Evaluation of the impact of the exposure route on the human kinetic adjustment factor

Evaluation of models for predicting pediatric fraction unbound in plasma for human health risk assessment

Pediatric physiologically based pharmacokinetic (PBPK) models facilitate the prediction of PK parameters in children under specific exposure conditions. Pharmacokinetic outcomes are highly sensitive to fraction unbound in plasma (fup) as incorporated into PBPK models. Rarely is fup in children (fup_child) experimentally derived and prediction is based upon fup in adults (fup_adult) as well as a ratio of plasma protein concentrations between children and adults. The objectives were to (i) evaluate protein concentration vs. age profile derived from ontogeny models, (ii) assess predictive performances of fup ontogeny models, and (iii) determine overall uncertainty in fup_child prediction resulting from a combination of quantitative structure-property relationship (QSPR) model and ontogeny models. The plasma albumin and alpha-acid glycoprotein (AAG) concentration data for pediatrics and fup_child and fup_adult data were obtained from literature. The protein concentration vs. age profile derived from ontogeny models were compared to observed levels. Fup_child values were calculated according to ontogeny models using both observed and QSPR-predicted fup_adult as inputs and predictive performances of ontogeny models assessed by comparing predicted fup_child to observed values. Protein concentrations vs. age profiles derived from non-linear equations were more congruent with observed albumin levels than linear or step-wise models. When observed fup_adult values were used as input, the fup_child data were under-predicted with average fold error (AFE) amounts ranging 0.79-0.81 and 0.77-0.97 for albumin and AAG ontogeny models, respectively. When QSPR-predicted fup_adult values were used as input, AFE of fup_child ranged 1.2-1.35 and 0.98-1.2 for albumin and AAG models, respectively. The choice of ontogeny model with respect to prediction accuracy is more important for AAG, highly bound compounds and infants. For these compounds and scenarios, experimental determination of fup_child for inclusion into a pediatric PBPK model is necessary to have confidence in PBPK model outputs.

Estimation of toluene exposure in air from BMA (S-benzylmercapturic acid) urinary measures using a reverse dosimetry approach based on physiologically pharmacokinetic modeling

This study aimed to use a reverse dosimetry PBPK modeling approach to estimate toluene atmospheric exposure from urinary measurements of S-benzylmercapturic acid (BMA) in a small group of individuals and to evaluate the uncertainty associated to urinary spot-sampling compared to 24-h collected urine samples. Each exposure assessment technique was developed namely to estimate toluene air exposure from BMA measurements in 24-h urine samples (24-h-BMA) and from distributions of daily urinary BMA spot measurements (DUBSM). Model physiological parameters were described based upon age, weight, size and sex. Monte Carlo simulations with the PBPK model allowed converting DUBSM distribution (and 24-h-BMA) into toluene air levels. For the approach relying on DUBSM distribution, the ratio between the 95% probability of predicted toluene concentration and its 50% probability in each individual varied between 1.2 and 1.4, while that based on 24-h-BMA varied between 1.0 and 1.1. This suggests more variability in estimated exposure from spot measurements. Thus, estimating toluene exposure based on DUBSM distribution generated about 20% more uncertainty. Toluene levels estimated (0.0078-0.0138 ppm) are well below Health Canada's maximum chronic air guidelines. PBPK modeling and reverse dosimetry may be combined to interpret urinary metabolites data of VOCs and assess related uncertainties.

Assessing the impacts on fetal dosimetry of the modelling of the placental transfers of xenobiotics in a pregnancy physiologically based pharmacokinetic model

The developmental origin of health and diseases theory supports the critical role of the fetal exposure to children's health. We developed a physiologically based pharmacokinetic model for human pregnancy (pPBPK) to simulate the maternal and fetal dosimetry throughout pregnancy. Four models of the placental exchanges of chemicals were assessed on ten chemicals for which maternal and fetal data were available. These models were calibrated using non-animal methods: in vitro (InV) or ex vivo (ExV) data, a semi-empirical relationship (SE), or the limitation by the placental perfusion (PL). They did not impact the maternal pharmacokinetics but provided different profiles in the fetus. The PL and InV models performed well even if the PL model overpredicted the fetal exposure for some substances. The SE and ExV models showed the lowest global performance and the SE model a tendency to underprediction. The comparison of the profiles showed that the PL model predicted an increase in the fetal exposure with the pregnancy age, whereas the ExV model predicted a decrease. For the SE and InV models, a small decrease was predicted during the second trimester. All models but the ExV one, presented the highest fetal exposure at the end of the third trimester. Global sensitivity analyses highlighted the predominant influence of the placental transfers on the fetal exposure, as well as the metabolic clearance and the fraction unbound. Finally, the four transfer models could be considered depending on the framework of the use of the pPBPK model and the availability of data or resources to inform their parametrization.

