Perchlorate and radioiodide kinetics across life stages in the human: using PBPK models to predict dosimetry and thyroid inhibition and sensitive subpopulations based on developmental stage

Structural Malformations in the Neonatal Rat Brain Accompany Developmental Exposure to Ammonium Perchlorate

Environmental contaminants are often flagged as thyroid system disruptors due to their actions to reduce serum thyroxine (T4) in rodent models. The presence of a periventricular heterotopia (PVH), a brain malformation resulting from T4 insufficiency, has been described in response to T4 decrements induced by pharmaceuticals that reduce the hormone synthesis enzyme thyroperoxidase. In this report, we extend these observations to the environmental contaminant perchlorate, an agent that interferes with thyroid status by inhibiting iodine uptake into the thyroid gland. Pregnant rat dams were administered perchlorate in their drinking water (0, 30, 100, 300, 1000 ppm) from gestational day (GD) 6 until the weaning of pups on postnatal day (PN) 21. Serum T4 was reduced in dams and fetuses in late gestation and remained lower in lactating dams. Pup serum and brain T4, however, were not reduced beyond PN0, and small PVHs were evident in the brains of offspring when assessed on PN14. To emulate the developmental time window of the brain in humans, a second study was conducted in which pups from perchlorate-exposed dams were administered perchlorate orally from PN0 to PN6. This treatment reduced serum and brain T4 in the pup and resulted in large PVH. A third study extended the period of serum and brain TH suppression in pups by coupling maternal perchlorate exposure with maternal dietary iodine deficiency (ID). No PVHs were evident in the pups from ID dams, small PVHs were observed in the offspring of dams exposed to 300 ppm of perchlorate, and very large PVHs were present in the brains of pups born to dams receiving ID and perchlorate. These findings underscore the importance of the inclusion of serum hormone profiles in pregnant dams and fetuses in in vivo screens for thyroid-system-disrupting chemicals and indicate that chemical-induced decreases in fetal rat serum that resolve in the immediate postnatal period may still harbor considerable concern for neurodevelopment in humans.

Cross species extrapolation of the disruption of thyroid hormone synthesis by oxyfluorfen using in vitro data, physiologically based pharmacokinetic (PBPK), and thyroid hormone kinetics models

The thyroid hormones play key roles in physiological processes such as regulation of the metabolic and cardiac systems as well as the development of the brain and surrounding sympathetic nervous system. Recent efforts to screen environmental chemicals for their ability to alter thyroid hormone synthesis, transport, metabolism and/or function have identified novel chemicals that target key processes in the thyroid pathway. One newly identified chemical, oxyfluorfen, is a diphenyl-ether herbicide used for control of annual broadleaf and grassy weeds in a variety of tree fruit, nut, vine, and field crops. Using in vitro high-throughput screening (HTS) assays, oxyfluorofen was identified to be a potent inhibitor of the thyroidal sodium-iodide symporter (NIS). To quantitatively assess this inhibition mechanism in vivo, we extrapolated in vitro NIS inhibition data to in vivo disruption of thyroid hormones synthesis in rats using physiologically based pharmacokinetic (PBPK) and thyroid hormone kinetics models. The overall computational model (chemical PBPK and THs kinetic sub-models) was calibrated against in vivo data for the levels of oxyfluorfen in thyroid tissue and serum and against serum levels of thyroid hormones triiodothyronine (T3) and thyroxine (T4) in rats. The rat thyroid model was then extrapolated to humans using human in vitro HTS data for NIS inhibition and the chemical specific hepatic clearance rate in humans. The overall species extrapolated PBPK-thyroid kinetics model can be used to predict dose-response (% drop in thyroid serum levels compared to homeostasis) relationships in humans. These relationships can be used to estimate points of departure for health risks related to a drop in serum levels of TH hormones based on HTS assays in vitro to in vivo extrapolation (IVIVE), toxicokinetics, and physiological principles.

Perchlorate and chlorate assessment in drinking water in northern Chilean cities

Perchlorate and chlorate are endocrine disruptors considered emerging contaminants (ECs). Both oxyanions are commonly associated with anthropogenic contamination from fertilizers, pesticides, explosives, and disinfection byproducts. However, the soils of the Atacama Desert are the most extensive natural reservoirs of perchlorate in the world, compromising drinking water sources in northern Chile. Field campaigns were carried (2014-2018) to assess the presence of these ECs in the water supply networks of twelve Chilean cities. Additionally, the occurrence of perchlorate, chlorate and other anions typically observed in drinking water matrices of the Atacama Desert (i.e., nitrate, chloride, sulfate) was evaluated using a Spearman correlation analysis to determine predictors for perchlorate and chlorate. High concentrations of perchlorate (up to 114.48 μg L-1) and chlorate (up to 9650 μg L-1) were found in three northern cities. Spatial heterogeneities were observed in the physicochemical properties and anion concentrations of the water supply network. Spearman correlation analysis indicated that nitrate, chloride, and sulfate were not useful predictors for the presence of perchlorate and chlorate in drinking water in Chile. Hence, this study highlights the need to establish systematic monitoring, regulation, and treatment for these EC of drinking water sources in northern Chilean cities for public health protection.

