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Predicting Neonatal Perchlorate Dose and Inhibition of Iodide Uptake in the Rat During

Lactation Using Physiologically-Based Pharmacokinetic Modeling

Rebecca A. Clewell1#*, Elaine A. Merrill1, Kyung O. Yu.3,

Deirdre A. Mahle4, Teresa R. Sterner2, Jeffrey W. Fisher3†, Jeffery M. Gearhart4

1Geo-Centers, Inc., Wright-Patterson AFB, OH 45433

2Operational Technologies Corp., Dayton, OH 45432

3AFRL/HEST, Wright-Patterson AFB, OH 45433

4Mantech Environmental Technology, Inc., Dayton, OH 45437

#Current Address: CIIT Centers for Health Research, RTP, NC 27709

†Current Address: The University of Georgia, Athens, GA

* To whom correspondence should be addressed:

Rebecca A. Clewell

CIIT Centers for Health Research

Six Davis Drive

Research Triangle Park, NC 27709-2137

Tel: (919) 558-1307

Fax: (919) 558-1300

E-mail: rclewell@ciit.org

Abbreviated title: PBPK ClO4- Model for Rat Lactation

Copyright (c) 2003 Society of Toxicology

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ABSTRACT

Perchlorate (ClO4-), a contaminant in drinking water, competitively inhibits active uptake

of iodide (I-) into various tissues, including mammary tissue. During postnatal development,

inhibition of I- uptake in the mammary gland and neonatal thyroid, and the active concentration

ClO4- in milk indicate a potentially increased susceptibility of neonates to endocrine disruption.

A physiologically based pharmacokinetic (PBPK) model was developed to reproduce measured

ClO4- distribution in the lactating and neonatal rat and predict resulting effects on I- kinetics from

competitive inhibition at the sodium iodide symporter (NIS). Kinetic I- and ClO4- behavior in

tissues with NIS (thyroid, stomach, mammary gland and skin) was simulated with multiple sub-

compartments, Michaelis-Menten (M-M) kinetics and competitive inhibition. Physiological and

kinetic parameters were obtained from literature and experiment. Systemic clearance and M-M

parameters were estimated by fitting simulations to tissue and serum data. The model

successfully describes maternal and neonatal thyroid, stomach, skin, and plasma, as well as

maternal mammary gland and milk data after ClO4- exposure (from 0.01 to 10 mg/kg-day ClO4

-)

and acute radioiodide (2.1 to 33,000 ng/kg I-) dosing. The model also predicts I- uptake

inhibition in the maternal thyroid, mammary gland and milk. Model simulations predict a

significant transfer of ClO4- through milk after maternal exposure; approximately 50% to 6% of

the daily maternal dose at doses ranging from 0.01 to 10.0 mg ClO4-/kg-day, respectively.

Comparison of predicted dosimetrics across life-stages in the rat indicates that neonatal thyroid I-

uptake inhibition is similar to the adult and approximately 10-fold less than the fetus.

Keywords: PBPK model, lactation, perchlorate, iodide, inhibition, milk

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INTRODUCTION

Perchlorate (ClO4-), the soluble anion of ammonium and potassium perchlorate, is

a thyroid iodide uptake inhibitor known to be present in several United States drinking water

sources, ranging in concentrations from less than 4 ppb to more than 3,700 ppm in some Las

Vegas water samples (Motzer, 2001). Human health concerns arise from the fact that ClO4-,

being similar in size and shape to iodide (I-), is able to bind to the sodium-iodide symporter

(NIS), thus reducing the amount of iodide taken up into the thyroid. Thyroid hormones are

synthesized from I- in the thyroid and are responsible for regulating metabolism. In the adult,

lack of iodide causes reduced thyroxine (T4) and triiodothyronine (T3) levels and can eventually

lead to hypothyroidism (Wolff, 1998). Furthermore, since these hormones are required for

normal physical and mental development, exposure to thyroid inhibitors during the period of

rapid growth in late gestation and early infancy could result in long-term consequences

(Howdeshell, 2002; Porterfield, 1994). Congenital hypothyroidism and gestational iodide

deficiency are known to cause delayed development and, in severe cases, lowered IQ, mental

retardation and even cretinism (Delange, 2000; Haddow et al., 1999; Howdeshell, 2002; Klein et

al., 1972; Porterfield, 1994). In the case of perchlorate contamination of drinking water sources,

the question is whether ClO4- is capable of inducing these same developmental effects and at

what level of exposure the fetus or infant may be at risk of adverse effects.

In order to help answer these questions, several studies have been conducted in rats

involving chronic and short-term perchlorate exposure during gestation, lactation and in adult

males at a variety of doses (Bekkedal et al., 2001; Mahle et al., 2002; Mahle et al., In Press;

York et al., 1999; York et al., 2001; Yu et al., 2002). None of the available studies show the

same extent of adverse effects from perchlorate exposure as are known to occur in iodide

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deficiency. However, consolidating these various data sets into a quantitative measure of risk to

the perchlorate-exposed infant is quite difficult due to the variations in study design, as well as

the rapid physical and biochemical changes taking place during lactation and infancy. To

incorporate these kinetic, physiological and biochemical data into a predictive tool for

perchlorate, iodide and perchlorate-induced inhibition kinetics, a physiologically based

pharmacokinetic (PBPK) model was developed in the lactating and neonatal rat. Together with

the concurrent PBPK models developed for the male rat (Merrill et al., In Press), pregnant and

fetal rat (Clewell et al., In Press), and the adult human (Merrill et al., 2001), the models can be

used to compare internal dose metrics, such as ClO4- concentration in the serum across

developmental life stages and species. Thus, the models provide a means for extrapolating

predicted kinetics and measures of dose to the potentially more sensitive and often overlooked

subpopulation, the human fetus and infant (Clewell and Gearhart, 2002a).

Although the hormone feedback system of the postnatal rat is independent of the mother

(Howdeshell, 2002; Potter et al., 1959; Vigouroux and Rostaqui, 1980), the affect of maternal

perchlorate exposure is intricately tied to neonatal risk. In fact, there are several unique factors

that must be accounted for when attempting to quantify risk to the nursing neonate. For

example, the lactating mammary gland contains active NIS that concentrates iodide in the milk

ensuring an adequate supply of iodide to the newborn. However, since ClO4- competitively

inhibits iodide binding to NIS, maternal exposure during lactation also inhibits iodide transfer in

the milk, as has been noted in several species including the rat, goat, rabbit and cow (Brown-

Grant, 1957; Cline et al., 1969; Grosvenor, 1963; Lengemann, 1965; Potter et al., 1959). It is

also possible that this binding of perchlorate to NIS, which inhibits iodide uptake, is responsible

for concentration of ClO4- in milk. Intra-laboratory studies have shown milk ClO4

- levels to be

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consistently higher than the maternal plasma, and the neonate was found to have significant

blood ClO4- concentrations after nursing from the exposed dams (Yu et al., 2001). Thus, the

infant would be at risk not only from the diminished iodide intake from the milk, but also from

the significant doses of ClO4- received from the milk, and the resulting additional inhibition of

iodide uptake at the neonatal thyroid NIS. The PBPK model described here is able to account for

the changing physiology of the lactating dam and pup, as well as the resulting impact of these

physiological changes on experimentally determined iodide and perchlorate kinetics in order to

provide a meaningful, quantitative estimate of two previously uncharacterized determinants of

neonatal risk: the relative ClO4- dose to maternal and neonatal rats, and the dose-response

relationship between perchlorate exposure and iodide inhibition in the maternal thyroid and milk.

At this stage, the model includes only a rudimentary description of endogenous I- kinetics and

incorporation into thyroid hormones, sufficient to reproduce the kinetics of radioiodide.

METHOD

Supporting Experiments

All supporting experiments were performed on timed-pregnant rats and pups of the

Sprague-Dawley strain (Crl: CD, Charles River Laboratory, Raleigh, NC). Animals were housed

in individual light, heat and humidity controlled cages and were kept on a 12 h light/dark cycle

with access to water and food ad libitum. Euthanization was performed by CO2 asphyxiation on

either postnatal day (PND) 5 or 10 and tissues were collected for analysis of ClO4- or radioiodide

content using the methods described in Narayanan et al. (In Press), respectively. In all

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experiments, pup serum was pooled by sex within individual litters due to small sample volumes.

Pup skin, gastrointestinal (GI) tract, GI contents and maternal tissues were analyzed individually.

Perchlorate Drinking Water Study. Pregnant dams (n=12 per group) were given either

deionized water or water containing perchlorate from gestational day (GD) 2 through the day of

sacrifice. Daily measurements of body weight and water intake were taken to ensure consistent

dosing at levels of 0.0, 0.01, 0.1, 1.0 and 10.0 mg ClO4-/kg-day. Maternal serum, thyroid and

milk, and neonatal serum were collected from the PND 10 groups and analyzed for ClO4-

content. On PND 5, 6 of the dams from each dosing regimen were given a tail vein injection of

33 µg/kg 125I- 2 hours prior to sacrifice. Maternal and neonatal serum, skin, GI contents and GI

tract, as well as maternal thyroid and mammary gland, were collected from these PND 5 rats and

analyzed for ClO4- and 125I-. Thyroid hormones (free and total T4 and T3) and TSH were also

measured in the serum of PND 5 rats that were not dosed with radioiodide.

Radioiodide and Inhibition Kinetic Studies. Lactating dams (6 control, 6 inhibition) were

dosed via tail vein injection to 125I- (average dose = 2.10 ng/kg) on PND 10 and euthanized at

0.5, 2, 4, 8 and 24 h postdosing. Two hours prior to the administration of 125I-, dams from the

inhibition group were given a 1.0 mg/kg ClO4- iv and euthanized at 0.5, 1, 2, 4, 8, 12 and 24 h

post-125I- dosing. This particular ClO4- dose was chosen to be large enough dose to significantly

affect iodide uptake, based on inhibition of thyroid iodide uptake in the male rat (Merrill et al., In

Press), while being lower than the dose required to saturate the symporter, based on the drinking

water study results (see Results section below). Maternal and neonatal serum, skin, GI contents

and GI tract, and maternal thyroid and mammary gland tissue were collected from both control

and perchlorate dosed groups and analyzed for 125I- with a gamma counter.

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Direct Pup Radioiodide Dosing. PND 10 Sprague-Dawley pups (n=6) were given an oral

gavage of 125I- (0.001mg/kg) in water. Pups and nursing dams were euthanized at 0.5, 1, 2, 4, 8

and 24 h postdosing. Neonatal serum, thyroid, skin, GI contents and GI tract, as well as maternal

serum and thyroid were harvested and analyzed for radioiodide content.

Model Structure.

All model code was written in ACSL (Advanced Continuous Simulation Language,

Aegis Technologies Group, Inc., Huntsville, AL). The model structure is based on those of the

male rat and gestation models for iodide and perchlorate kinetics developed concurrently by

Merrill et al. (In Press) and Clewell et al. (In Press). The maternal model (Figure 1A) consists of

compartments for plasma, thyroid, skin, GI, kidney, liver, fat, mammary gland and milk, plus

compartments for the combined slowly and richly perfused tissues. The thyroid, GI and

mammary gland are described with three subcompartments representing the stroma, follicle and

colloid in the thyroid, the capillary bed, GI tissue and GI contents in the GI, and the capillary

blood, tissue and milk in the mammary gland. For iodide, additional compartments representing

the organified (hormone-bound) iodine were included in the thyroid and serum (Figure 1B).