Development of a generic lifelong physiologically based biokinetic model for exposome studies

The current study within the frame of the HEALS project aims at the development of a lifelong physiologically based biokinetic (PBBK) model for exposome studies. The aim was to deliver a comprehensive modelling framework for addressing a large chemical space. Towards this aim, the delivered model can easily adapt parameters from existing ad-hoc models or complete the missing compound specific parameters using advanced quantitative structure activity relationship (QSAR). All major human organs are included, as well as arterial, venous, and portal blood compartments. Xenobiotics and their metabolites are linked through the metabolizing tissues. This is mainly the liver, but also other sites of metabolism might be considered (intestine, brain, skin, placenta) based on the presence or not of the enzymes involved in the metabolism of the compound of interest. Each tissue is described by three mass balance equations for (a) red blood cells, (b) plasma and interstitial tissue and (c) cells respectively. The anthropometric parameters of the models are time dependent, so as to provide a lifetime internal dose assessment, as well as to describe the continuously changing physiology of the mother and the developing fetus. An additional component of flexibility is that the biokinetic processes that relate to metabolism are related with either Michaelis-Menten kinetics, as well as intrinsic clearance kinetics. The capability of the model is demonstrated in the assessment of internal exposure and the prediction of expected biomonitored levels in urine for three major compounds within the HEALS project, namely bisphenol A (BPA), Bis(2-ethylhexyl) phthalate (DEHP) and cadmium (Cd). The results indicated that the predicted urinary levels fit very well with the ones from human biomonitoring (HBM) studies; internal exposure to plasticizers is very low (in the range of ng/L), while internal exposure to Cd is in the range of μg/L.

Critical assessment and integration of separate lines of evidence for risk assessment of chemical mixtures

Humans are exposed to multiple chemicals on a daily basis instead of to just a single chemical, yet the majority of existing toxicity data comes from single-chemical exposure. Multiple factors must be considered such as the route, concentration, duration, and the timing of exposure when determining toxicity to the organism. The need for adequate model systems (in vivo, in vitro, in silico and mathematical) is paramount for better understanding of chemical mixture toxicity. Currently, shortcomings plague each model system as investigators struggle to find the appropriate balance of rigor, reproducibility and appropriateness in mixture toxicity studies. Significant questions exist when comparing single-to mixture-chemical toxicity concerning additivity, synergism, potentiation, or antagonism. Dose/concentration relevance is a major consideration and should be subthreshold for better accuracy in toxicity assessment. Previous work was limited by the technology and methodology of the time, but recent advances have resulted in significant progress in the study of mixture toxicology. Novel technologies have added insight to data obtained from in vivo studies for predictive toxicity testing. These include new in vitro models: omics-related tools, organs-on-a-chip and 3D cell culture, and in silico methods. Taken together, all these modern methodologies improve the understanding of the multiple toxicity pathways associated with adverse outcomes (e.g., adverse outcome pathways), thus allowing investigators to better predict risks linked to exposure to chemical mixtures. As technology and knowledge advance, our ability to harness and integrate separate streams of evidence regarding outcomes associated with chemical mixture exposure improves. As many national and international organizations are currently stressing, studies on chemical mixture toxicity are of primary importance.