Endocrine-Disrupting Chemicals and Persistent Organic Pollutants in Infant Formulas and Baby Food: Legislation and Risk Assessments

Human milk is the healthiest option for newborns, although, under specific circumstances, infant formula is a precious alternative for feeding the baby. Except for the nutritional content, infant formulas and baby food must be pollutant-free. Thus, their composition is controlled by continuous monitoring and regulated by establishing upper limits and guideline values for safe exposure. Legislation differs worldwide, although there are standard policies and strategies for protecting vulnerable infants. This work presents current regulations and directives for restricting endocrine-disrupting chemicals and persistent organic pollutants in infant formulas. Risk assessment studies, which are limited, are necessary to depict exposure variations and assess the health risks for infants from dietary exposure to pollutants.

Systematic review of physiologically based kinetic lactation models for transfer of xenobiotic compounds to milk

Lactational elimination has been described mathematically for nearly 50 years. Over 40 published articles, containing >50 physiologically based kinetic (PBK) lactation models were included in the systematic review. These PBK models described the lactational elimination of xenobiotic compounds in humans, rats, mice, and dairy cows and goats. A total of 78 compounds have been modelled, ranging from industrial chemicals, pesticides, to pain medication, antibiotics, and caffeine. Few models included several species or compounds, and models were thus generally not translational or generic. Three dairy cow models mechanistically described the intramammary disposition of pharmaceuticals after intramammary administration, including volume changes caused by milking, while empirically describing the remaining pharmacokinetics. The remaining models were semi- or whole body PBK models, describing long-term exposure of environmental pollutants, or short-term exposure of pharmaceuticals. The absolute majority described the disposition to the mammary gland or milk with perfusion limited compartments, but permeability limited models were available as well. With long-term exposure, models often included changes in milk volume and/or consumption by the offspring, and changes in body weight of offspring. Periodic emptying of the mammary gland, as with feeding or milking, was sparsely applied. Rodent models used similar physiological parameters, while values of physiological parameters applied in human models could range widely. When milk composition was included in the models, it most often included the fat content. The review gives an extensive overview of the applied functions and modelling strategies of PBK lactation models.

Evaluation of a rapid, generic human gestational dose model

Chemical risk assessment considers potentially susceptible populations including pregnant women and developing fetuses. Humans encounter thousands of chemicals in their environments, few of which have been fully characterized. Toxicokinetic (TK) information is needed to relate chemical exposure to potentially bioactive tissue concentrations. Observational data describing human gestational exposures are unavailable for most chemicals, but physiologically based TK (PBTK) models estimate such exposures. Development of chemical-specific PBTK models requires considerable time and resources. As an alternative, generic PBTK approaches describe a standardized physiology and characterize chemicals with a set of standard physical and TK descriptors - primarily plasma protein binding and hepatic clearance. Here we report and evaluate a generic PBTK model of a human mother and developing fetus. We used a published set of formulas describing the major anatomical and physiological changes that occur during pregnancy to augment the High-Throughput Toxicokinetics (httk) software package. We simulated the ratio of concentrations in maternal and fetal plasma and compared to literature in vivo measurements. We evaluated the model with literature in vivo time-course measurements of maternal plasma concentrations in pregnant and non-pregnant women. Finally, we prioritized chemicals measured in maternal serum based on predicted fetal brain concentrations. This new model can be used for TK simulations of 859 chemicals with existing human-specific in vitro TK data as well as any new chemicals for which such data become available. This gestational model may allow for in vitro to in vivo extrapolation of point of departure doses relevant to reproductive and developmental toxicity.

Towards a science-based testing strategy to identify maternal thyroid hormone imbalance and neurodevelopmental effects in the progeny-part III: how is substance-mediated thyroid hormone imbalance in pregnant/lactating rats or their progeny related to neurodevelopmental effects?