Skin is described with two subcompartments, representing the capillary bed and tissue. Active

uptake into the thyroid follicle and colloid, as well as the skin tissue, mammary gland, milk and

GI contents, was described with Michaelis-Menten (M-M) type kinetics for saturable processes

(bold arrows in Fig. 1). Permeability area cross products and partition coefficients were used to

describe the passive movement of the anions (I- and ClO4-) between the capillary bed, tissue and

inner compartments (small arrows in Fig. 1), which results from the inherent electrochemical

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gradients within these tissues (Chow et al., 1969). The flow-limited kidney, liver and fat

compartments were described with partitions and blood flows. Plasma binding of the inorganic

anions (I- and ClO4-) was simulated using a saturable term for association of the anions to

binding sites in the plasma and a first order clearance rate for dissociation from plasma binding

sites. Urinary clearance and transfer of anions between the dam and pup were represented by

first order clearance rates.

Due to the short time-frame of the radioiodide experiments, the kinetic behavior of total

radioiodine was assumed to behave as free iodide in all compartments other than the thyroid and

plasma. Inorganic iodide and perchlorate were then modeled in the same manner, based on the

similar size and charge of the ions and their shared affinity for NIS (Wolff, 1998). The thyroid,

skin, GI and mammary gland contain active NIS and were therefore defined separately in the

structure of the model (Kotani et al., 1998; Spitzweg et al., 1998). The thyroid, mammary gland,

milk, skin and GI contents have also been found to maintain higher concentrations of ClO4- and

I- than the plasma (Brown-Grant, 1961; Brown-Grant and Pethes, 1959; Chow et al., 1969;

Halmi and Stuelke, 1959; Wolff, 1998; Zeghal et al., 1995). Although other tissues, such as the

salivary gland, ovary and choroid plexus, are also known to sequester iodide and perchlorate in

the rat and human (Brown-Grant, 1961; Honour et al., 1952; Spitzweg et al., 1998), the small

amounts of anions present in these tissues do not affect plasma concentrations. These tissues

were therefore combined in the richly or slowly perfused compartments.

In order to describe free thyroidal iodide, it was necessary to account for the

incorporation of iodide into hormones in the thyroid and the secretion of this incorporated iodine

into the blood. Our goal was to describe this process with enough detail to predict time course

data, while keeping the model as parsimonious as possible. Thus, thyroid hormone production,

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or the incorporation of iodide into hormones, is described using a first order clearance (ClProdci)

of inorganic iodide from the thyroid follicle to the incorporated thyroid iodine compartment.

Secretion of the incorporated iodine into the plasma is also described with a first order clearance

(ClSecrci) from the incorporated thyroid iodine compartment to the incorporated plasma iodine

compartment (Figure 1B). It was not necessary to include a description of hormone

incorporation in the perchlorate model, since ClO4- is not organified or metabolized in vivo

(Anbar et al., 1959).

The incorporated plasma iodine compartment represents combined plasma hormonal iodine,

including free T3 and T4 as well as protein bound T3 and T4, but does not attempt to predict

individual hormone kinetics. Studies of iodine distribution from dietary intake suggest that the

majority (>80%) of serum iodine is, in fact, incorporated into hormones or bound to plasma

proteins (Stolc et al., 1973a). In contrast, studies in our laboratory found that inorganic iodide

accounts for approximately 80% of the total measured plasma radioiodine up to 24 h after an

administered 125I- dose (Mahle et al., 2002). This apparent discrepancy may be explained by the

slow incorporation of administered or ingested iodide into hormones over time. Endogenous

serum iodine data primarily reflect hormone-incorporated iodine, since the system is at steady

state. This normal iodine turnover is well established in the animal when the radioiodide is

introduced. However, the kinetics reflected in the radiolabeled iodide time course is primarily

due to binding of the free anion to plasma proteins, uptake of the anion into various tissues and

urinary clearance. Hormone incorporation would have little effect on these radioiodide kinetics,

due to the long time-frame required to incorporate the radioiodide into hormones in the thyroid

and the slow secretion of these newly produced radiolabeled hormones into the serum. The

model is able to reconcile these data by including an incorporated iodine compartment in the

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plasma, into which the hormone-incorporated iodine enters as it is secreted from the thyroid. A

generic first order rate (ClDeiodci) is then used to describe the overall deiodination accomplished

in the various tissues, allowing the inorganic iodide to re-enter the free plasma compartment.

Some description of plasma binding was required for both anions in order to adequately

reproduce the available data. The inclusion of binding to plasma proteins is especially important

in the case of perchlorate. In fact, at low serum concentrations (<100 µg/L), approximately 99%

of the anion is bound to plasma proteins and at higher concentrations (>500 µg/L), 50% is bound

(Fisher, 2002). Binding of perchlorate to plasma proteins has also been measured in both human

and bovine serum (Carr, 1952; Scatchard and Black, 1949). Iodine also binds to plasma proteins,

but to a lesser extent than ClO4-. Therefore, the model includes a description for the binding of I-

and ClO4- to plasma proteins. Competition of the two anions for plasma binding sites was also

included in the model.

In addition to the reported presence of NIS in the mammary gland (Spitzweg et al.,

1998), studies of perchlorate-induced inhibition of iodide uptake in milk and mammary tissue

support the conclusion that a transport mechanism similar to that of the thyroid exists in the

mammary gland (Brown-Grant, 1957; Grosvenor; 1963; Potter et al., 1959). Furthermore,

hormones produced during lactation, such as prolactin, regulate the mammary gland NIS activity

(Tazebay et al., 2000). Shennan and Peaker (2000) also found evidence of a second anion

transport mechanism in the secretory cells of the mammary gland, suggesting that this transporter

is also able to move iodide and perchlorate against a concentration gradient. This second anion

channel is represented in the model as active uptake into the milk compartment.

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The kidney and liver were separately defined within the structure of the model in order to

describe the rapid urinary clearance of the anions and to allow for future elaboration of the model

that would address hormone metabolism in the liver. A fat compartment was also included to

account for the possible effect of changing fat volume on the kinetics due to the hydrophilic

nature of both anions. Since kidney, liver and fat do not maintain tissue:plasma ratios greater

than one for either anion, these tissues were described as single, flow-limited compartments and

do not contain terms for active uptake. Effective partitioning into these compartments is thought

to result from the electrochemical gradient that moves ClO4- from serum to tissue (Chow and

Woodbury, 1970).

The basic structure of the neonatal model (Figure 1A) is similar to that of the lactating

rat, excluding the mammary gland. In order to simplify the model, all pups from a single litter

were combined together within the model structure. Neonatal dose is described as a first order

transfer rate between the maternal milk and pup GI contents. The anions are then recirculated to

the mother through the pup urine based on the work of Samel and Caputa (1965), showing that

lactating dams ingest approximately 60% of the neonate’s iodine dose while grooming their

pups.

Perchlorate-induced inhibition of iodide uptake was included in the maternal and

neonatal thyroid follicle and colloid, GI contents and skin, as well as the maternal mammary

gland and milk. Literature sources have reported inhibition of iodide uptake into gastric juice of

the male rat (Halmi and Stuelke, 1959) and the milk of the lactating rat (Brown-Grant, 1957;

Grosvenor, 1963; Potter et al., 1959). Studies in our laboratory have also shown consistent

evidence of significant inhibition of iodide uptake in neonatal GI and skin, and slight inhibition

in the maternal skin and mammary gland (Mahle et al., 2002).

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Dosing Procedures.

In order to simulate the daily dosing regimen of the perchlorate drinking water

experiment, a pulse function in ACSL was used to introduce drinking water to the GI contents of

the lactating dam at a constant rate for 12 hours per day (1800 to 0600 hours). The neonate was

dosed continuously throughout the day from the maternal milk. Both the pup milk dose and the

oral bolus dose were introduced into the GI contents of the neonate utilizing pulse functions.

Tail vein injections were simulated by introducing the anions into the intravenous serum

compartment. Dosing for the dietary iodine studies (Stolc et al., 1973a,b) was based on the

iodine content of the feed and supplemented water, as well as published water, milk and dietary

intake data (Stolc et al., 1966) in both the maternal and neonatal rat throughout the postnatal time

period, assuming a constant (24 h/day) intake for both dam and neonate.

Model Parameters.

Model equations are described in the appendix. Whenever possible, physiological and

kinetic parameters were obtained from literature or experiments. Allometric scaling was

generally employed to account for differences in parameters due to variations in body weight of

male, female and neonatal rats. Tissue volumes were scaled linearly by body weight (BW).

Blood flows, maximum velocities, permeability area cross products (PA) and clearance values

were scaled by BW0.75. Pup values were scaled in a similar manner to the maternal parameters.

Physiological and chemical specific parameters were scaled first by the body weight of an

individual pup, as described above, and were then multiplied by the total number of neonates to

represent the value for the entire the litter.

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Physiological Parameters. The physiological description of maternal and neonatal rats

during lactation is based on the work of Fisher et al. (1990), measurements from our laboratory

and published physiological data. Due to the non-uniform changes in tissue volume and body

weight during lactation, it was necessary to include gender and life stage-specific physiological

descriptions whenever possible. Parameters that were not available specifically for the lactating

female or neonate were described by adjusting male rat values by body weight. Final values for

the physiological parameters and sources from which they were obtained are listed in Table 1.

Lactation-specific changes in tissue volumes and suckling rates were included in the

model using ACSL TABLE functions, which employ linear interpolation between available data

points. Maternal body weight was assumed to increase by 12% between PND 1 and 10, based on

the daily measurements of dams in the perchlorate drinking water study described previously.

Since there was no significant difference in the average daily body weights between the five dose

groups, the average body weight from all doses were used. The relative volume of the mammary

tissue increased from 4.4% on PND 2 to 5.6, 6.3 and 6.6% of the maternal body weight on PND

7, 14 and 21, respectively (Knight et al., 1984). Maternal body fat increased from 12.4 to 15.2%

of the body weight between parturition and PND 2, with a subsequent decrease to 6.9% of the

body weight from PND 2 to 16 (Naismith et al., 1982). Values for body fat content on PND 2

and 16 were taken from the measured values of Naismith et al. (1982). Maternal body fat at

parturition was calculated from the previously developed PBPK model for the pregnant rat

(Clewell et al., In Press). Thus, the relative volume of the maternal body fat in the model

increases slightly between PND 1 and 2 and then decreases after PND 2. The rate of milk

production was assumed to be equal to the suckling rate described below.

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As in the maternal tissues, TABLE functions were used to interpolate between reported

data points for the changing body weight, suckling rate and relative tissue volumes in the

neonate. Growth of the neonate is directly dependent on the ingestion of milk. Stolc et al.

(1966) measured both pup body weight and the milk ingestion of suckling rats from birth

through weaning. Although the author used a different strain of rats than was used in our

studies, the pup body weights were nearly identical between the two studies. Thus, the more

comprehensive, published data set of Stolc et al. (1966) was used for these physiological

parameters. Values for neonatal body fat were based on the data of Naismith et al. (1982),

showing a rapid increase from 2.7 to 11% BW between PND 2 and 16 and a subsequent decrease

to the adult value of 4.61% (Brown et al., 1997).

Increase in neonatal thyroid volume was based on the work of Florsheim et al. (1966),

who reported relative thyroid volumes of 0.013, 0.015, 0.012, 0.014, 0.013, 0.013 and 0.013%

body weight for neonates on PND 1 through 5, 7 and 11, respectively. The model also describes

changing thyroid stroma, follicle and colloid fractions over time based on the work of Conde et

al. (1991), who measured the fractional volumes on postnatal days 0, 5, 10, 15, 20, 25, 30, 60

and 120. Relative tissue volumes of the skin, GI tract, liver and kidney were modeled based on

measured body and tissue weights on PND 1, 5, 10, 20, 30 and 64 (Palou et al. 1983). Relative

skin volume increased from 19.3 to 20.8% BW from PND 1 to 20 and then decreased to 19%

BW by PND 30. Similar trends were also seen in the GI, kidney and liver, with increasing

volume (with respect to body weight) peaking at PND 30, 20 and 30, respectively.