Model qualification of the PK-Sim® pediatric module for pediatric exposure assessment of CYP450 metabolized compounds

Pediatric physiologically based pharmacokinetic (PBPK) models facilitate the estimation of pharmacokinetic (PK) parameters in children under specific exposure conditions. In human health risk assessment, PBPK modeling has been used to determine a chemical-specific human kinetic adjustment factor (HKAF). Due to increased demands in regulatory assessment, model evaluation and qualification have gained growing attention. The aim of this study was to undertake model qualification of pediatric PBPK models for compounds that are primarily metabolized by cytochrome P450 (CYP) enzymes. The objectives were to determine the appropriateness of the virtual individual creating algorithm in PK-Sim® in predicting PK parameters and their variability in children and identify critical system-specific inputs. PBPK models in adults were constructed for several pharmaceuticals (grouped by major clearance process such as CYP3A4). Several age groups of virtual individuals were created to represent children in pediatric clinical studies. The mean and variance of clearance (CL) from virtual populations were compared to observed values. Sensitivity analysis on area under the curve (AUC) was performed. System-specific parameters of virtual children that contribute to inter-individual PK properties were assessed. Eighty-one percent of the comparisons between simulated and observed clearance values were within twofold error. The mean fold errors were 1.1, 1, 0.7 and 1.8 in adolescents, children, infants and neonates, respectively. CL variability was reasonably predicted for 70% of the comparisons with comparable coefficients of variation between observed and predicted. The sensitivity analysis revealed that fraction unbound in plasma, parameters related to CYP enzyme-mediated metabolism and liver volumewere most important in the estimation of pediatric exposure. A comparison of variabilities in weight, height and liver volume in virtual children showed reliable agreement with observed data. The presented results of predictive performance and properties of virtual populations provide confidence in the use of PK-Sim for pediatric PBPK modeling in toxicological applications including PBPK-based-HKAF derivation.

Physiology-based toxicokinetic modelling in the frame of the European Human Biomonitoring Initiative

Given the opportunities provided by internal dosimetry modelling in the interpretation of human biomonitoring (HBM) data, the assessment of the links between exposure to chemicals and observed HBM data can be effectively supported by PBTK modelling. This paper gives a comprehensive review of available human PBTK models for compounds selected as a priority by the European Human Biomonitoring Initiative (HBM4EU). We highlight their advantages and deficiencies and suggest steps for advanced internal dose modelling. The review of the available PBTK models highlighted the conceptual differences between older models compared to the ones developed recently, reflecting commensurate differences in research questions. Due to the lack of coordinated strategies for deriving useful biomonitoring data for toxicokinetic properties, significant problems in model parameterisation still remain; these are further increased by the lack of human toxicokinetic data due to ethics issues. Finally, questions arise as well as to the extent they are really representative of interindividual variability. QSARs for toxicokinetic properties is a complementary approach for PBTK model parameterisation, especially for data poor chemicals. This approach could be expanded to model chemico-biological interactions such as intestinal absorption and renal clearance; this could serve the development of more complex generic PBTK models that could be applied to newly derived chemicals. Another gap identified is the framework for mixture interaction terms among compounds that could eventually interact in metabolism. From the review it was concluded that efforts should be shifted toward the development of generic multi-compartmental and multi-route models, supported by targeted biomonitoring coupled with parameterisation by both QSAR approach and experimental (in-vivo and in-vitro) data for newly developed and data poor compounds.

Reverse dosimetry modeling of toluene exposure concentrations based on biomonitoring levels from the Canadian health measures survey

Biomonitoring might provide useful estimates of population exposure to environmental chemicals. However, data uncertainties stemming from interindividual variability are common in large population biomonitoring surveys. Physiologically based pharmacokinetic (PBPK) models might be used to account for age- and gender-related variability in internal dose. The objective of this study was to reconstruct air concentrations consistent with blood toluene measures reported in the third Canadian Health Measures Survey using reverse dosimetry PBPK modeling techniques. Population distributions of model's physiological parameters were described based upon age, weight, and size for four subpopulations (12-19, 20-39, 40-59, and 60-79 years old). Monte Carlo simulations applied to PBPK modeling allowed converting the distributions of venous blood measures of toluene obtained from CHMS into related air levels. Based upon blood levels observed at the 50^th, 90^th and 95^th percentiles, corresponding air toluene concentrations were estimated for teenagers aged 12-19 years as being, respectively, 0.009, 0.04 and 0.06 ppm. Similarly, values were computed for adults aged 20-39 years (0.007, 0.036, and 0.06 ppm), 40-59 years (0.007, 0.036 and 0.06 ppm) and 60-79 years (0.006, 0.022 and 0.04 ppm). These estimations are well below Health Canada's maximum recommended chronic air guidelines for toluene. In conclusion, PBPK modeling and reverse dosimetry may be combined to help interpret biomonitoring data for chemical exposure in large population surveys and estimate the associated toxicological health risk.