This review investigated which patterns of thyroid- and brain-related effects are seen in rats upon gestational/lactational exposure to 14 substances causing thyroid hormone imbalance by four different modes-of-action (inhibition of thyroid peroxidase, sodium-iodide symporter and deiodinase activities, enhancement of thyroid hormone clearance) or to dietary iodine deficiency. Brain-related parameters included motor activity, cognitive function, acoustic startle response, hearing function, periventricular heterotopia, electrophysiology and brain gene expression. Specific modes-of-action were not related to specific patterns of brain-related effects. Based upon the rat data reviewed, maternal serum thyroid hormone levels do not show a causal relationship with statistically significant neurodevelopmental effects. Offspring serum thyroxine together with offspring serum triiodothyronine and thyroid stimulating hormone appear relevant to predict the likelihood for neurodevelopmental effects. Based upon the collated database, thresholds of ≥60%/≥50% offspring serum thyroxine reduction and ≥20% and statistically significant offspring serum triiodothyronine reduction indicate an increased likelihood for statistically significant neurodevelopmental effects; accuracies: 83% and 67% when excluding electrophysiology (and gene expression). Measurements of brain thyroid hormone levels are likely relevant, too. The extent of substance-mediated thyroid hormone imbalance appears more important than substance mode-of-action to predict neurodevelopmental impairment in rats. Pertinent research needs were identified, e.g. to determine whether the phenomenological offspring thyroid hormone thresholds are relevant for regulatory toxicity testing. The insight from this review shall be used to suggest a tiered testing strategy to determine whether gestational/lactational substance exposure may elicit thyroid hormone imbalance and potentially also neurodevelopmental effects.

Mechanistic Computational Model for Extrapolating In vitro Thyroid Peroxidase (TPO) Inhibition Data to Predict Serum Thyroid Hormone Levels in Rats

High throughput (HTP) in vitro assays are developed to screen chemicals for their potential to inhibit thyroid hormones (THs) synthesis. Some of these experiments, such as the thyroid peroxidase (TPO) inhibition assay, are based on thyroid microsomal extracts. However, the regulation of thyroid disruption chemicals (TDCs) is based on THs in vivo serum levels. This necessitates the estimation of TDCs in vivo tissue levels in the thyroid where THs synthesis inhibition by TPO takes place. The in vivo tissue levels of chemicals are controlled by pharmacokinetic determinants such as absorption, distribution, metabolism and excretion (ADME), and can be described quantitatively in physiologically based pharmacokinetic (PBPK) models. An integrative computational model including chemical specific PBPK and TH kinetics models provides a mechanistic quantitative approach to translate thyroidal HTP in vitro assays to in vivo measures of circulating THs serum levels. This computational framework is developed to quantitatively establish the linkage between applied dose, chemical thyroid tissue levels, thyroid TPO inhibition potential, and in vivo TH serum levels. Once this link is established quantitively, the overall model is used to calibrate the TH kinetics parameters using experimental data for THs levels in thyroid tissue and serum for the two drugs Propylthiouracil (PTU) and Methimazole (MMI). The calibrated quantitative framework is then evaluated against literature data for the environmental chemical ethylenethiourea (ETU). The linkage of PBPK and TH kinetics models illustrates a computational framework that can be extrapolated to humans to screen chemicals based on their exposure levels and potential to disrupt serum THs levels in vivo.

Using quantitative modeling tools to assess pharmacokinetic bias in epidemiological studies showing associations between biomarkers and health outcomes at low exposures

Biomarkers of exposure can be measured at lower and lower levels due to advances in analytical chemistry. Using these sensitive methods, some epidemiology studies report associations between biomarkers and health outcomes at biomarker levels much below those associated with effects in animal studies. While some of these low exposure associations may arise from increased sensitivity of humans compared with animals or from species-specific responses, toxicology studies with drugs, commodity chemicals and consumer products have not generally indicated significantly greater sensitivity of humans compared with test animals for most health outcomes. In some cases, these associations may be indicative of pharmacokinetic (PK) bias, i.e., a situation where a confounding factor or the health outcome itself alters pharmacokinetic processes affecting biomarker levels. Quantitative assessment of PK bias combines PK modeling and statistical methods describing outcomes across large numbers of individuals in simulated populations. Here, we first provide background on the types of PK models that can be used for assessing biomarker levels in human population and then outline a process for considering PK bias in studies intended to assess associations between biomarkers and health outcomes at low levels of exposure. After providing this background, we work through published examples where these PK methods have been applied with several chemicals/chemical classes - polychlorinated biphenyls (PCBs), perfluoroalkyl substances (PFAS), polybrominated biphenyl ethers (PBDE) and phthalates - to assess the possibility of PK bias. Studies of the health effects of low levels of exposure will be improved by developing some confidence that PK bias did not play significant roles in the observed associations.

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.

