Variability in urinary concentrations of primary aromatic amines

Chinthakindi, Sridhar; Kannan, Kurunthachalam

doi:10.1016/j.scitotenv.2022.154768

Cited by 9 publications

(7 citation statements)

References 33 publications

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“…The virtual oral doses used in this 28-day modeling were generated by reverse dosimetry based on the 50 th and 95 th percentile urinary levels from biomonitoring data. Reverse dosimetry analyses using the two human PBPK models to estimate the daily intake of aniline and 2,6-dimethylaniline based on reported human urinary concentrations of aniline and 2,6-dimethylaniline from biomonitoring data (Chinthakindi and Kannan, 2022b) are shown in Table 3. The repeated dose levels of aniline (11 and 26 µg/kg/day) and 2,6-dimethylaniline (8.3 and 29 µg/kg/day) were reversely calculated using the 50th and 95th percentiles of human urinary concentration levels of aniline (6.0 and 13.7 ng/mL) and 2,6-dimethylaniline (3.8 and 13.3 ng/mL) published in a biomonitoring report (Chinthakindi and Kannan, 2022b) (Table 3).…”

Section: Using Simplified Pbpk Models To Estimate the Pharmacokinetic...mentioning

confidence: 99%

“…Reverse dosimetry analyses using the two human PBPK models to estimate the daily intake of aniline and 2,6-dimethylaniline based on reported human urinary concentrations of aniline and 2,6-dimethylaniline from biomonitoring data (Chinthakindi and Kannan, 2022b) are shown in Table 3. The repeated dose levels of aniline (11 and 26 µg/kg/day) and 2,6-dimethylaniline (8.3 and 29 µg/kg/day) were reversely calculated using the 50th and 95th percentiles of human urinary concentration levels of aniline (6.0 and 13.7 ng/mL) and 2,6-dimethylaniline (3.8 and 13.3 ng/mL) published in a biomonitoring report (Chinthakindi and Kannan, 2022b) (Table 3). Modeling repeated daily administrations of aniline and 2,6-dimethylaniline indicated that exposures of aniline and 2,6-dimethylaniline should be apparent in humans (Fig.…”

Section: Using Simplified Pbpk Models To Estimate the Pharmacokinetic...mentioning

confidence: 99%

“…Aniline itself is produced globally on a large scale (e.g., 8.4 million tons in 2020) (Chinthakindi and Kannan, 2022a;Bugosen et al, 2020), although it reportedly has carcinogenic potential in humans. Nonetheless, the tolerable daily intake (TDI) value of aniline has been set by the United States Environmental Protection Agency at 7.0 µg/kg/day (Chinthakindi and Kannan, 2022b). Aniline and 2,6-dimethylaniline are both metabolized to hematotoxic N-hydroxylated metabolites and excretable glucuronide conjugates of their amino groups (Miura et al, 2021a;Lewalter and Korallus, 1985;Gonçalves et al, 2001).…”

Section: Introductionmentioning

confidence: 99%

“…These aromatic amines can migrate from food contact materials such as containers, packaging, cutlery, and kitchen equipment (Chinthakindi and Kannan, 2022a;Perez et al, 2019). Among several aromatic amines, aniline and 2,6-dimethylaniline have been commonly detected in urine samples from humans (Chinthakindi and Kannan, 2022b), dogs, and cats (Chinthakindi and Kannan, 2022a) and in feces from dogs and cats (Chinthakindi and Kannan, 2022a).…”

Section: Introductionmentioning

confidence: 99%

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Forward and reverse dosimetry for aniline and 2,6-dimethylaniline in humans extrapolated from humanized-liver mouse data using simplified physiologically based pharmacokinetic models

et al. 2022

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Although human urinary aniline and 2,6-dimethylaniline were unexpectedly detected in biomonitoring data, little is known about the daily intake doses of aniline and 2,6-dimethylaniline in the living environment or their relation to tolerable daily intake (TDI) values in humans. In the current study, to evaluate the daily oral intake of aniline and 2,6-dimethylaniline in humans, forward and reverse dosimetry was carried out using simplified in silico physiologically based pharmacokinetic (PBPK) modeling established using in vivo experimental pharmacokinetic data. These data were from humanized-liver mice after single oral doses of 100 mg/kg aniline (previously determined) and 116 mg/kg 2,6-dimethylanine (currently investigated). The in vivo elimination rates of 2,6-dimethylaniline from plasma in humanized-liver mice were generally slow compared with those of aniline. Faster in vitro metabolic elimination rates of aniline mediated by liver 9000 × g supernatant fractions from rats than those from humans may suggest the existence of higher first-pass effects in rats than in humanized-liver mice. In silico aniline and 2,6-dimethylaniline concentration curves in human urine after virtual oral administrations were estimated by human PBPK models created with data from humanized-liver mice. Reverse dosimetry analysis using human PBPK models estimated the daily intake of aniline, based on reported human urinary concentrations in biomonitoring data, to be roughly similar to the aniline TDI level. These results suggest that forward and reverse dosimetry using simplified human PBPK models founded on data from humanized-liver mice can be used to evaluate possible higher than expected exposures of aniline and 2,6-dimethylaniline in humans.