A Physiologically-Based Pharmacokinetic Modeling Approach Using Biomonitoring Data in Order to Assess the Contribution of Drinking Water for the Achievement of an Optimal Fluoride Dose for Dental Health in Children

Due to an optimal fluoride concentration in drinking water advised for caries prevention purposes, the population is now exposed to multiple sources of fluoride. The availability of population biomonitoring data currently allow us to evaluate the magnitude of this exposure. The objective of this work was, therefore, to use such data in order to estimate whether community water fluoridation still represents a significant contribution toward achieving a suggested daily optimal fluoride (external) intake of 0.05 mg/kg/day. Therefore, a physiologically-based pharmacokinetic model for fluoride published in the literature was used and adapted in Excel for a typical 4-year-old and 8-year-old child. Biomonitoring data from the Canadian Health Measures Survey among people living in provinces with very different drinking water fluoridation coverage (Quebec, 2.5%; Ontario, 70% of the population) were analyzed using this adapted model. Absorbed doses for the 4-year-old and 8-year-old children were, respectively, 0.03 mg/kg/day and 0.02 mg/kg/day in Quebec and of 0.06 mg/kg/day and 0.05 mg/kg/day in Ontario. These results show that community water fluoridation contributes to increased fluoride intake among children, which leads to reaching, and in some cases even exceeding, the suggested optimal absorbed dose of 0.04 mg/kg/day, which corresponds to the suggested optimal fluoride intake mentioned above. In conclusion, this study constitutes an incentive to further explore the multiple sources of fluoride intake and suggests that a new balance between them including drinking water should be examined in accordance with the age-related physiological differences that influence fluoride metabolism.

Hair nicotine levels in children with bronchopulmonary dysplasia

BACKGROUND

Tobacco smoke exposure (TSE) may increase respiratory morbidities in young children with bronchopulmonary dysplasia (BPD). Rapid respiratory rates, close proximity to a smoking caregiver, and increased dermal absorption of tobacco smoke components can contribute to systemic exposure. In this study, hair nicotine levels were used as a biomarker of chronic TSE in young children with BPD to determine if hair nicotine levels correlate with caregiver self-report of TSE and respiratory morbidities.

METHODS

From 2012 to 2014, hair nicotine levels were measured from consecutive children seen in a BPD outpatient clinic and compared with caregiver questionnaires on household smoking. The relationship between respiratory morbidities and self-reported TSE or hair nicotine level was assessed.

RESULTS

The mean hair nicotine level from 117 children was 3.1 ± 13.2 ng/mg. Hair nicotine levels were significantly higher in children from smoking households by caregiver self-report compared with caregivers who reported no smoking (8.2 ± 19.7 ng/mg vs 1.8 ± 10.7; P < .001). In households that reported smoking, hair nicotine levels were higher in children with a primary caregiver who smoked compared with a primary caregiver who did not smoke. Among children with BPD who required respiratory support (n = 50), a significant association was found between higher log hair nicotine levels and increased hospitalizations and limitation of activity.

CONCLUSIONS

Chronic TSE is common in children with BPD, with hair nicotine levels being more likely to detect TSE than caregiver self-report. Hair nicotine levels were also a better predictor of hospitalization and activity limitation in children with BPD who required respiratory support at outpatient presentation.

The effects of electronic cigarette emissions on systemic cotinine levels, weight and postnatal lung growth in neonatal mice

Background/Objective

Electronic cigarette (E-cigarettes) emissions present a potentially new hazard to neonates through inhalation, dermal and oral contact. Exposure to nicotine containing E-cigarettes may cause significant systemic absorption in neonates due to the potential for multi-route exposure. Systemic absorption of nicotine and constituents of E-cigarette emissions may adversely impact weight and lung development in the neonate. To address these questions we exposed neonatal mice to E-cigarette emissions and measured systemic cotinine levels and alveolar lung growth.