Occurrence of perchlorate, chlorate and polar herbicides in different baby food commodities

The incidence of endocrine disruptors, both possible (glyphosate and glufosinate), and demonstrated (perchlorate and chlorate), was estimated in baby food commodities (meat, fish, cheese, vegetable and fruit). Ion-chromatography coupled to high resolution mass spectrometry analysis of the 105 samples did not show traces of glyphosate, glufosinate or their metabolites, while in 10.5% of the samples a quantifiable amount of perchlorate was found. Some samples based on fruit and vegetables revealed a substantial amount of chlorate, especially the preparations that contained carrots and potatoes: five samples were in a concentration range of 40-120 μg kg^-1, while one homogenized pear sample reached 372.2 μg kg^-1. The pure meat samples revealed occasional chlorate appearance, with less than 10 μg kg^-1. This is the first report of chlorate evaluated in various types of baby food and may serve as symptomatic data regarding its occurrence in infant/toddler diets. Therefore, effective monitoring programs and subsequent strict regulations are strongly required.

Empirical models for anatomical and physiological changes in a human mother and fetus during pregnancy and gestation

Many parameters treated as constants in traditional physiologically based pharmacokinetic models must be formulated as time-varying quantities when modeling pregnancy and gestation due to the dramatic physiological and anatomical changes that occur during this period. While several collections of empirical models for such parameters have been published, each has shortcomings. We sought to create a repository of empirical models for tissue volumes, blood flow rates, and other quantities that undergo substantial changes in a human mother and her fetus during the time between conception and birth, and to address deficiencies with similar, previously published repositories. We used maximum likelihood estimation to calibrate various models for the time-varying quantities of interest, and then used the Akaike information criterion to select an optimal model for each quantity. For quantities of interest for which time-course data were not available, we constructed composite models using percentages and/or models describing related quantities. In this way, we developed a comprehensive collection of formulae describing parameters essential for constructing a PBPK model of a human mother and her fetus throughout the approximately 40 weeks of pregnancy and gestation. We included models describing blood flow rates through various fetal blood routes that have no counterparts in adults. Our repository of mathematical models for anatomical and physiological quantities of interest provides a basis for PBPK models of human pregnancy and gestation, and as such, it can ultimately be used to support decision-making with respect to optimal pharmacological dosing and risk assessment for pregnant women and their developing fetuses. The views expressed in this article are those of the authors and do not necessarily represent the views or policies of the U.S. Environmental Protection Agency.

Development of a Novel Maternal-Fetal Physiologically Based Pharmacokinetic Model I: Insights into Factors that Determine Fetal Drug Exposure through Simulations and Sensitivity Analyses

Determining fetal drug exposure (except at the time of birth) is not possible for both logistical and ethical reasons. Therefore, we developed a novel maternal-fetal physiologically based pharmacokinetic (m-f-PBPK) model to predict fetal exposure to drugs and populated this model with gestational age-dependent changes in maternal-fetal physiology. Then, we used this m-f-PBPK to: 1) perform a series of sensitivity analyses to quantitatively demonstrate the impact of fetoplacental metabolism and placental transport on fetal drug exposure for various drug-dosing regimens administered to the mother; 2) predict the impact of gestational age on fetal drug exposure; and 3) demonstrate that a single umbilical venous (UV)/maternal plasma (MP) ratio (even after multiple-dose oral administration to steady state) does not necessarily reflect fetal drug exposure. In addition, we verified the implementation of this m-f-PBPK model by comparing the predicted UV/MP and fetal/MP AUC ratios with those predicted at steady state after an intravenous infusion. Our simulations yielded novel insights into the quantitative contribution of fetoplacental metabolism and/or placental transport on gestational age-dependent fetal drug exposure. Through sensitivity analyses, we demonstrated that the UV/MP ratio does not measure the extent of fetal drug exposure unless obtained at steady state after an intravenous infusion or when there is little or no fluctuation in MP drug concentrations after multiple-dose oral administration. The proposed m-f-PBPK model can be used to predict fetal exposure to drugs across gestational ages and therefore provide the necessary information to assess the risk of drug toxicity to the fetus.