All maternal blood flows that were not directly affected by the changes induced by

lactation were scaled allometrically from the adult male rat parameters. TABLE functions were

used to describe the changing in cardiac output and fractional blood flow to the mammary tissue

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throughout lactation, according to the data of Hanwell and Linzell (1973) and the neonatal

cardiac output, hematocrit and regional blood flows, based on the data of Rakusan and Marcinek

(1973). Among other tissues, Rakusan and Marcinek (1973) measured fractional blood flows to

the kidney, liver, skin, stomach and large and small intestines in 1, 30, 60, and 140 day-old rats.

Relative blood flow to the neonatal kidney, liver and total GI are modeled as increasing from 3.6,

4.5 and 4.6 to 15.5, 5.2 and 6.8 % cardiac output, respectively, in the first 60 days. Blood flow

to the skin remains relatively constant after birth, at approximately 11% of the cardiac output.

Chemical Specific Parameters. Chemical specific parameters (Table 2) for perchlorate

and iodide in tissues other than the mammary gland were kept as similar as possible to those

used in the PBPK models for the male and pregnant rat (Merrill et al., In Press; Clewell et al., In

Press) in order to facilitate comparison of the models and extrapolation between life-stages. As

in the previous models, binding of I- to NIS was given a Km of 4.0x 106 ng/L based on the work

of Gluzman and Niepomniszcze (1983) in human thyroid slices. This value for the follicular Km

(KmTFi) remained constant across species (Gluzman and Niepomniszcze, 1983) and tissues

(Wolff, 1998) and was therefore applied to all compartments in the model with NIS. The second

transporter located at the apical membrane in the thyroid was studied by Golstein et al. (1992),

who measured a Km of approximately 4.0 x 109 ng/L for iodide (KmTLi) in bovine thyroid. In

the model, a somewhat lower value than that measured by Golstein et al. of 1.0 x 109 was used

for KmTLi, based on the ability of the model to fit the later (> 8 h) time-points. The Km for the

second active transport mechanism in the mammary gland (KmMk), for milk uptake, was set by

fitting the model simulation to available mammary gland and milk data.

The Km value for ClO4- transport by NIS was given a value of 1.5 x 105 ng/L for all

relevant compartments. This value is based on the assumption that perchlorate acts as a

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competitive inhibitor of iodide uptake and is, in fact, transferred into the tissues via NIS (Clewell

and Gearhart, 2002b). Therefore, the Km value for perchlorate transport by NIS would be equal

to its Ki value. Kosugi et al. (1996) measured the Ki for ClO4- at 1.5 x 105 ng/L. This value was

adjusted slightly to obtain the best fit of thyroid perchlorate to the drinking water data, resulting

in a Km of 2.0 x 105ng/L. This value is further supported by various literature sources suggesting

that ClO4- actually has as much as an order of magnitude greater affinity for NIS than I- itself

(Chow et al., 1969; Halmi and Stuelke, 1959; Harden et al., 1968; Lazarus et al., 1974).

Likewise, the Km values for perchlorate transport by the second anion channels in the thyroid and

mammary gland were also nearly a factor of 10 less than that of iodide, resulting in values of 1.0

x 108 and 1.0 x 106 ng/L for KmTLp and KmMkp, respectively.

The values for Vmax vary significantly across species and tissues with NIS (Glutzman and

Niepomniszcze, 1983; Wolff, 1998) and were, therefore, determined by fitting the model

simulations to available data in the various tissues of PND 5 and 10 rats. In the perchlorate

drinking water study, the non-linearity of tissue ClO4- concentrations across doses in

compartments with NIS suggests that the symporter is saturated between the 1.0 and 10.0 mg/kg-

day doses. Thus at doses below saturation (<1.0 mg ClO4-/kg-day), the active transport via NIS

would drive tissue concentrations and were therefore used to set Vmax values. For iodide, kinetic

data were taken at doses well below the saturation of NIS. Thus, the time course data from the

kinetic studies were used to determine values for Vmax in tissues with active uptake.

Partitioning of ClO4- and I- into tissues results from the electrochemical potential present

across tissue membranes (Chow and Woodbury, 1970). Theoretical effective partition

coefficients were calculated from measured electrical potentials presented by Chow and

Woodbury (1970) using the equations given in Kotyk and Janacek (1977). Calculations are

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described in detail in the male rat perchlorate model (Merrill et al., In Press). Ranges for the

partition coefficients corresponding to the stroma:follicle and follicle:lumen membrane diffusion

were estimated to be 0.11 to 0.15 and 6.48 to 8.74, respectively. Based on the fit of the model

simulation to the data and the calculated values above, values of 0.15 and 7.0 were used for PTFi

and PTLi, respectively.

As mentioned previously, the perchlorate drinking water data indicate that NIS transport

is saturated between the 1.0 and 10.0 mg ClO4-/kg-day doses. Therefore, at 10.0 mg/kg-day,

ClO4- uptake into the various tissues would be predominantly determined by the passive

diffusion parameters. Thus, parameters describing partitioning of ClO4- into the tissues were

obtained by fitting the model simulation to the highest dose group data from the drinking water

study. In the cases where data were not available in the lactating or neonatal rat, such as the

muscle (slowly perfused), liver (richly perfused), kidney and red blood cells, values were

obtained from those used in the adult male rat model (Merrill et al., In Press). The partition

coefficient for perchlorate in fat was measured in the laying hen (Pena et al., 1976). Other

tissues in the hen, such as the muscle and kidney, were found to have similar partition

coefficients to those of the rat.

Iodide partition coefficients and PA values were calculated from the tissue:blood ratios

measured during the clearance phase of data for the tissue of interest either from literature or

experimental data in the rat. The partitioning parameters for the muscle (slowly perfused), liver

(richly perfused), kidney and red blood cells were given the same values measured in the male

rat (Merrill et al., In Press) and the value for partitioning of iodide into the fat was given the

same value as ClO4-.

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Parameters for plasma binding were determined by fitting the model to time course data

in the case of iodide and the 0.01 and 0.1 mg/kg-day drinking water data in the case of ClO4-, due

to the fact that binding was most prevalent at the lower doses. Urinary clearance of ClO4- was

determined from fitting the serum at the 10.0 mg/kg-day dose group, where binding had little

effect on serum concentrations. First-order clearances for incorporation of iodide into thyroid

hormones and hormone secretion were determined by the fit of the model to the incorporated and

free thyroid iodide time course data. Parameters for binding of inorganic iodide to plasma

proteins were determined by the fit of the model simulation to initial portion of the serum

radioiodine data. Later time-points were assumed to be more affected by hormone secretion and

deiodination rates, as sufficient time had passed to allow for incorporation of the administered

radioiodide into hormones. Urinary iodide clearance was determined from the fit of the model to

serum inorganic iodide time course data.

Up-regulation of Thyroid NIS Activity. At the time of data collection in the drinking

water study, rats had been exposed to ClO4- throughout gestation and up to the day of sacrifice.

At this point, up-regulation of the thyroid activity is evidenced by decreased T4 and elevated

TSH levels in the serum at all doses, as well as a lack of noticeable thyroid iodide uptake

inhibition (Yu et al., 2001). Since increased TSH up-regulates thyroid iodide uptake by

increasing the number and activity of NIS (Wolff, 1998), the value for VmaxcTFi, which

corresponds to the maximum capacity of active transport at the basolateral membrane, was

increased to fit the measured radioiodide concentrations in the up-regulated thyroids for each

dose. The resulting values for VmaxcTFi were then plotted versus the corresponding

concentrations of serum free ClO4- and the data were fitted with a Michaelis-Menten (M-M)

equation. This equation then was used in the model to describe the induction of NIS up-

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regulation with dose, in a similar manner to the description used by Andersen et al. (1984) to

describe enzyme induction.

Up-regulation of thyroidal NIS also affects thyroid ClO4- uptake, and hence the

measured thyroid ClO4- concentrations in the drinking water study, as both ClO4

- and I- are

transported by the same symporter (Wolff, 1964, 1998). Thus, increased thyroid ClO4- uptake

was modeled in the same manner as I-, increasing the value for VmaxcTFp with dose and

applying the resulting M-M fit to the model.

Dietary Iodine Model. The dietary iodine model is identical to that of the radioiodine

model. Dosing is accomplished as a constant intake of iodine through water and diet. All

chemical specific parameters are assumed to be the same as those determined from the

radioiodide kinetics. The radioiodide, endogenous iodine and perchlorate models operate

independently in tissues with passive diffusion, and are linked through competitive uptake in

tissues with NIS (e.g,. thyroid follicle). Thus, in tissues governed by passive diffusion,

tissue:blood ratios are identical for the radiolabeled and dietary iodine models. The interaction

of the three models through competitive inhibition at NIS allows us to explore the effect of

varying dietary intake on both radiolabeled iodine kinetics and perchlorate-induced inhibition of

radioiodide uptake in the thyroid.

Sensitivity Analysis of Chemical Specific Parameters. A sensitivity analysis was run after

finalizing the model parameters as to examine the relative influence of each of the chemical

specific parameters on model predictions. The model was run to determine the change in the

average serum ClO4- concentration (AUC: area under the curve) and total thyroid iodide uptake

at 8 hr post-dosing, resulting from a 1% change in the value of each kinetic parameter. In an

effort to determine the effect of NIS saturation on relative parameter importance, the sensitivity

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analysis was performed at two ClO4- doses, presumably representing unsaturated and saturated

symporter states (0.1 and 10.0 mg-kg-day, respectively). Since the iodide doses used in this

model are not expected to saturate the NIS, thyroid iodide sensitivity analysis was run only at the

dose used in the kinetic experiments (2.1 ng/kg 125I-). The following equation shows the

calculation of the sensitivity coefficient for each parameter.

Sensitivity Coefficient = (A - B)/B(C - D)/D

Where A is the serum AUC with 1% increased parameter value, B is the serum AUC at the

starting parameter value, C is the parameter value after 1% increase and D is the original

parameter value.

RESULTS

Model Parameterization.

The ClO4- data from the drinking water study were used to determine kinetic parameters

for ClO4- in the lactating and neonatal rat. Up-regulation of NIS transport of ClO4

- into the

thyroid was accounted for as described in the Methods section. Figure 2 shows the model

simulations for ClO4- concentrations in the maternal and neonatal serum, maternal thyroid, GI

contents, mammary gland and milk, versus measured data from the drinking water study on PND

5 and 10 at 0.01, 0.1, 1.0 and 10.0 mg ClO4-/kg-day. The up-regulated values for Vmaxc_TFp

were used in the simulation of the thyroid as described in the Methods section. In these and

subsequent plots, solid lines indicate the model prediction and cross-bars indicate the mean ±

standard deviation (SD) of measured data.

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Neonatal iodide kinetic parameters were determined by the fit of the model to the data

obtained from directly dosing the pup, while maternal parameters were primarily determined

from the data obtained by dosing the dam via iv. Transfer from the neonate to the dam was

established by fitting the maternal kinetic parameters first and then utilizing maternal data from

the pup dosing study to determine the magnitude of iodide transfer to the maternal stomach via

pup urine. In the same way, milk transfer was parameterized by first fitting the neonatal

parameters from the pup dosing study and then utilizing the pup data from the maternal dosing

kinetic study to estimate pup exposure via milk. PA values were adjusted to describe the

behavior of iodide data, where increasing PA values toward 1.0 L/h-kg generally increased the

rate at which uptake and clearance in a particular tissue occurred, and decreasing PA slowed

uptake and clearance. Model simulations of radioiodide kinetics in maternal and neonatal tissues

versus the data obtained from dosing the dams are shown as the control group in the inhibition

study (Figure 3). The fit of the model to iodide levels in maternal and neonatal tissues from the

direct oral dosing of PND 10 pups are shown in Figure 4. The model was able to reproduce data

in both maternal and neonatal tissues, whether exposure occurred via maternal iv or oral bolus to

the pup. Thus, the model is able to describe both maternal to neonatal and neonatal to maternal

iodide transfer, and is also able to reproduce data across exposure routes.