Methods/Main Results

Neonatal mice were exposed to E-cigarettes for the first 10 days of life. E-cigarette cartridges contained either 1.8% nicotine in propylene glycol (PG) or PG vehicle alone. Daily weights, plasma and urine cotinine levels and lung growth using the alveolar mean linear intercept (MLI) method were measured at 10 days of life and compared to room air controls. Mice exposed to 1.8% nicotine/PG had a 13.3% decrease in total body weight compared to room air controls. Plasma cotinine levels were found to be elevated in neonatal mice exposed to 1.8% nicotine/PG E-cigarettes (mean 62.34± 3.3 ng/ml). After adjusting for sex and weight, the nicotine exposed mice were found to have modestly impaired lung growth by MLI compared to room air control mice (p<.054 trial 1; p<.006 trial 2). These studies indicate that exposure to E-cigarette emissions during the neonatal period can adversely impact weight gain. In addition exposure to nicotine containing E-cigarettes can cause detectable levels of systemic cotinine, diminished alveolar cell proliferation and a modest impairment in postnatal lung growth.

Electronic cigarette use and exposure in the pediatric population

Electronic cigarette (e-cigarette) use has gained recent widespread popularity and acceptance in the general population. What effect e-cigarettes may have on pediatric health remains unknown. Although many jurisdictions have laws that prevent the sale of e-cigarettes to minors and the use of e-cigarettes in public places, infants, children, and adolescents are increasingly exposed to them. In this pediatric-focused review, we discuss the history of these devices, user demographics, known health effects, and current legislative efforts to protect minors from exposure.

Assessing human variability in kinetics for exposures to multiple environmental chemicals: a physiologically based pharmacokinetic modeling case study with dichloromethane, benzene, toluene, ethylbenzene, and m-xylene

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.

Physiological daily inhalation rates for health risk assessment in overweight/obese children, adults, and elderly

Physiological daily inhalation rates reported in our previous study for normal-weight subjects 2.6-96 years old were compared to inhalation data determined in free-living overweight/obese individuals (n = 661) aged 5-96 years. Inhalation rates were also calculated in normal-weight (n = 408), overweight (n = 225), and obese classes 1, 2, and 3 adults (n = 134) aged 20-96 years. These inhalation values were based on published indirect calorimetry measurements (n = 1,069) and disappearance rates of oral doses of water isotopes (i.e., (2)H2 O and H2 (18)O) monitored by gas isotope ratio mass spectrometry usually in urine samples for an aggregate period of over 16,000 days. Ventilatory equivalents for overweight/obese subjects at rest and during their aggregate daytime activities (28.99 ± 6.03 L to 34.82 ± 8.22 L of air inhaled/L of oxygen consumed; mean ± SD) were determined and used for calculations of inhalation rates. The interindividual variability factor calculated as the ratio of the highest 99th percentile to the lowest 1st percentile of daily inhalation rates is higher for absolute data expressed in m3 /day (26.7) compared to those of data in m3/kg-day (12.2) and m3/m2-day (5.9). Higher absolute rates generally found in overweight/obese individuals compared to their normal-weight counterparts suggest higher intakes of air pollutants (in μg/day) for the former compared to the latter during identical exposure concentrations and conditions. Highest absolute mean (24.57 m3/day) and 99th percentile (55.55 m3 /day) values were found in obese class 2 adults. They inhale on average 8.21 m3 more air per day than normal-weight adults.

Characterization of the human kinetic adjustment factor for the health risk assessment of environmental contaminants

A default uncertainty factor of 3.16 (√10) is applied to account for interindividual variability in toxicokinetics when performing non-cancer risk assessments. Using relevant human data for specific chemicals, as WHO/IPCS suggests, it is possible to evaluate, and replace when appropriate, this default factor by quantifying chemical-specific adjustment factors for interindividual variability in toxicokinetics (also referred to as the human kinetic adjustment factor, HKAF). The HKAF has been determined based on the distributions of pharmacokinetic parameters (e.g., half-life, area under the curve, maximum blood concentration) in relevant populations. This article focuses on the current state of knowledge of the use of physiologically based algorithms and models in characterizing the HKAF for environmental contaminants. The recent modeling efforts on the computation of HKAF as a function of the characteristics of the population, chemical and its mode of action (dose metrics), as well as exposure scenario of relevance to the assessment are reviewed here. The results of these studies, taken together, suggest the HKAF varies as a function of the sensitive subpopulation and dose metrics of interest, exposure conditions considered (route, duration, and intensity), metabolic pathways involved and theoretical model underlying its computation. The HKAF seldom exceeded the default value of 3.16, except in very young children (i.e., <≈ 3 months) and when the parent compound is the toxic moiety. Overall, from a public health perspective, the current state of knowledge generally suggest that the default uncertainty factor is sufficient to account for human variability in non-cancer risk assessments of environmental contaminants.