Revision of the affinity constant for perchlorate binding to the sodium-iodide symporter based on in vitro and human in vivo data

A series of previously published physiologically based pharmacokinetic (PBPK) models describe the effect of perchlorate on iodide uptake by the thyroid, with the mechanism being competitive inhibition of iodide transport by the sodium-iodide symporter (NIS). Hence a key parameter of these models is the affinity of perchlorate for the NIS, characterized as the Michaelis-Menten kinetic constant, K_m . However, when model predictions were compared to published results of a human study measuring radio-iodide uptake (RAIU) inhibition after controlled perchlorate exposures, it was found to only fit the lowest exposure level and underpredicted RAIU inhibition at higher levels. Published in vitro data, in which perchlorate-induced inhibition of iodide uptake via the NIS was measured, were re-analyzed. K_m for binding of perchlorate to the NIS originally derived from these data, 1.5 μm, had been obtained using Lineweaver-Burk plots, which allow for linear regression but invert the signal-noise of the data. Re-fitting these data by non-linear regression of the non-inverted data yielded a 60% lower value for the K_m , 0.59 μm. Substituting this value into the PBPK model for an average adult human significantly improved model agreement with the human RAIU data for exposures <100 μg kg^-1  day^-1 . Thus, this lower K_m value both fits the in vitro NIS kinetics and provides better predictions of human in vivo RAIU data. This change in K_m increases the predicted sensitivity of humans to perchlorate over twofold for low-level exposures. Published 2016. This article is a U.S. Government work and is in the public domain in the USA. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

Integration of Life-Stage Physiologically Based Pharmacokinetic Models with Adverse Outcome Pathways and Environmental Exposure Models to Screen for Environmental Hazards

A computational framework was developed to assist in screening and prioritizing chemicals based on their dosimetry, toxicity, and potential exposures. The overall strategy started with contextualizing chemical activity observed in high-throughput toxicity screening (HTS) by mapping these assays to biological events described in Adverse Outcome Pathways (AOPs). Next, in vitro to in vivo (IVIVE) extrapolation was used to convert an in vitro dose to an external exposure level, which was compared with potential exposure levels to derive an AOP-based margins of exposure (MOE). In this study, the framework was applied to estimate MOEs for chemicals that can potentially cause developmental toxicity following a putative AOP for fetal vasculogenesis/angiogenesis. A physiologically based pharmacokinetic (PBPK) model was developed to describe chemical disposition during pregnancy, fetal, neonatal, and infant to adulthood stages. Using this life-stage PBPK model, maternal exposures were estimated that would yield fetal blood levels equivalent to the chemical concentration that altered in vitro activity of selected HTS assays related to the most sensitive vasculogenesis/angiogenesis putative AOP. The resulting maternal exposure estimates were then compared with potential exposure levels using literature data or exposure models to derive AOP-based MOEs.

Dietary Iodine Sufficiency and Moderate Insufficiency in the Lactating Mother and Nursing Infant: A Computational Perspective

The Institute of Medicine recommends that lactating women ingest 290 μg iodide/d and a nursing infant, less than two years of age, 110 μg/d. The World Health Organization, United Nations Children’s Fund, and International Council for the Control of Iodine Deficiency Disorders recommend population maternal and infant urinary iodide concentrations ≥ 100 μg/L to ensure iodide sufficiency. For breast milk, researchers have proposed an iodide concentration range of 150–180 μg/L indicates iodide sufficiency for the mother and infant, however no national or international guidelines exist for breast milk iodine concentration. For the first time, a lactating woman and nursing infant biologically based model, from delivery to 90 days postpartum, was constructed to predict maternal and infant urinary iodide concentration, breast milk iodide concentration, the amount of iodide transferred in breast milk to the nursing infant each day and maternal and infant serum thyroid hormone kinetics. The maternal and infant models each consisted of three sub-models, iodide, thyroxine (T4), and triiodothyronine (T3). Using our model to simulate a maternal intake of 290 μg iodide/d, the average daily amount of iodide ingested by the nursing infant, after 4 days of life, gradually increased from 50 to 101 μg/day over 90 days postpartum. The predicted average lactating mother and infant urinary iodide concentrations were both in excess of 100 μg/L and the predicted average breast milk iodide concentration, 157 μg/L. The predicted serum thyroid hormones (T4, free T4 (fT4), and T3) in both the nursing infant and lactating mother were indicative of euthyroidism. The model was calibrated using serum thyroid hormone concentrations for lactating women from the United States and was successful in predicting serum T4 and fT4 levels (within a factor of two) for lactating women in other countries. T3 levels were adequately predicted. Infant serum thyroid hormone levels were adequately predicted for most data. For moderate iodide deficient conditions, where dietary iodide intake may range from 50 to 150 μg/d for the lactating mother, the model satisfactorily described the iodide measurements, although with some variation, in urine and breast milk. Predictions of serum thyroid hormones in moderately iodide deficient lactating women (50 μg/d) and nursing infants did not closely agree with mean reported serum thyroid hormone levels, however, predictions were usually within a factor of two. Excellent agreement between prediction and observation was obtained for a recent moderate iodide deficiency study in lactating women. Measurements included iodide levels in urine of infant and mother, iodide in breast milk, and serum thyroid hormone levels in infant and mother. A maternal iodide intake of 50 μg/d resulted in a predicted 29–32% reduction in serum T4 and fT4 in nursing infants, however the reduced serum levels of T4 and fT4 were within most of the published reference intervals for infant. This biologically based model is an important first step at integrating the rapid changes that occur in the thyroid system of the nursing newborn in order to predict adverse outcomes from exposure to thyroid acting chemicals, drugs, radioactive materials or iodine deficiency.