Model Validation. Once model parameters were established as described above, the robustness

of the model was tested against a variety of data sets taken across different laboratories, rat

strains, exposure routes and time points in lactation. Several published kinetic studies using

various isotopes of iodide were used to test the model description of iodide kinetics in the dam

and neonate (see below). Accuracy and usefulness of the model perchlorate and iodide

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descriptions were further validated against studies of perchlorate-induced inhibition of iodide

uptake in the maternal thyroid, mammary gland, milk and neonatal tissues based on the

description of competitive binding to NIS.

Radioiodide Kinetics on PND 10. Validation of PND 10 iodide kinetics was performed

with the data of Iino and Greer (1961), Samel and Caputa (1965), Vigouroux (1976) and

Vigouroux and Rostaqui (1980). In order to simplify comparison of the different data sets,

which were originally performed at slightly different dose levels, the data of each study were

normalized to a dose of 1.0 ng. The model simulation was then run versus the combined data

sets (Figure 5). Figures 5A and 5B show the maternal and neonatal thyroid radioiodide levels on

PND 10 following an acute 131I- dose to the dam. The model is able to predict the maternal

thyroid iodide, but underpredicts pup thyroid iodide levels at the 24 h time point. However, the

model prediction is within a factor of two of the measured data. Figures 5C and 5D show the

model-predicted maternal and neonatal thyroid iodide levels after an ip dose to the pup. The

model simulation is able to describe both maternal and neonatal thyroid uptake, again within a

factor of two.

The data of Samel and Caputa (1965) also allowed validation of the model parameters for

urinary output in the pup. Difficulty in separating maternal and pup urine precluded the

collection of these data in our own studies. Therefore, urinary clearance values in the model

were determined by the fit of the serum to the time course data. Using the previously determined

kinetic parameters, the model-predicted urinary iodide, 4 hours after an iv dose of 131I- in the

PND 10 rat, was 14% of the pup dose, which is close to the range of values (0.61 to 10.9%)

given by Samel and Caputa (1965).

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Radioiodide Kinetics on PND 5. In order to determine whether the model would provide

reasonable predictions of iodide and perchlorate kinetics in younger pups (<PND 10), the model

was tested against data obtained in our laboratory after a single iv injection of 125I- on PND 5 of

the ClO4- drinking water study. Since the control group did not receive perchlorate during the

study, tissue 125I- data from these animals can be used to confirm the model’s ability to predict

kinetics in PND 5 rats. Figure 6 shows that the model-predicted radioiodide concentrations in

the maternal serum, thyroid and mammary gland and neonatal serum are in good agreement with

the available data on PND 5.

Up-regulation of thyroid NIS activity was modeled against the thyroid iodide levels

measured after 23 days of exposure to perchlorate in drinking water at doses of 0.01, 0.1, 1.0,

and 10.0 mg ClO4-/kg-day as was described in the Methods section. Using this equation for the

up-regulation of the follicular Vmaxc (VmaxcTFi) , it was possible to describe the increase in

iodide uptake based on the perchlorate dose in chronic exposure scenarios. Neither the measured

data nor the model showed any inhibition in iodide concentrations in the maternal thyroid 2 h

postdosing with 125I- after 18 days of exposure to 0.01, 0.1, 1.0 and 10.0 mg/kg ClO4- in drinking

water. Thus, the model was able to describe the up-regulation of thyroid NIS activity resulting

from subchronic perchlorate exposures.

Radioiodide Kinetics in Late Lactation. The model’s ability to simulate iodide kinetics at

later time points in lactation (>PND 10) was tested against the normalized data of several

literature studies. Figure 7 shows the model-predicted radioiodide milk:plasma ratio versus the

data of Brown-Grant (1957), Grosvenor (1963) and Potter et al. (1959) collected on PND 14, 17-

20 and 18, respectively. Although the simulation shown in Figure 7 was run on PND 14, there is

no noticeable change in the model-predicted milk:plasma ratio when run at different days in

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lactation. Despite the changing kinetics (body composition, suckling rate, etc.), the model

prediction of relative iodide concentration in the milk remains constant. Although the amount of

milk provided to the infant may change during the course of lactation, the concentration of iodide

does not. This assumption is supported by the available data, which do not show any increasing

or decreasing trend in milk iodide concentrations. Dietary iodine studies by Stolc et al. (1966;

1973a,b) also showed a relatively unchanging milk iodine concentration through the different

stages of lactation. The model predictions are in reasonable agreement with the trend suggested

by the total composite of the different data sets.

The maternal urinary iodide was tested against the data of Grosvenor (1960). For the

reasons mentioned previously, urine was not collected in our own studies. Thus, model

parameters for maternal urinary clearance (ClUci) were determined by fitting the model

simulation to serum time course data, while maintaining fits to data in the thyroid, mammary

gland and pup. Using these previously set parameters, the model predicts that 40.8% of the 131I-

dose will be excreted within 8 hours post-131I- dosing, which is within the range of 36.7 to 42.1%

reported in Grosvenor’s 1960 study.

Perchlorate-induced Inhibition of Iodide Uptake. The ability of the model to predict

inhibition of iodide uptake into the thyroid, milk and other tissues is not only important in

calculating risk to the dam and neonate, but is also indicative of the model’s ability to accurately

describe both perchlorate and iodide kinetics. Thus, the available data for perchlorate-induced

inhibition of iodide kinetics in lactation was used as the final validation of the current model

structure. Using the conditions for the inhibition time course study described in the methods

section, the model simulation was run to predict the effect of the administration of 1.0 mg ClO4-

/kg on the kinetic behavior of an iv dose of radioiodide (given 2 h post-ClO4- dosing). Figure 8

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shows that the model accurately simulates inhibition of iodide uptake in the maternal thyroid and

mammary gland. The simulations of the iodide inhibition kinetics in the mammary gland also

suggest that the model is able to predict the affect of perchlorate exposure on the availability of

iodide to the neonate. Although NIS inhibition would occur in both maternal GI and skin,

neither the data nor the model showed significant difference between the control and ClO4- dosed

animals, suggesting that other factors (i.e. diffusion, partitioning) are offsetting the effects of

symporter inhbition.

The model-predicted inhibition of both milk and thyroid iodide was validated against the

data of Potter et al. (1959). Potter and coauthors measured the amount of radioiodide ( 131I-)

taken up into the thyroid gland and the combined mammary gland and expressed milk 24 h after

dosing with iodide in PND 18 rats. The total effect on iodide uptake was measured after two

ClO4- doses given 1 h prior to and 30 min after the radioiodide dose. At these large doses of

ClO4-, thyroid iodide uptake is essentially blocked (approximately 99% inhibition). Therefore, it

is likely that the NIS transport of iodide into the mammary gland is also completely inhibited.

However, unlike the thyroid, the milk still showed significant amounts of iodide (approximately

10% of the control value at 24 h). It is possible that the second mammary transport mechanism

is responsible for this difference in tissue response to ClO4- exposure, because it depletes iodine

content in the mammary gland to the extent that passive diffusion between the gland and the

blood becomes significant. In contrast, passive diffusion of iodine into the thyroid is restricted

by the slow clearance via secretion of hormones into the blood, as well as the lower permeability

and partitioning of the anions suggested by the model. The ability of the model to predict the

combined mammary gland and milk control and ClO4- dosed data of Potter et al. (1959) (Figure

9) supports the accuracy of the description of iodide partitioning in the mammary gland and the

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second active transporter. The model predicts the data remarkably well despite significant

differences between this study and those used for model development, such as different time

points in lactation (PND 18 vs. 10) and a different dosing regimen.

Dietary Iodine. In three separate experiments, Stolc et al. (1966; 1973a,b) studied the

distribution of endogenous iodine in various tissues of the maternal and neonatal rat resulting

from a controlled intake of iodine through the diet and water. Model-predictions of the maternal

and neonatal tissue iodine concentrations are shown in Figure 10 versus data collected at water

and feed concentrations of 60 ng I/g and 500ng I/mL, respectively (Stolc et al., 1973b), which

corresponds to daily doses of 4.8 mg I/kg-d. Of the three dosing levels presented by Stolc and

coauthors, this highest dose was chosen to validate the model prediction of normal iodine

distribution, due to the fact that it is within the range of normal dietary intake for rats and it is

closest to dietary intake expected for our experimental studies (800 ng I/mg food). The two

lower dose groups would be considered moderately deficient and deficient iodine diets, resulting

in changes in the H-P-T axis in order to affect up-regulation as is evidenced by the measured

tissue iodine concentrations. Despite a 5-fold difference in water iodide concentrations, the

serum and thyroid concentrations remain unchanged. Other tissues, including the skin and GI,

do show a dose-dependent change in tissue concentration. Thus, since this model does not yet

include the pharmacodynamic response of the thyroid axis to dietary insufficiency, it is

premature to attempt to predict such data. Using kinetic parameters obtained from acute data,

the model is generally able to predict endogenous data within a factor of 2 of the measured data

for tissue concentrations ranging over more than four orders of magnitude (Figure 10).

While admittedly only a preliminary description, this endogenous iodine model could be

exercised to assess the affect of changing dietary intake on predicted acute radioiodide kinetics,

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as well as predicted perchlorate-induced inhibition of radioiodide kinetics in the perinatal and

adult rats. Since the radioiodide, endogenous iodine and perchlorate models operate

independently in tissues with passive diffusion, and are linked through competitive uptake in

tissues with NIS (e.g thyroid follicle), only tissues with active uptake are expected to show any

change in tissue concentrations with varying dietary intake. From this modeling exercise, it was

determined that the effects of changes in dietary iodine intake on acute radioiodide kinetics are

likely to be negligible. In fact, significant differences in predicted thyroid concentrations were

not observed at feed concentrations as high as 8.0 ppm (more than an order of magnitude higher

than standard laboratory diet). Indeed, the first apparent change in predicted inhibition of

thyroidal radioiodide uptake is seen at feed concentrations 100 times greater than standard

laboratory rat chow.

Sensitivity Analysis. Sensitivity analysis performed at 0.1 and 10.0 mg ClO4-/kg-day

drinking water revealed a dose-dependent difference in model sensitivity to several of the

chemical specific parameters (Figure 11). At 0.1 mg/kg-day, the maternal serum is primarily

dependent on serum binding, showing less sensitivity to urinary clearance. All other parameters

had calculated sensitivity coefficients less than 0.1. At the 10.0 mg/kg-day dose, binding

parameters are no longer important determinants of predicted serum levels. Only the urinary

clearance remains significant, with a sensitivity coefficient of – 0.87. Neonatal serum ClO4-

levels are influenced by several model parameters at the 0.1 mg/kg-day dose, including the

parameters defining passive diffusion and active transfer in the mammary gland, milk and

neonatal GI. However, similar to dam, neonatal serum AUC shows the greatest sensitivity to

serum binding parameters at this lower dose. At the higher dose (10.0 mg/kg-day), where active

uptake into the mammary gland and serum binding are likely saturated, partitioning into

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mammary gland and milk and urinary clearance (both maternal and neonatal) show the greatest

influence on pup serum ClO4- levels. Results of the sensitivity analysis for thyroid iodide uptake

(not shown) were similar, in that the magnitude of all of the parameter sensitivities were less

than one, although model predictions for this metric were sensitive to a much larger number of

input parameters. This result is not unexpected due to the fact that the uptake prediction is for a

specific point in time after administration of the radioiodide, and the rate of distribution into all

tissues can effect the time-dependent result (as compared to an average, or AUC, measure, which

reflects steady-state behavior). Thus, the validation of the model with kinetic thyroid iodine

uptake and inhibition data provides a reasonable test of the model parameterization.