Studying permethrin exposure in flight attendants using a physiologically based pharmacokinetic model

Assessment of potential health risks to flight attendants from exposure to pyrethroid insecticides, used for aircraft disinsection, is limited because of (a) lack of information on exposures to these insecticides, and (b) lack of tools for linking these exposures to biomarker data. We developed and evaluated a physiologically based pharmacokinetic (PBPK) model to assess the exposure of flight attendants to the pyrethroid insecticide permethrin attributable to aircraft disinsection. The permethrin PBPK model was developed by adapting previous models for pyrethroids, and was parameterized using currently available metabolic parameters for permethrin. The human permethrin model was first evaluated with data from published human studies. Then, it was used to estimate urinary metabolite concentrations of permethrin in flight attendants who worked in aircrafts, which underwent residual and pre-flight spray treatments. The human model was also applied to analyze the toxicokinetics following permethrin exposures attributable to other aircraft disinsection scenarios. Predicted levels of urinary 3-phenoxybenzoic acid (3-PBA), a metabolite of permethrin, following residual disinsection treatment were comparable to the measurements made for flight attendants. Simulations showed that the median contributions of the dermal, oral and inhalation routes to permethrin exposure in flight attendants were 83.5%, 16.1% and 0.4% under residual treatment scenario, respectively, and were 5.3%, 5.0% and 89.7% under pre-flight spray scenario, respectively. The PBPK model provides the capability to simulate the toxicokinetic profiles of permethrin, and can be used in the studies on human exposure to permethrin.

Assessing the impact of child/adult differences in hepatic first-pass effect on the human kinetic adjustment factor for ingested toxicants

The objective of this study was to evaluate the impact of interindividual differences in hepatic first-pass effect (FPE) on the magnitude of the human kinetic adjustment factor (HKAF) for ingested toxicants. This factor aims at replacing a default value of 3.2 used in non-cancer risk assessment. Coupled with Monte Carlo simulations, steady-state equations that account for FPE were used to obtain distributions of arterial blood concentrations (CAss) and rates of metabolism in adults, neonates, infants and toddlers continuously exposed to an oral dose of 1 μg/kg/d of theoretical CYP2E1 and CYP1A2 substrates. For such substrates exhibiting a range of blood:air partition coefficients (Pb: 1-10,000) and hepatic extraction ratios in an average adult (E(ad): 0.01-0.99), HKAFs were computed as the ratio of the 95th percentile of dose metrics for each subpopulation over the 50th percentile value in adults. The reduced hepatic enzyme content in neonates as compared to adults resulted in correspondingly diminished FPE. Consequently, HKAFs greater than 3.2 could be observed, based on CAss only, in the following cases: for some CYP2E1 substrates with E(ad) ≤ 0.3, in neonates (max.: 6.3); and for some CYP1A2 substrates with E(ad) ≤ 0.1 and 0.7, in, respectively, neonates and infants (max.: 28.3). Overall, this study pointed out the importance of accounting for child/adult differences in FPE when determining the HKAF for oral exposure.

Critical appraisal of the assessment of benefits and risks for foods, 'BRAFO Consensus Working Group'

BRAFO, Benefit-Risk Analysis for Foods, was a European Commission project funded within Framework Six as a Specific Support Action and coordinated by ILSI Europe. BRAFO developed a tiered methodology for assessing the benefits and risks of foods and food components, utilising a quantitative, common scale for health assessment in higher tiers. This manuscript reports on the implications of the experience gained during the development of the project for the further improvement of benefit-risk assessment methodology. It was concluded that the methodology proposed is applicable to a range of situations and that it does help in optimising resource utilisation through early identification of those benefit-risk questions where benefit clearly outweighs risk or vice versa. However, higher tier assessments are complex and demanding of time and resources, emphasising the need for prioritisation. Areas identified as requiring further development to improve the utility of benefit-risk assessment include health weights for different populations and endpoints where they do not currently exist, extrapolation of effects from studies in animals to humans, use of in vitro data in benefit-risk assessments, and biomarkers of early effect and how these would be used in a quantitative assessment.