Association of prenatal perchlorate, thiocyanate, and nitrate exposure with neonatal size and gestational age

BACKGROUND

Perchlorate and similar anions compete with iodine for uptake into the thyroid by the sodium iodide symporter (NIS). This may restrict fetal growth via impaired thyroid hormone production.

METHODS

We collected urine samples from 107 pregnant women and used linear regression to estimate differences in newborn size and gestational age associated with increases in perchlorate, thiocyanate, nitrate, and perchlorate equivalence concentrations (PEC; measure of total NIS inhibitor exposure).

RESULTS

NIS inhibitor concentrations were not associated with newborn weight, length, or gestational age. Each 2.62ng/μg creatinine increase in perchlorate was associated with smaller head circumference (0.32cm; 95% CI: -0.66, 0.01), but each 3.38ng/μg increase in PEC was associated with larger head circumference (0.48cm; -0.01, 0.97).

CONCLUSIONS

These anions may have effects on fetal development (e.g. neurocognitive) that are not reflected in gross measures. Future research should focus on other abnormalities in neonates exposed to NIS inhibitors.

Quantitative global sensitivity analysis of a biologically based dose-response pregnancy model for the thyroid endocrine system

A deterministic biologically based dose-response model for the thyroidal system in a near-term pregnant woman and the fetus was recently developed to evaluate quantitatively thyroid hormone perturbations. The current work focuses on conducting a quantitative global sensitivity analysis on this complex model to identify and characterize the sources and contributions of uncertainties in the predicted model output. The workflow and methodologies suitable for computationally expensive models, such as the Morris screening method and Gaussian Emulation processes, were used for the implementation of the global sensitivity analysis. Sensitivity indices, such as main, total and interaction effects, were computed for a screened set of the total thyroidal system descriptive model input parameters. Furthermore, a narrower sub-set of the most influential parameters affecting the model output of maternal thyroid hormone levels were identified in addition to the characterization of their overall and pair-wise parameter interaction quotients. The characteristic trends of influence in model output for each of these individual model input parameters over their plausible ranges were elucidated using Gaussian Emulation processes. Through global sensitivity analysis we have gained a better understanding of the model behavior and performance beyond the domains of observation by the simultaneous variation in model inputs over their range of plausible uncertainties. The sensitivity analysis helped identify parameters that determine the driving mechanisms of the maternal and fetal iodide kinetics, thyroid function and their interactions, and contributed to an improved understanding of the system modeled. We have thus demonstrated the use and application of global sensitivity analysis for a biologically based dose-response model for sensitive life-stages such as pregnancy that provides richer information on the model and the thyroidal system modeled compared to local sensitivity analysis.

The use of PBPK models to inform human health risk assessment: case study on perchlorate and radioiodide human lifestage models

Physiologically-based pharmacokinetic (PBPK) models are often submitted to or selected by agencies, such as the U.S. Environmental Protection Agency (U.S. EPA) and Agency for Toxic Substances and Disease Registry, for consideration for application in human health risk assessment (HHRA). Recently, U.S. EPA evaluated the human PBPK models for perchlorate and radioiodide for their ability to estimate the relative sensitivity of perchlorate inhibition on thyroidal radioiodide uptake for various population groups and lifestages. The most well-defined mode of action of the environmental contaminant, perchlorate, is competitive inhibition of thyroidal iodide uptake by the sodium-iodide symporter (NIS). In this analysis, a six-step framework for PBPK model evaluation was followed, and with a few modifications, the models were determined to be suitable for use in HHRA to evaluate relative sensitivity among human lifestages. Relative sensitivity to perchlorate was determined by comparing the PBPK model predicted percent inhibition of thyroidal radioactive iodide uptake (RAIU) by perchlorate for different lifestages. A limited sensitivity analysis indicated that model parameters describing urinary excretion of perchlorate and iodide were particularly important in prediction of RAIU inhibition; therefore, a range of biologically plausible values available in the peer-reviewed literature was evaluated. Using the updated PBPK models, the greatest sensitivity to RAIU inhibition was predicted to be the near-term fetus (gestation week 40) compared to the average adult and other lifestages; however, when exposure factors were taken into account, newborns were found to be populations that need further evaluation and consideration in a risk assessment for perchlorate.