Calculation of Internal Dose Metrics

The model was used to calculate internal dose metrics corresponding to both acute and

subchronic perchlorate exposure in the lactating and neonatal rat. These internal measures of

dose include: area under the curve (AUC) for ClO4- in the maternal and neonatal serum, relative

neonatal dose (% maternal dose) and inhibition of thyroid iodide uptake after acute dosing.

Table 3 shows the predicted neonatal dose on PND 10 as % maternal dose and as an amount

adjusted for milk intake and pup body weight. The model predicts a significant transfer of

maternal ClO4- to the neonate on PND 10 at low maternal doses. In fact, per kg body weight, the

PND 10 pup receives a greater dose than the dam (0.07 vs. 0.01 mg/kg BW). Tables 4 and 5

show the dose metric comparisons between the adult male, pregnant, fetal, lactating and neonatal

rats for serum ClO4- AUCs from drinking water exposure, as well as thyroid iodide inhibition

after acute iv exposures in the adult male, GD 20 pregnant and fetal rats, and the PND 10

lactating and neonatal rats. The internal dose metrics in the lactating and neonatal rat were

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compared to those of the male (Merrill et al., In Press), pregnant and fetal rat (Clewell et al., In

Press) in order to provide insight on relative exposure at different life stages. From Tables 4 and

5, it is apparent that while the lactating rat shows the highest serum ClO4- concentrations, the

fetal rat actually shows the greatest inhibition of thyroid iodide uptake.

DISCUSSION

The PBPK model is able to describe iodine kinetics across doses, exposure routes and

time points during lactation for both acute dosing and dietary iodine studies. The iodide model

was simplified by assuming that radiolabeled iodide could be described as free iodide in all

compartments other than the thyroid and plasma. Simulations were performed against total

radioiodide concentrations in extrathyroidal tissues and against inorganic and incorporated iodide

in thyroid and serum. Despite this simplification, the model is able to describe radiodide data in

maternal and neonatal tissues from PND 5 through 18 over doses spanning more than 4 orders of

magnitude, as well as distribution data from dietary iodine intake. Thus, the model description

of extrathyroidal tissue iodide uptake based on the transfer of inorganic iodide via NIS predicts

the data reasonably well without the added uncertainty or complexity of significant contribution

from the uptake of incorporated radioiodine by extrathyroidal tissues.

Although preliminary extrapolation of the acute iodide kinetic model to long-term

exposure scenarios compares favorably with the data, this model does not yet address the

feedback mechanisms involved in maintaining normal iodine homeostasis. However, the model

predicted interaction between dietary and administered radioiodide does indicate that the small

variations in laboratory rat chow expected between studies should not affect model predictions of

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radioiodide distribution or perchlorate-induced inhibition of thyroid radioiodide uptake. At the

dietary intake required to affect competition for NIS, serum levels would be high enough (>250

µg/L) to trigger a response from the thyroid known as the Wolff-Chaikoff effect, wherein the

thyroid appears to expel inorganic iodide from the cells (Wolff and Chaikoff, 1948). In order to

address cases of dietary iodine excess or deficiency, future elaborations of the model would have

to include a more detailed description of hormone distribution, homeostasis and regulation.

However, the present model should be useful for predicting tissue dosimetry and inhibition of

thyroid iodide uptake in the rat and for extrapolation to the average human with a normal iodide

diet.

The PBPK model described here also successfully reproduces measured perchlorate and

radioiodide distribution kinetics in the lactating rat and neonate. The model simulates ClO4-

distribution and transfer via breast milk with reasonable accuracy in drinking water exposures

ranging over three orders of magnitude (0.01 - 10.0 mg/kg-day) and at two time-points in

lactation, PND 5 and 10. In the absence of acute perchlorate kinetic data in rat lactation, we rely

on the consistency of this model structure and its parameters with those of the male rat (Merrill

et al., In Press), which successfully describes such data. Having accounted for differences in

physiology due to lactation, most of the remaining chemical specific parameters remain

essentially unchanged from those of the adult male rat. Therefore, we can assume that, like the

male rat model, the acute perchlorate kinetics can be adequately described with model structure

based on iodide kinetics. This is further supported by the ability of the model to predict acute

iodide inhibition kinetics, as inhibition of thyroid uptake is dependent on free serum perchlorate

levels. Additionally, in terms of exposure route, drinking water dosing is actually more relevant

to the risk assessment. Thus, the model is able to describe distribution to the target tissues and in

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the serum resulting from exposure via the route that is most applicable to that of humans. The

accuracy of the model ClO4- description allows us to answer two vital questions in determining

risk across life stages: 1) the dose to the neonate and 2) the relative sensitivity, with respect to

tissue dose and thyroid iodide inhibition, compared to the non-pregnant and pregnant adult, as

well as to the fetus (Tables 3 through 5).

Experiments in our laboratory have confirmed that perchlorate was indeed transferred to

the pup through suckling through the detection of ClO4- in milk, as well as in the neonate serum,

GI contents and skin (Figure 2). However, the small number of data points and the difficulty in

determining ingestion of milk, loss through urinary clearance and other competing processes

made the determination of neonatal dose quite difficult by classical methods. Because the model

accounts for physiological and kinetic differences, it is able to provide a reasonable estimate of a

previously uncharacterized measure of risk, ClO4- dose to the neonate (Table 3). In fact, the

model predicts that the pup receives a 7-fold greater perchlorate dose than the dam on PND 10

when adjusted for body weight at the lowest experimental dose (0.01 mg ClO4-/kg-day). This

difference between the maternal and neonatal dose disappears, however, at higher doses (10 mg

ClO4-/kg-day), where toxicity would be expected.

Additional calculations were performed with the model to determine the AUC for

perchlorate in serum across doses and life stages. Serum, rather than thyroid, perchlorate

concentration was designated as a dose metric for life-stage and species comparison.

Perchlorate’s action on the thyroid is the inhibition of iodide uptake, leading to diminished

intrathyroidal I- levels and potentially decreased hormone production. Since thyroid iodide

uptake inhibition is dependent on serum ClO4- levels, this variable was determined to be a more

appropriate dose metric by which to judge relative sensitivity to later effects. By comparing these

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measures of average serum concentrations across life stages, valuable insight can be gained

regarding relative sensitivity to perchlorate exposure. Thus it is evident that, despite the

increased dose to the neonate (0.07 vs. 0.01 mg/kg-day in the adult), the PND 10 pup serum

average ClO4- concentrations are consistently lower than those of the adult. In fact, a

comparison across life stages reveals that the serum ClO4- concentrations of the lactating dam

were slightly higher than the male, pregnant, fetal or neonatal rat, suggesting that lactation may

be the time period with the greatest internal perchlorate exposure. This increased serum

concentration of ClO4- in the lactating rat, suggested by both model simulations and measured

data, is somewhat surprising, considering the additional clearance route provided through the

milk, and is likely due to increased serum binding (Iino and Greer, 1961).

In developing the perchlorate thyroid model, some assumptions were made concerning

the mode of action, as well as in the designation of values for some of the parameters. The

model structure is highly dependent on the chosen definition of the mode of action, which in the

case of perchlorate involves the competitive binding of the perchlorate ion to NIS, resulting in

diminished I- thyroidal uptake and the active concentration of ClO4- in the thyroid cells.

Although it has been suggested that ClO4- may not be transferred into the thyrocytes based on

electrogenicity studies in oocytes (Soldin, 2002), the larger body of evidence suggests otherwise.

Specifically, published studies with both radiolobeled and cold perchlorate consistently report

thyroid: serum ratios that are greater than 1 and as much as 30 (Chow and Woodbury, 1970;

Clewell et al., 2002b; Clewell et al., In Press; Yu et al., 2002). Furthermore, ClO4- has been

shown in studies in our laboratory to be concentrated in all of the measured extra-thyroidal

tissues known to contain NIS, including the GI contents, skin and milk (see Figure 2 and Clewell

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et al, 2002b; Yu et al., 2002). A more detailed justification for the use of competitive inhibition

is available elsewhere (Clewell and Gearhart, 2002b).

Thus, this model structure is based upon competitive inhibition of iodide at the

symporter. However, despite the obvious influence this interpretation has on predicted internal

thyroid ClO4- levels, it actually has very little influence on the either thyroid iodide inhibition or

serum ClO4- levels. Since the relative thyroid volume is very small, the total amount of chemical

is quite low in spite of the high concentrations. Therefore, large changes in predicted thyroid

concentrations do not significantly affect blood levels. Additionally, the ability of ClO4- to

inhibit iodide uptake is based on the relative affinities and the amount of free ClO4- in the blood,

rather than the amount of perchlorate in the thyroid itself. Thus, the active uptake of perchlorate

into the thyroid cells, though included for pharmacokinetic accuracy, does not affect the

usefulness of the model for comparing life-stage and species differences in the precursors to

hormone disruption.

Linking the perchlorate and iodide models via competitive inhibition at the symporter

also enables the model to predict ClO4--induced inhibition of iodide uptake in the maternal and

neonatal tissues after acute ClO4- exposure in the lactating rat. Because ClO4

- has a greater

affinity for NIS than I-, it effectively inhibits uptake not only into the thyroid, but also into the

milk, stomach and skin. The model accurately predicts data on this inhibition of iodide uptake in

the maternal thyroid mammary gland and milk from our studies and those of Potter et al. (1959).

Although data are not available directly in the neonate, confidence in the model predictions is

increased by the ability of the maternal model, as well as the previously described sister models

in the male, pregnant and fetal rat (Clewell et al., In Press; Merrill et al., In Press), to describe

this inhibition using the same mechanistic construct and validated chemical specific parameters.

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Thus, the model provides a means for estimating neonatal inhibition of thyroid iodide in the

absence of such data.

The ability of ClO4- to reduce iodide levels in the milk, as well as uptake in thyroid,

presents a potentially increased health risk to the neonate. In order to quantitatively determine

the effect of maternal ClO4- exposure on the transfer of iodide in breast milk and subsequent

neonatal thyroid levels, the model predicted percent inhibition in maternal and neonatal thyroids

were compared to those generated for the male, pregnant and fetal rat with the models of Merrill

et al. (In Press) and Clewell et al. (In Press). In spite of the multiple inhibition sites (mammary

gland, milk and thyroid), inhibition in the neonatal thyroid was similar to that of the dam. This

may be due to the fact that neonatal serum perchlorate levels are less than those of the dam.

From the model estimates given in Table 5, the neonate shows less perchlorate-induced

inhibition of thyroid iodide uptake compared to the other life stages in the rat. Model estimates

suggest that the fetal rat thyroid is most vulnerable to inhibition, with a 10-fold greater inhibition

than the neonate at the lowest measured dose (0.01 mg/kg ClO4-).

Thus, it is possible to utilize these pharmacokinetic models to develop reasonable

estimates of internal dose metrics based on quantitative biological concepts and a variety of data

collected in different conditions, species and life stages. The chosen dose metrics are measures

of internal dose, and should be better indicators of relative risk than external dose (i.e.

perchlorate intake). However, these internal dose metrics are merely measures of the precursor

kinetics and do not give a complete picture of perchlorate’s affect on hormone homeostasis.

Indeed, determining which life stage is at greatest risk actually depends on the chosen precursor

dose metric. Of those presented in this paper, utilizing serum ClO4- levels indicates that the

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lactating dam is at highest risk, while thyroid iodide inhibition suggests the fetus is the most

sensitive life stage.

In reality, many factors must be taken into consideration when assessing the risk

associated with perchlorate exposure. For example, although the predicted thyroid inhibitions

across life stages indicate that the fetal thyroid is most vulnerable, overall risk to the fetus may

actually be less than that of the neonate. This is due to the fact that inhibition of thyroid iodide

uptake is only a precursor to hormone disruption. In gestation, maternal thyroid hormones are

available to the fetus, as opposed to lactation, where the neonate is responsible for its hormone

synthesis. Therefore, the maternal hormones may compensate for the increased inhibition seen

in the fetal thyroid resulting in less chance of adverse developmental effects. In fact, in the

developmental studies of York et al. (1999; 2001), the pregnant dam showed the greatest change

in serum TSH and T4 levels. Thus, it is possible that the additional pharmacodynamic

interactions (hormone synthesis, metabolism, etc.) could result in a relative risk profile not at all

suggested by the preliminary measurements of tissue dose or pharmacokinetic perturbations. For

this reason, further elaboration of these models to include hormone homeostasis and the

pharamocodynamic interactions is critical to improve the risk assessment for perchlorate.