Modeling the Human Kinetic Adjustment Factor for Inhaled Volatile Organic Chemicals: Whole Population Approach versus Distinct Subpopulation Approach

The objective of this study was to evaluate the impact of whole- and sub-population-related variabilities on the determination of the human kinetic adjustment factor (HKAF) used in risk assessment of inhaled volatile organic chemicals (VOCs). Monte Carlo simulations were applied to a steady-state algorithm to generate population distributions for blood concentrations (CAss) and rates of metabolism (RAMs) for inhalation exposures to benzene (BZ) and 1,4-dioxane (1,4-D). The simulated population consisted of various proportions of adults, elderly, children, neonates and pregnant women as per the Canadian demography. Subgroup-specific input parameters were obtained from the literature and P3M software. Under the “whole population” approach, the HKAF was computed as the ratio of the entire population's upper percentile value (99th, 95th) of dose metrics to the median value in either the entire population or the adult population. Under the “distinct subpopulation” approach, the upper percentile values in each subpopulation were considered, and the greatest resulting HKAF was retained. CAss-based HKAFs that considered the Canadian demography varied between 1.2 (BZ) and 2.8 (1,4-D). The “distinct subpopulation” CAss-based HKAF varied between 1.6 (BZ) and 8.5 (1,4-D). RAM-based HKAFs always remained below 1.6. Overall, this study evaluated for the first time the impact of underlying assumptions with respect to the interindividual variability considered (whole population or each subpopulation taken separately) when determining the HKAF.

Development of a human Physiologically Based Pharmacokinetic (PBPK) Toolkit for environmental pollutants

Physiologically Based Pharmacokinetic (PBPK) models can be used to determine the internal dose and strengthen exposure assessment. Many PBPK models are available, but they are not easily accessible for field use. The Agency for Toxic Substances and Disease Registry (ATSDR) has conducted translational research to develop a human PBPK model toolkit by recoding published PBPK models. This toolkit, when fully developed, will provide a platform that consists of a series of priority PBPK models of environmental pollutants. Presented here is work on recoded PBPK models for volatile organic compounds (VOCs) and metals. Good agreement was generally obtained between the original and the recoded models. This toolkit will be available for ATSDR scientists and public health assessors to perform simulations of exposures from contaminated environmental media at sites of concern and to help interpret biomonitoring data. It can be used as screening tools that can provide useful information for the protection of the public.

An assessment of the interindividual variability of internal dosimetry during multi-route exposure to drinking water contaminants

The objective of this study was to evaluate inter-individual variability in absorbed and internal doses after multi-route exposure to drinking water contaminants (DWC) in addition to the corresponding variability in equivalent volumes of ingested water, expressed as liter-equivalents (LEQ). A multi-route PBPK model described previously was used for computing the internal dose metrics in adults, neonates, children, the elderly and pregnant women following a multi-route exposure scenario to chloroform and to tri- and tetra-chloroethylene (TCE and PERC). This scenario included water ingestion as well as inhalation and dermal contact during a 30-min bathroom exposure. Monte Carlo simulations were performed and distributions of internal dose metrics were obtained. The ratio of each of the dose metrics for inhalation, dermal and multi-route exposures to the corresponding dose metrics for the ingestion of drinking water alone allowed computation of LEQ values. Mean BW-adjusted LEQ values based on absorbed doses were greater in neonates regardless of the contaminant considered (0.129–0.134 L/kg BW), but higher absolute LEQ values were obtained in average adults (3.6–4.1 L), elderly (3.7–4.2 L) and PW (4.1–5.6 L). LEQ values based on the parent compound’s AUC were much greater than based on the absorbed dose, while the opposite was true based on metabolite-based dose metrics for chloroform and TCE, but not PERC. The consideration of the 95th percentile values of BW-adjusted LEQ did not significantly change the results suggesting a generally low intra-subpopulation variability during multi-route exposure. Overall, this study pointed out the dependency of the LEQ on the dose metrics, with consideration of both the subpopulation and DWC.