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Section: Using Simplified Pbpk Models To Estimate the Pharmacokinetic...mentioning

confidence: 99%

Section: Using Simplified Pbpk Models To Estimate the Pharmacokinetic...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Forward and reverse dosimetry for aniline and 2,6-dimethylaniline in humans extrapolated from humanized-liver mouse data using simplified physiologically based pharmacokinetic models

et al. 2022

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“…8,9) Simplified PBPK models that use some fixed physiological system parameters are easier to handle than full PBPK models and are of use in the fields of drug discovery, poisoning, or therapeutic drug monitoring 7,[10][11][12] as well as in risk assessment for a variety of general chemicals or food components/additives. 13) Although the metabolic profiles of disparate chemicals (including aromatic amines 14,15) ) traditionally have been elucidated in rodent studies, 16) so-called new alternative methods (NAMs) for evaluating chemical safety have been widely investigated using in silico or in vitro approaches. 17,18) The approach that applies simple PBPK modeling, without any reference to experimental pharmacokinetic data, has the potential to play significant roles in replacing and reducing the use of animals for estimating toxicokinetics or internal exposures of drugs, food components, and general chemicals.…”

Section: Introductionmentioning

confidence: 99%

Updated <i>in Silico</i> Prediction Methods for Fractions Absorbed and Key Input Parameters of 355 Disparate Chemicals for Physiologically Based Pharmacokinetic Models for Time-Dependent Plasma Concentrations after Virtual Oral Doses in Humans

Adachi

Shimizu

Yamazaki

2022

Biological & Pharmaceutical Bulletin

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Human metabolic profiles for substances such as toxic food-derived compounds are usually allometrically extrapolated from traditionally determined in vivo rat concentration profiles. To evaluate internal exposures in humans without any reference to experimental data, physiologically based pharmacokinetic (PBPK) modeling could be used if the model input parameters could be estimated in silico. This approach would simplify the use of PBPK models for forward dosimetry after oral doses. In this study, the in silico estimation of input parameters for PBPK models (i.e., fraction absorbed × intestinal availability, absorption rate constants, and volumes of the systemic circulation) was updated for an panel of 355 chemicals (212 previously analyzed and 143 additional substances) using a light gradient boosting machine learning algorithms (LightGBM) based on between 11 and 29 in silico-calculated chemical descriptors.Simplified human PBPK models were then used to calculate virtual maximum plasma concentrations (Cmax) and areas under the concentration-time curve (AUC) based on two sets of input parameters, i.e., traditionally derived values from in vivo data and those calculated in silico using the current updated systems. Both sets of Cmax and AUC data were well correlated (r = 0.87 and r = 0.73, respectively; p < 0.01, n = 355). Therefore, input parameters for human PBPK models for a diverse range of compounds could be successfully estimated using chemical descriptors and in silico tools. This approach to pharmacokinetic modeling has potential for application in computational toxicology and in the clinical setting for assessing the potential risk of general chemicals.

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Development of a TiO2 nanotube photoanode decorated with MIL-53(Fe) for the photoelectrochemical degradation of 2,4-dimethylaniline

da Silva,

Cavalheri,

Cardoso

et al. 2024

Catalysis Today

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Variability in urinary concentrations of primary aromatic amines

Cited by 9 publications

References 33 publications

Forward and reverse dosimetry for aniline and 2,6-dimethylaniline in humans extrapolated from humanized-liver mouse data using simplified physiologically based pharmacokinetic models

Forward and reverse dosimetry for aniline and 2,6-dimethylaniline in humans extrapolated from humanized-liver mouse data using simplified physiologically based pharmacokinetic models

Updated <i>in Silico</i> Prediction Methods for Fractions Absorbed and Key Input Parameters of 355 Disparate Chemicals for Physiologically Based Pharmacokinetic Models for Time-Dependent Plasma Concentrations after Virtual Oral Doses in Humans

Development of a TiO2 nanotube photoanode decorated with MIL-53(Fe) for the photoelectrochemical degradation of 2,4-dimethylaniline

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