This model allows the integration of a wide variety of physiological, biochemical and

dosimetry information, to produce parameter estimates consistent with measured perchlorate and

iodide kinetic data during important periods of development. In order to further assess model

performance, other analytical tools can be applied to the model, including statistical evaluation

of the goodness of model fit to present data sets, more comprehensive sensitivity analyses for

multiple dosimetrics and assessment of the effects of parameter variability on dose measures.

Sensitivity analysis (Figure 11) provides insight into the relative importance of model parameters

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with respect to specific measures of dose. The variability analysis, performed with known

distributions for model parameters, allows the prediction of likely ranges of the dosimetrics

within a human population. For the application of risk assessment, incorporation of a more

comprehensive evaluation of variability of the more sensitive model parameters will be more

important than a formal estimation with the present data sets.

An informative use of this PBPK model is in the correlation of predicted internal

dosimetrics to periods in gestation where perchlorate exposure and/or iodide deficiency has been

associated with developmental effects. The model can be used to predict tissue dosimetry in

effects studies and to pinpoint specific times in development fetal/neonatal iodide uptake is most

critical.

Further elaboration of these models to extrapolate dosimetry to humans has been

explored elsewhere (Clewell et al., 2001; Clewell and Gearhart, 2002a). Together with the

models of Merrill et al. (2001; In Press) and Clewell et al. (In Press), this model can be used to

approximate species and life stage kinetic differences at specific doses. Furthermore, since these

PBPK models to relate complex pharmacokinetic variables back to the basic physiological and

biochemical parameters that are often measurable, we can use the comparative information

provided by the PBPK models about the chemical kinetics to develop quantitative estimates of

species and life stage differences. Thus, it is possible to extrapolate these models to the

population of interest (human gestation and lactation), in order to run simulations for sensitive

human populations at a variety of exposure scenarios to estimate internal dose (Clewell et al.,

2001).

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ACKNOWLEDGEMENTS

The animals used in in-house studies were handled in accordance with the principles

stated in the Guide for the Care and Use of Laboratory Animals, National Research Council,

1996, and the Animal Welfare Act of 1966, as amended.

The authors would like to thank Tammie Covington, Harvey Clewell, Dr. Melvin

Andersen and Dr. Peter Robinson for their modeling advice; Latha Narayanan and Gerry Buttler

for sample analyses; Charles Goodyear for performing statistical analyses of the data; and Dick

Godfrey, Peggy Parish, Susan Young, TSgt Todd Ligman, MSgt Jim McCafferty, Tim Bausman,

SSgt Paula Todd and MSgt Rick Black for technical support. The authors would like to

acknowledge Annie Jarabek, LtCol Dan Rogers, Dr. David Mattie, Dr. Richard Stotts and the

U.S. Air Force for their support of this project and the U.S. Navy for financial support.

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Figure Titles

Figure 1. (A) Schematic of perchlorate PBPK model for lactating dam (left) and neonate (right).

Model structure for sister iodine model is similar. Differences are contained within the inset area

outlined with the dashed line. (B) Thyroid and serum compartments for radioiodide, with

additional compartments for the incorporation of iodide into hormones in the thyroid and

secretion of the hormones into the serum incorporated iodine compartment as is discussed in the

Methods section.

Figure 2. Perchlorate concentration in maternal (A) serum (Clewell et al., 2001) (B) thyroid (up-

regulated) (Clewell et al., 2001) (C) GI contents (D) mammary gland (E) milk (Clewell and

Gearhart, 2002a) and (F) male neonatal serum (Clewell and Gearhart, 2002) at the 0.01, 0.1, 1.0

and 10.0 mg/kg-day doses on PND 5 and 10. Solid lines indicate model prediction. Cross-bars

indicate mean ± SD of the measured data.

Figure 3. Concentration of maternal (A) inorganic radioiodide in serum, (B) plasma bound

radioiodine, (C) thyroidal inorganic radioiodide and incorporated radioiodine, (D) mammary

gland and neonatal (E) serum after an iv dose to the dam of 2.10 ng/kg 125I- on PND 10.

Figure 4. Concentration of neonatal (A) plasma bound radioiodine and plasma inorganic

radioiodide, (B) thyroidal incorporated radioiodine and inorganic radioiodide, (C) GI contents

(●) and skin (□) radioiodide and (D) maternal total serum and thyroid radioiodine after an oral

gavage of 1.0 ng/kg 125I- to the pup on PND 10.

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Figure 5. Amount of radioiodide in (A) maternal and (B) neonatal thyroid after iv dose to dam

and in (C) maternal and (D) neonatal serum after iv dose to pup on PND 10 versus the

normalized data (1.0 ng 131I-) of (○) Iino and Greer (1961), (■) Samel and Caputa (1965), (▲)

Vigouroux (1976) and (●) Vigouroux and Rostaqui (1980).

Figure 6. Radioiodide concentration in maternal serum, mammary gland, thyroid and neonatal

serum versus the measured data after an iv dose of 33,000 ng/kg 131I- to the dam on PND 5.

Figure 7. Radioiodide milk:plasma concentration after an iv dose to the dam versus the combined

literature data. The data points represent individual measurements provided in (▲) Brown-Grant

(1957), (●) Grosvenor (1963) and (■) Potter et al. (1959) on PND 14, 18 and 17-20, respectively.

Figure 8. Iodide concentration in (A) maternal thyroid and (B) mammary gland with and without

1.0 mg/kg ClO4- iv dose 2 hours prior to an iv dose of 2.10 ng/kg 125I- to the dam on PND 10.

The top simulation (solid line) and data (□) indicate the control group. The lower simulation

(dashed line) and data (■) indicate inhibition.

Figure 9. Radioiodide concentration in milk with and without ClO4- (Clewell et al., 2001).

Perchlorate doses of 25 mg and 12.5 mg were given to the dam 30 min before and 4 h after

administration of 131I-, respectively. The top simulation and data (▲) indicate the control group.

The lower simulation and data (●) indicate the inhibition group. Data points represent milk

samples from individual dams from Potter et al. (1959).

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Figure 10. Model predicted tissue iodine vs. measured data of Stolc et al. (1973b) with a normal

dietary intake (approx. 560 ng/day). Standard deviations were given with the measured maternal

data only.

Figure 11. Calculated sensitivity coefficients for model parameters with respect to serum

perchlorate AUC at drinking water doses of 0.1 and 10.0 mg/kg-day.

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Neonate

KidneyQK

Urine

KidneyQK

Urine

RBCs

bound

free

PlasmaQC

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QT

QS

LiverQL

RichlyPerfused

QR

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Skin

SkinBlood

Skin

SkinBlood QSK

FatQF

CA

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GITissue

GIBlood

QG

QG

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Plasma

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Lactating Female

RBCs

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free

PlasmaQC

Ivc

SlowlyPerfused

QT

QS

LiverQL

RichlyPerfused

QR

Colloid

ThyroidFollicle

Stroma

Skin

SkinBlood QSK

FatQF

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QG

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Milk

Mammary Tissue

Mammary Blood

(inset)

Lactating Female

RBCs

bound

free

PlasmaQC

Ivc

SlowlyPerfused

QT

QS

LiverQL

RichlyPerfused

QR

Colloid

ThyroidFollicle

Stroma

Skin

SkinBlood

Skin

SkinBlood QSK

FatQF

CA

GIContents

GITissue

GIBlood

QG

QG

pDose

Plasma

QM

Milk

Mammary Tissue

Mammary Blood

(inset)

Figure 1A.

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RBCs

I-

QC

Ivc

QT

Colloid

ThyroidFollicle

Stroma

CA

Plasma

(inset)

Alb-I-Alb-T3, Alb-T4, fT3, fT4

IncorporatedAlb-T3, Alb-T4, fT3, fT4

Incorp. Bound

RBCs

I-

QC

Ivc

QT

Colloid

ThyroidFollicle

Stroma

CA

Plasma

(inset)

Alb-I-Alb-T3, Alb-T4, fT3, fT4

IncorporatedAlb-T3, Alb-T4, fT3, fT4

Incorp. Bound

Figure 1B.

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0 64 128 192 256 320

0.01

0.1

1.0

10.0

Time after Parturition (hours)

Perc

hlor

ate

in M

ater

nal S

erum

(m

g/L

)

A

0 64 128 192 256 320

0.01

0.1

1.0

10.0

Time after Parturition (hours)

Perc

hlor

ate

in M

ater

nal S

erum

(m

g/L

)

A

0 64 128 192 256 320

0.1

1.0

10

100

Time after Parturition (hours)

Perc

hlor

ate

in M

ater

nal T

hyro

id (

mg/

L)

B

0 64 128 192 256 320

0.1

1.0

10

100

Time after Parturition (hours)

Perc

hlor

ate

in M

ater

nal T

hyro

id (

mg/

L)

B

0 64 128 192 256 320

0.1

1.0

10

100

Time after Parturition (hours)

Perc

hlor

ate

in M

ater

nal G

I C

onte

nts

(mg/

L) C

0 64 128 192 256 320

0.1

1.0

10

100

Time after Parturition (hours)

Perc

hlor

ate

in M

ater

nal G

I C

onte

nts

(mg/

L) C

320256192128640

0.01

0.1

1.0

Time after Parturition (hours)

Perc

hlor

ate

in M

amm

ary

Gla

nd (

mg/

L)

D

320256192128640

0.01

0.1

1.0

Time after Parturition (hours)

Perc

hlor

ate

in M

amm

ary

Gla

nd (

mg/

L)

D

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Figure 2

0 64 128 192 256 320

0.01

1.0

10.0

Time after Parturition (hours)

Perc

hlor

ate

in M

ilk

(mg/

L)

0.1

E

0 64 128 192 256 320

0.01

1.0

10.0

Time after Parturition (hours)

Perc

hlor

ate

in M

ilk

(mg/

L)

0.1

E

Time after Parturition (hours)

0 64 128 192 256 320

0.01

0.1

1.0

10.0

Perc

hlor

ate

in M

ale

Neo

nata

l Ser

um (

mg/

L) F

Time after Parturition (hours)

0 64 128 192 256 320

0.01

0.1

1.0

10.0

Perc

hlor

ate

in M

ale

Neo

nata

l Ser

um (

mg/

L) F

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238.0 244.4 250.8 257.2 263.6 270.0

Time after iodide administration (hours)

0

1

2

3

4

5

Tot

al R

adio

iodi

nein

Ser

um (

ng/L

)

A

238.0 244.4 250.8 257.2 263.6 270.0

Time after iodide administration (hours)

0

1

2

3

4

5

Tot

al R

adio

iodi

nein

Ser

um (

ng/L

)

238.0 244.4 250.8 257.2 263.6 270.0

Time after iodide administration (hours)

0

1

2

3

4

5

0

1

2

3

4

5

Tot

al R

adio

iodi

nein

Ser

um (

ng/L

)

A

238.0 244.4 250.8 257.2 263.6 270.0

Time after iodide administration (hours)

0.0

0.2

0.4

0.6

0.8

1.0

Bou

nd I

odin

e* in

Ser

um (

ng/L

)

B

238.0 244.4 250.8 257.2 263.6 270.0

Time after iodide administration (hours)

0.0

0.2

0.4

0.6

0.8

1.0

0.0

0.2

0.4

0.6

0.8

1.0

Bou

nd I

odin

e* in

Ser

um (

ng/L

)

