

Tohon

Valcke

Haddad

2019

J of Applied Toxicology

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This study aimed to assess the impact of multi‐route co‐exposures to chemicals on interindividual variability in toxicokinetics. Probabilistic physiologically based pharmacokinetic multi‐route interaction models were developed for adults and four younger subpopulations. Drinking water‐mediated multi‐route exposures were simulated for benzene alone or in co‐exposure with toluene, ethylbenzene and m‐xylene, for trichloroethylene or vinyl chloride (VC), alone and in mixture. These simulations were performed for “low” and “high” exposure scenarios, involving respectively the US EPA's short‐term drinking water health advisories, and 10 times these advisory values. Distributions of relevant internal dose metrics for benzene, trichloroethylene and VC were obtained using Monte Carlo simulations. Intergroup variability indexes (VI) were computed for the “low” (VIL) and “high” (VIH) exposure scenarios, as the ratio between the 95th percentile in each subpopulation over the median in adults. Thus, for benzene, parent compound's area under the curve‐based VIL for single exposures vs. co‐exposures correspondingly varied between 1.7 (teenagers) and 2.8 (infants) vs. 1.9 and 3.1 respectively. VIH varied between 2.5 and 3.5 vs. 2.9 and 4.1. Inversely, VIL and VIH for the amount of benzene metabolized via CYP2E1 pathway decreased in co‐exposure compared to single exposure. For VC and trichloroethylene, similar results were obtained for the “high” exposure, but “low” co‐exposures did not impact the toxicokinetics of individual substances. In conclusion, multi‐route co‐exposures can have an impact on the toxicokinetics of individual substances, but to an extent, that does not seem to challenge the default values attributed to the factors deemed at reflecting interindividual or child/adult differences in toxicokinetics.

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Physiologically Based Modeling of Pharmacokinetic Interactions in Chemical Mixtures

Cited by 5 publications

References 52 publications

Assessing Human Variability in Kinetics for Exposures to Multiple Environmental Chemicals: A Physiologically Based Pharmacokinetic Modeling Case Study with Dichloromethane, Benzene, Toluene, Ethylbenzene, andm-Xylene

Assessing Human Variability in Kinetics for Exposures to Multiple Environmental Chemicals: A Physiologically Based Pharmacokinetic Modeling Case Study with Dichloromethane, Benzene, Toluene, Ethylbenzene, andm-Xylene

Physicologically Based Toxicokinetic Models of Tebuconazole and Application in Human Risk Assessment

An assessment of the impact of multi‐route co‐exposures on human variability in toxicokinetics: A case study with binary and quaternary mixtures of volatile drinking water contaminants

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