Using a physiologically based pharmacokinetic model to link urinary biomarker concentrations to dietary exposure of perchlorate

Exposure to perchlorate is widespread in the United States and many studies have attempted to character the perchlorate exposure by estimating the average daily intakes of perchlorate. These approaches provided population-based estimates, but did not provide individual-level exposure estimates. Until recently, exposure activity database such as CSFII, TDS and NHANES become available and provide opportunities to evaluate the individual-level exposure to chemical using exposure surveillance dataset. In this study, we use perchlorate as an example to investigate the usefulness of urinary biomarker data for predicting exposures at the individual level. Specifically, two analyses were conducted: (1) using data from a controlled human study to examine the ability of a physiologically based pharmacokinetic (PBPK) model to predict perchlorate concentrations in single-spot and cumulative urine samples; and (2) using biomarker data from a population-based study and a PBPK model to demonstrate the challenges in linking urinary biomarker concentrations to intake doses for individuals. Results showed that the modeling approach was able to characterize the distribution of biomarker concentrations at the population level, but predicting the exposure-biomarker relationship for individuals was much more difficult. The type of information needed to reduce the uncertainty in estimating intake doses, for individuals, based on biomarker measurements is discussed.

Breastfed infants metabolize perchlorate

Bifidobacteria are the dominant intestinal bacteria in breastfed infants. It is known that they can reduce nitrate. Although no direct experiments have been conducted until now, inferred pathways for Bifidobacterium bifidum include perchlorate reduction via perchlorate reductase. We show that when commercially available strains of bifidobacteria are cultured in milk, spiked with perchlorate, perchlorate is consumed. We studied 13 breastfed infant-mother pairs who provided 43 milk samples and 39 infant urine samples, and 5 formula-fed infant-mother pairs who provided 21 formula samples and 21 infant urine samples. Using iodine as a conservative tracer, we determined the average urinary iodine (UI) to milk iodine (MI) concentration ratio to be 2.87 for the breastfed infants. For the same samples, the corresponding perchlorate concentration ratio was 1.37 (difference significant, p < 0.001), indicating that perchlorate is lost. For the formula fed infant group the same ratios were 1.20 and 1.58; the difference was not significant (p = 0.68). However, the small number of subjects in the latter group makes it more difficult to conclude definitively whether perchlorate reduction does or does not occur.

Extrapolation of hypothalamic-pituitary-thyroid axis perturbations and associated toxicity in rodents to humans: case study with perchlorate

Functional aspects of the Hypothalamic-Pituitary-Thyroid (HPT) axis in rats and humans are compared, exposing why extrapolation of toxicant-induced perturbations in the rat HPT axis to the human HPT axis cannot be accomplished using default risk assessment methodology. Computational tools, such as biologically based dose response models for the HPT axis, are recommended to perform complex animal to human extrapolations involving the HPT axis. Experimental and computational evidence are presented that suggest perchlorate acts directly on the thyroid gland in rats. The apparent escape from perchlorate-induced inhibition of thyroidal uptake of radioactive iodide in humans is discussed along with "rebound" or increased thyroidal uptake of radioactive iodide observed after discontinued clinical treatment with perchlorate.

ISDD: A computational model of particle sedimentation, diffusion and target cell dosimetry for in vitro toxicity studies

BACKGROUND

The difficulty of directly measuring cellular dose is a significant obstacle to application of target tissue dosimetry for nanoparticle and microparticle toxicity assessment, particularly for in vitro systems. As a consequence, the target tissue paradigm for dosimetry and hazard assessment of nanoparticles has largely been ignored in favor of using metrics of exposure (e.g. μg particle/mL culture medium, particle surface area/mL, particle number/mL). We have developed a computational model of solution particokinetics (sedimentation, diffusion) and dosimetry for non-interacting spherical particles and their agglomerates in monolayer cell culture systems. Particle transport to cells is calculated by simultaneous solution of Stokes Law (sedimentation) and the Stokes-Einstein equation (diffusion).

RESULTS

The In vitro Sedimentation, Diffusion and Dosimetry model (ISDD) was tested against measured transport rates or cellular doses for multiple sizes of polystyrene spheres (20-1100 nm), 35 nm amorphous silica, and large agglomerates of 30 nm iron oxide particles. Overall, without adjusting any parameters, model predicted cellular doses were in close agreement with the experimental data, differing from as little as 5% to as much as three-fold, but in most cases approximately two-fold, within the limits of the accuracy of the measurement systems. Applying the model, we generalize the effects of particle size, particle density, agglomeration state and agglomerate characteristics on target cell dosimetry in vitro.