B

238.0 244.4 250.8 257.2 263.6 270.0

Time after iodide administration (hours)

10

100

1000

Rad

ioio

dine

in T

hyro

id (

ng/L

)

Free Inorganic Radioiodide

Total Radioiodine

C

238.0 244.4 250.8 257.2 263.6 270.0

Time after iodide administration (hours)

10

100

1000

10

100

1000

Rad

ioio

dine

in T

hyro

id (

ng/L

)

Free Inorganic Radioiodide

Total Radioiodine

C

238.0 244.4 250.8 257.2 263.6 270.0

Time after iodide administration (hours)

0

4

8

12

16

20

Tot

al R

adio

iodi

ne in

Mam

mar

y G

land

(ng

/L) D

238.0 244.4 250.8 257.2 263.6 270.0

Time after iodide administration (hours)

0

4

8

12

16

20

0

4

8

12

16

20

Tot

al R

adio

iodi

ne in

Mam

mar

y G

land

(ng

/L) D

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Figure 3

238.0 244.4 250.8 257.2 263.6 270.0

0.3

0.6

0.9

1.2

1.5

0.0Tot

alR

adio

labe

led

Iodi

de in

Mal

e N

eona

te S

erum

(n

g/L

)

Time after iodide administration (hours)

E

238.0 244.4 250.8 257.2 263.6 270.0

0.3

0.6

0.9

1.2

1.5

0.0Tot

alR

adio

labe

led

Iodi

de in

Mal

e N

eona

te S

erum

(n

g/L

)

Time after iodide administration (hours)

E

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Figure 4

240 315300285270255

100

102

Time after iodide administration (hours)

Rad

ioio

dine

in M

ater

nal T

issu

es (

ng/L

)

Thyroid

Serum

104

101

103

105

D

240 315300285270255

100

102

Time after iodide administration (hours)

Rad

ioio

dine

in M

ater

nal T

issu

es (

ng/L

)

Thyroid

Serum

104

101

103

105

D

240 315300285270255

10

100

1000

Time after iodide administration (hours)

Rad

ioio

dine

in N

eona

te S

erum

(ng

/L)

Total Iodine

Bound Iodine

A

240 315300285270255

10

100

1000

Time after iodide administration (hours)

Rad

ioio

dine

in N

eona

te S

erum

(ng

/L)

Total Iodine

Bound Iodine

240 315300285270255

10

100

1000

Time after iodide administration (hours)

Rad

ioio

dine

in N

eona

te S

erum

(ng

/L)

Total Iodine

Bound Iodine

A

240 315300285270255

103

104

Time after iodide administration (hours)R

adio

iodi

nein

Neo

nate

Thy

roid

(ng

/L)

Total Iodine

Free Iodide

105

106

B

240 315300285270255

103

104

Time after iodide administration (hours)R

adio

iodi

nein

Neo

nate

Thy

roid

(ng

/L)

Total Iodine

Free Iodide

105

106

B

240 315300285270255

102

103

Time after iodide administration (hours)

Rad

ioio

dine

in N

eona

te T

issu

es (

ng/L

)

GI Contents

Skin

104

C

240 315300285270255

102

103

Time after iodide administration (hours)

Rad

ioio

dine

in N

eona

te T

issu

es (

ng/L

)

GI Contents

Skin

104

C

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Figure 5

Time after iodide administration (hours)

Rad

ioio

dide

in M

ater

nal T

hyro

id (

ng)

0.2

0.4

0.0

1.0

0.8

0.6

Dose Administered to Dam

15 25201050

A

Time after iodide administration (hours)

Rad

ioio

dide

in M

ater

nal T

hyro

id (

ng)

0.2

0.4

0.0

1.0

0.8

0.6

Dose Administered to Dam

15 25201050

A

Time after iodide administration (hours)R

adio

iodi

de in

Neo

nata

l Thy

roid

(ng

)

0.2

0.4

0.0

1.0

0.8

0.6

Dose Administered to Dam

15 25201050

B

Time after iodide administration (hours)R

adio

iodi

de in

Neo

nata

l Thy

roid

(ng

)

0.2

0.4

0.0

1.0

0.8

0.6

Dose Administered to Dam

15 25201050

B

15

Time after iodide administration (hours)

Rad

ioio

dide

in M

ater

nal T

hyro

id (

ng)

25201050

0.08

0.16

0.00

0.40

0.32

0.24

Dose Administered to NeonateC

15

Time after iodide administration (hours)

Rad

ioio

dide

in M

ater

nal T

hyro

id (

ng)

25201050

0.08

0.16

0.00

0.40

0.32

0.24

Dose Administered to NeonateC

Time after iodide administration (hours)

Rad

ioio

dide

in N

eona

tal T

hyro

id (

ng)

0.4

0.8

0.0

2.0

1.6

1.2

Dose Administered to Neonate

15 25201050

D

Time after iodide administration (hours)

Rad

ioio

dide

in N

eona

tal T

hyro

id (

ng)

0.4

0.8

0.0

2.0

1.6

1.2

Dose Administered to Neonate

15 25201050

D

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Figure 6

3

Time after iodide administration (hours)

Rad

ioio

dide

Con

cent

rati

on (

ng/L

)

54210

103

104

105

102

107

Maternal Thyroid

Maternal Serum

106

Mammary Gland

Neonatal Serum

3

Time after iodide administration (hours)

Rad

ioio

dide

Con

cent

rati

on (

ng/L

)

54210

103

104

105

102

107

Maternal Thyroid

Maternal Serum

106

Mammary Gland

Neonatal Serum

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Figure 7

Time after iodide administration (hours)

Rad

ioio

dide

Mil

k:Pl

asm

a R

atio

16

32

0

80

64

48

15 25201050

Time after iodide administration (hours)

Rad

ioio

dide

Mil

k:Pl

asm

a R

atio

16

32

0

80

64

48

15 25201050

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Figure 8

0.0 30.023.617.210.84.4

0

1200

Time after perchlorate administration (hours)

Rad

ioio

dine

in M

ater

nal T

hyro

id (

ng/L

)

Control

Perchlorate

2400

600

1800

3000

0.0 30.023.617.210.84.4

0

1200

Time after perchlorate administration (hours)

Rad

ioio

dine

in M

ater

nal T

hyro

id (

ng/L

)

Control

Perchlorate

2400

600

1800

3000

238.0 270.0263.6257.2250.8244.4

0

6

Time after perchlorate administration (hours)

Rad

ioio

dine

in M

amm

ary

Gla

nd (

ng/L

)

Control

Perchlorate

12

3

9

15

B

238.0 270.0263.6257.2250.8244.4

0

6

Time after perchlorate administration (hours)

Rad

ioio

dine

in M

amm

ary

Gla

nd (

ng/L

)

Control

Perchlorate

12

3

9

15

B

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Figure 9

Time after Parturition (hours)460454.2448.4442.6463.8431

Rad

ioio

dide

in M

ilk

(ng/

L)

0.0

1.2

2.0

0.4

0.8

1.6 Control

Perchlorate

Time after Parturition (hours)460454.2448.4442.6463.8431

Rad

ioio

dide

in M

ilk

(ng/

L)

0.0

1.2

2.0

0.4

0.8

1.6

Time after Parturition (hours)460454.2448.4442.6463.8431

Rad

ioio

dide

in M

ilk

(ng/

L)

0.0

1.2

2.0

0.4

0.8

1.6 Control

Perchlorate

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Figure 10.

1.0E+00

1.0E+01

1.0E+02

1.0E+03

1.0E+041.0E+05

1.0E+06

1.0E+07

1.0E+08

1.0E+09

Dam T

hyro

id

Dam B

ound

Ser

um

Dam S

kin

Dam G

IM

ilk

Pup T

hyro

id

Pup B

ound

Ser

um

Pup S

kin

Pup G

I

Iod

ine

Co

nce

ntr

atio

n (

ng

/L)

PredictedTissueConcentration

MeasuredTissueConcentration

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-1-0.8-0.6-0.4-0.2

00.20.40.60.8

1

Vmax

cBKm

B

Kunbc

ClUc

PMPM

k

Vmax

cM

Vmax

cMk

KmM

PaMc

PG_F

PGJ_F

Vmax

cG_F

PAGJc_F

ClUc_

F

Vmax

cB_F

Kunbc

_F

Sen

siti

vity

Co

effi

cien

t

Dam Serum AUC - 0.1 mg/kg-d Dam Serum AUC - 10.0 mg/kg-d

Pup Serum AUC - 0.1 mg/kg-d Pup Serum AUC - 10.0 mg/kg-d

Figure 11.

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Table 1. Physiological Parameters

Parameters Lactation SourceTissue Volumes Dam Neonate

Body Weight BW (kg)0.277 -0.310 0.0075 - 0.1985 Yu et al., 2001

Slowly Perfused VSc (%BW) 37.07-40.42 53.92-49.31 Brown et al., 1997Richly Perfused VRc (%BW) 5.35 5.36 Brown et al., 1997Fat VFc (%BW) 12.45 - 6.9 0.0 - 4.61 Naismith et al., 1982Kidney VKc (%BW) 1.7 1.7 Brown et al., 1997Liver VLc (%BW) 3.4 3.4 Brown et al., 1997Stomach Tissue VGc (%BW) 3.9 3.9 Merrill et al., In PressGastric Juice VGJc (%BW) 7.2 7.2 Yu et al., 2002Stomach Blood VGBc (%VG) 2.9 2.9 Altman & Dittmer, 1971Skin Tissue VSkc (%BW) 19.0 19.0 Brown et al., 1997Skin Blood VSkBc (%VSkc) 2.0 2.0 Brown et al., 1997

Thyroid Total VTc (%BW) 0.0105 0.0125Malendowicz & Bednarek, 1986; Florsheim et al., 1966

Thyroid Follicle VTFc (%Vttot) 45.89 61.4 - 37.2

Malendowicz & Bednarek, 1986; Conde et al.,1991

Thyroid Colloid VTLc (%VTtot) 45 18.3 – 32.5

Malendowicz & Bednarek, 1986; Conde et al.,1991

Thyroid Blood VTBc (%VTtot) 9.1 20.3 – 30.3

Malendowicz & Bednarek, 1986; Conde et al.,1991

Plasma VPlasc (%BW) 4.7 4.7Brown et al., 1997, Altman & Dittmer, 1971

Red Blood Cells VRBCc (%BW) 2.74 2.74

Brown et al., 1997, Altman & Dittmer, 1971

Mammary Tissue VMc (%BW) 4.4 - 6.6 --- Knight et al., 1984Mammary Blood VMBc (%VM) 18.1 --- Assume same % as Thyroid BloodMilk VMk (L) 0.002 --- Fisher et al., 1990Blood Flows

Cardiac Output QCc (L/h/kg) 14.0 - 21.0 14.0Hanwell & Linzell, 1973; Brown et al., 1997

Slowly Perfused QSc (%QC) 7.9-1.9 16.9 Brown et al., 1997Richly Perfused QRc (%QC) 40.8 40.8 Brown et al., 1997Fat QFc (%QC) 7.0 7.0 Brown et al., 1997Kidney QKc (%QC) 14.0 14.0 Brown et al., 1997Liver QLc (%QC) 18.0 18.0 Brown et al., 1997GI QGc (%QC) 1.61 1.61 Brown et al., 1997Skin QSkc (%QC) 0.058 0.058 Brown et al., 1997Thyroid QTc (%QC) 1.6 1.6 Brown et al., 1997Mammary QMc (%QC) 9.0 - 15.0 --- Hanwell & Linzell, 1973

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Table 2. Chemical Specific ParametersParameters Perchlorate Iodide