CONCLUSIONS

Our results confirm our hypothesis that for liquid-based in vitro systems, the dose-rates and target cell doses for all particles are not equal; they can vary significantly, in direct contrast to the assumption of dose-equivalency implicit in the use of mass-based media concentrations as metrics of exposure for dose-response assessment. The difference between equivalent nominal media concentration exposures on a μg/mL basis and target cell doses on a particle surface area or number basis can be as high as three to six orders of magnitude. As a consequence, in vitro hazard assessments utilizing mass-based exposure metrics have inherently high errors where particle number or surface areas target cells doses are believed to drive response. The gold standard for particle dosimetry for in vitro nanotoxicology studies should be direct experimental measurement of the cellular content of the studied particle. However, where such measurements are impractical, unfeasible, and before such measurements become common, particle dosimetry models such as ISDD provide a valuable, immediately useful alternative, and eventually, an adjunct to such measurements.

Approaches for assessing risks to sensitive populations: lessons learned from evaluating risks in the pediatric population

Assessing the risk profiles of potentially sensitive populations requires a "tool chest" of methodological approaches to adequately characterize and evaluate these populations. At present, there is an extensive body of literature on methodologies that apply to the evaluation of the pediatric population. The Health and Environmental Sciences Institute Subcommittee on Risk Assessment of Sensitive Populations evaluated key references in the area of pediatric risk to identify a spectrum of methodological approaches. These approaches are considered in this article for their potential to be extrapolated for the identification and assessment of other sensitive populations. Recommendations as to future research needs and/or alternate methodological considerations are also made.

Use of a simple pharmacokinetic model to characterize exposure to perchlorate

A simple two-compartment first-order pharmacokinetic model that predicts concentrations of perchlorate in blood and urine was constructed and validated. The model was validated using data from a high-dose experiment in humans where doses and resulting concentrations of perchlorate in blood and urine were well documented. Specifically, data were available for individuals who had been dosed at 0.5, 0.1, and 0.02 mg/kg/day for 14 consecutive days, significantly higher than the average background dose, which is estimated to be less than 0.0001 mg/kg/day. The average measured urine concentration in the high-dose regime during the experiment was 15.4 mg/l compared with an average prediction of 17.3 mg/l. In the medium-dose regime, the average measured was 3.0 mg/l compared with 4.1 mg/l predicted, and in the low-dose regime, the average measured was 0.53 mg/l compared with 0.68 mg/l predicted. For blood, the analogous results include 0.51 mg/l measured compared with 0.54 mg/l predicted in the high-dose regime and 0.12 mg/l measured versus 0.11 mg/l predicted in the medium-dose regime. The model was then used to study background exposures to perchlorate. A national sampling of perchlorate in urine showed a median concentration of 0.0035 mg/l, and this was used to back-calculate a dose of 0.000064 mg/kg/day. This finding was independently verified with the modeling structure of this study, as use of that back-calculated dose of 0.000064 mg/kg/day resulted in predictions of urine concentration with an average virtually identical at 0.0033 mg/l. An examination of literature data on the possible pathways of exposure suggests that the consumption of foods, rather than ingestion of water, dominates background exposures. Daily variation in urine concentration was studied with the model, and it was found that concentrations in the morning hours were lower than concentrations in the afternoon and evening hours, corresponding to the time when most exposure was assumed to occur.

On the incorporation of chemical-specific information in risk assessment

This paper describes the evolution of chemical risk assessment from its early dependence on generic default approaches to the current situation in which mechanistic and biokinetic data are routinely incorporated to support a more chemical-specific approach. Two methodologies that have played an important role in this evolution are described: mode-of-action evaluation and physiologically based biokinetic (PBBK) modelling. When used together, these techniques greatly increase the opportunity for the incorporation of biokinetic and mechanistic data in risk assessment. The resulting risk assessment approaches are more appropriately tailored to the specific chemical and are more likely to provide an accurate assessment of the potential hazards associated with human exposures. The appropriate application of PBBK models in risk assessment demands well-formulated statements about the chemical mode of action. It is this requirement for an explicit, mechanistic hypothesis that gives biologically motivated models their power, but at the same time serves as the greatest impediment to the acceptance of a chemical-specific risk assessment approach by regulators. The chief impediment to the regulatory acceptance and application of PBBK models in risk assessment is concern about uncertainties associated with their use. To some extent such concerns can be addressed by the development of generally accepted approaches for model evaluation and quantitative uncertainty analysis. In order to assure the protection of public health while limiting the economic and social consequences of over-regulation, greater dialogue between researchers and regulators is crucially needed to foster an increased use of emerging scientific information and innovative methods in chemical risk assessments.