Partition Coefficients (unitless) Dam Pup Dam PupSlowly Perfused / Plasma PS 0.31 0.31 0.21 0.21Rapidly Perfused / Plasma PR 0.5 0.5 0.4 0.4Fat/ Plasma PF 0.05 0.05 0.05 0.05Kidney/ Plasma PK 0.99 0.99 1.09 1.09Liver/Plasma PL 0.56 0.56 0.44 0.44Gastric Tissue/Gastric Blood PG 1.80 3.21 1.00 1.20Gastric Juice/Gastric Tissue PGJ 2.30 5.64 1.00 1.00Skin Tissue/Skin Blood PSk 1.15 1.15 0.70 1.00Thyroid Tissue/Thyroid Blood PTF 0.13 0.13 0.15 0.15Thyroid Lumen/Thyroid Tissue PTL 7.0 7.0 7.0 7.0Red Blood Cells/Plasma PRBC 0.73 0.73 1.00 1.00Mammary Tissue/ Mammary Blood PM 0.66 --- 0.80 ---Mammary/Milk PMk 2.39 --- 1.00 ---Max Capacity, Vmaxc (ng/h/kg)Thyroid Follicle VmaxcTF 1.5x103 1.50x103 5.0x104 1.3x104

Thyroid Colloid VmaxcTL 1.0x104 1.0x104 6.0x107 6.0x107

Skin VmaxcS 8.0x105 8.0x105 4.0x105 2.5x105

GI VmaxcG 1.0x106 1.0x106 2.0x106 2.0x106

Mammary VmaxcM 2.0x104 --- 8.0x105 ---Milk VmaxcMk 2.0x104 --- 4.0x105 ---Affinity Constants, Km (ng/L)Thyroid Follicle KmTF 1.5x105 1.5x105 4.0x106 4.0x106

Thyroid Lumen KmTL 1.0x108 1.0x108 1.0x109 1.0x109

Skin KmS 1.5x105 1.5x105 4.0x106 4.0x106

GI KmG 1.5x105 --- 4.0x106 ---Mammary KmM 1.5x105 --- 4.0x106 ---Milk KmMk 1.0x106 --- 1.0x107 ---

Permeability Area Cross Products, (L/h-kg)Gastric Blood to Gastric Tissue PAGc 1.00 1.00 0.80 0.04Gastric Tissue to Gastric Juice PAGJc 1.00 1.00 0.60 0.09Thyroid Blood to Thyroid Tissue PATFc 4.0x10-5 4.0x10-5 1.0x10-4 1.0x10-4 Thyroid Tissue to Thyroid Lumen PATLc 0.01 0.01 1.0x10-4 1.0x10-4 Skin Blood to Skin Tissue PASkc 0.50 1.00 0.20 0.02Mammary Blood to Mammary Tissue PAMc 0.01 --- 0.02 ---Mammary Tissue/Milk PAMkc 0.10 --- 0.02 ---Plasma to Red Blood Cells PARBCc 1.00 1.00 1.00 1.00

Clearance Values, (L/h-kg)Urinary excretion CLUc 0.07 0.0075 0.06 0.012Fraction of pup urine ingested by dam 0.80 0.80Hormone productions rate ClProdc_i --- --- 0.1 0.06

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Hormone secretion rate ClSecrc_i --- --- 7.0x10-7 1.0e-6 Deiodination --- --- 0.02 0.025Binding ConstantsVmaxcB 9.0x103 2.0x103 1.5x103 500KmB 1.0x104 1.0x104 1.0x105 1.0x105

Kunbc 0.034 0.01 0.09 0.05

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Table 3. Model-predicted Perchlorate Dose to the Pup from Maternal Drinking Water

Exposure on PND 10

Maternal Dose(mg/kg-day)

Pup Dose(mg/kg-day)

Relative Pup Dose(% Maternal Dose)

0.01 0.07 49.9

0.1 0.66 45.8

1.0 2.82 19.0

10.0 9.08 6.3

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Table 4: Model Predicted Internal Dosimetrics: Serum ClO4- AUC (mg/L) in Male,

Pregnant, Fetal, Lactating and Neonatal Rat from Drinking Water Perchlorate Exposure

ClO4- Dose

(mg/kg-day)

MaleRat

Pregnant Rat

(GD20)

FetalRat

(GD20)

Lactating Rat

(PND 10)

Neonate Rat

(PND 10)0.01 0.05 0.05 0.02 0.06 0.030.1 0.16 0.17 0.10 0.22 0.141.0 0.60 0.61 0.32 0.65 0.5410.0 1.52 1.56 0.62 4.63 1.72

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Table 5: Model Predicted Internal Dosimetrics: %Inhibition of Thyroid Iodide Uptake in

Male, Pregnant, Fetal, Lactating and Neonatal Rat from Acute Perchlorate Exposure

ClO4- Dose

(mg/kg/day)MaleRat

Pregnant Rat

FetalRat

Lactating Rat

NeonateRat

0.01 1.7 2.5 4.1 0.3 0.40.1 17.9 25.4 36.0 3.4 4.41.0 76.0 87.1 88.8 49.0 53.810.0 90.6 93.4 95.7 92.5 94.9

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Appendix

The following equations represent the distribution of iodide within the thyroid, in the

absence of competitive inhibition (Eq. 1-6). Perchlorate uptake into the thyroid is described

similarly, but without the organification (ClProdi) and hormone secretion (ClSecri) terms.

(Equation 1) ( ) iii

iiiii RupTFCTS

PTF

CTFPATFCTSCAQTRATS −

−∗+−∗=

(Equation 2) ( )iii

i

iii

i

iiiii CTFodClCTF

PTL

CTLPATLRupTL

PTF

CTFCTSPATFRupTFRATF ∗−

−∗+−

−∗+= Pr

(Equation 3)

−∗+=

i

iiiii PTL

CTLCTFPATLRupTLRATL

(Equation 4)ii

iii CTSKmT

CTSTFVRupTF

+∗

=max

(Equation 5)ii

iii CTFKmTL

CTFTLVRupTL

+∗

=max

(Equation 6) ( ) ( )iiiii CTbndClSecrCTFodClRAbnd ×−×= Pr

RATSi, RATFi RATLi and RABndi are the rates of change in the amount of inorganic

iodide in the thyroid stroma, follicle, colloid (lumen) and the rate of change in the amount of

organic or incorporated iodine in the total thyroid, respectively. PATFi, PATLi and PTFi, PTLi

are the PAs and effective partition coefficients for the stroma:follicle and follicle:colloid

membranes, respectively. RupTFi and RupTFi are the active uptake rates of iodide into the

follicle and colloid. VmaxTFi, VmaxTLi and KmTFi, KmTLi are the maximum velocities and

affinity constants for transport of iodide into the follicle and colloid. QT represents fractional

blood flow to the thyroid capillary bed. CAi, CTSi, CTFi, CTLi and CTbndi are the iodide

concentrations in arterial plasma, thyroid stroma, follicle, colloid and the incorporated

(organified) iodine compartment, respectively.

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The inhibited thyroid is described in the same manner as shown above, except that the

Michaelis-Menten terms for active uptake are modified to account for competitive inhibition.

The following equation gives an example of the description of competitive inhibition of iodide

uptake by perchlorate. As before, RupTFi represents the rate of active iodide uptake into the

thyroid follicle. This rate is modified by the affinity of transport mechanism in the follicle for

ClO4- (KmTFp) and the concentration of ClO4

- in the stroma (CTSp). Inhibition of iodide uptake

in other tissues with NIS is described in the same manner as the thyroid follicle inhibition.

(Equation 7)

ip

pi

iii

CTSKmTF

CTSKmTF

CTSTFVRupTF

+

+∗∗

=

1

max

The model description of uptake iodide uptake in the milk with competitive inhibition at

both transporters is shown in equations 8 through 12. Equations for perchlorate would be

similar, but without the terms for competitive uptake. RAMBi, RAMi, and RAMki are the rate of

change in the amount of iodide in the mammary gland capillary blood, the mammary gland

tissue, and the milk, respectively. RupMi and RupMki represent the rate of active uptake of

iodide into the mammary gland and the milk. VmaxMi, VmaxMki and KmMi, KmMki are the

maximum velocities and affinity constants for the active transport of iodide into the mammary

gland and milk. QM represents fractional blood flow to the mammary gland capillary bed.

PAMi, PAMki, PMi, and PMki are the permeability area cross products and partition coefficients

used to describe the passive diffusion of iodide between the capillary blood and mammary gland,

and the mammary gland and milk, respectively. CAi, CMBi, CMi and CMki are the iodide

concentrations in arterial plasma, mammary capillary blood, mammary gland and milk. Ktrans

represents the rate of milk production, which is assumed to be equal to the suckling rate.

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(Equation 8) ( ) iii

iiiii RupMCVMB

PM

CMPAMCVMBCAQMRAMB −

−×+−×=

(Equation 9)

−×+−+

−×= i

i

iiii

i

iiii CM

PMk

CMkPAMkRupMkRupM

PM

CMCVMBPAMRAM

(Equation 10) ( )ii

iiiii CMkKtrans

PMk

CMkCMPAMkRupMkRAMk ×−

−×+=

(Equation 11)

ip

pi

iii

CMBKmM

CMBKmM

CMBMVRupM

+

+∗∗=

1

max

(Equation 12) ip

p

i

iii

CMKmMk

CMKmMk

CMMkVRupMk

+

+∗∗

=

1

max

The model description for active uptake of iodide into the GI contents with competitive

inhibition by ClO4- is given in equations 13 through 16. The skin compartment is modeled in the

same manner. Equations for perchlorate would be similar to those of iodide without the terms

for competitive inhibition. Here RAGBi RAGi and RAGJi represent the rates of change in the GI

capillary blood, GI tract and GI contents, respectively. QG is the regional blood flow to the GI,

RMR is the rate of oral dosing, and CGBi CGi and CGJi are the total iodide concentration in the

GI blood, tract and contents. Finally, partitioning of iodide between the GI blood and tract and

the GI tract and contents is described using the partition coefficients (PGi and PGJi) and

permeability area cross products (PAGi and PAGJi).

(Equation 13)) ( )

−×+−×= ii

iiiii CVGBPG

CGPAGCVGBCAQGRAGB

(Equation 14)i

iii

ii

iiii RupGJCGPGJ

CGJPAGJPGCGCVGBPAGRAG −

−×+

−×=

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(Equation 15)i

iii

iii RMRPGJCGJCGPAGJRupGJRAGJ +

−×+=

(Equation 16)i

p

pi

ii

CGKmGCG

1KmG

CGGJmaxVRupGJi

+

+×

×=

Model equations for compartments without active uptake (shown for the liver, Eq. 17)

were modeled in the as flow-limited, using only partitioning and blood flow to control tissue

iodide and perchlorate concentrations. In the following equations, RALi is the rate of change in

the amount of total iodide in the liver, QL is the fractional blood flow to the liver, CLi is the

concentration of iodide in the liver and PLi is the blood:liver partition coefficient. The kidney

and fat are modeled similarly.

(Equation 17)

−×=i

iii PL

CLCAQLRAL

Model equations describing iodine in the arterial blood are given below (Eq. 18 –19). Where

RaBndi and RaIncorpi are the rates of change in amount of iodide bound to plasma proteins and

hormone incorporated iodine, respectively. VmaxBi and Kmi are the Michaelis-Menten terms for

saturable binding of inorganic iodide to plasma proteins. Kmp is the affinity constant for the

binding of ClO4- to plasma proteins, which is used to adjust the affinity of iodide in order to

mathematically describe the competitive inhibition of the anions for binding sites. Kunbi, Ksecri

and Kdeiodi are the first order rate constants for the dissociation of I- from plasma proteins, the

secretion of thyroid hormones (hormone incorporated iodine) form the thyroid and the whole-

body deiodination of thyroid hormones, respectively. CAi and CAp are the concentrations of free

inorganic iodide and free ClO4- in the plasma. The binding of perchlorate to plasma proteins

would be described in the same manner as iodide (Eq. 18).

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(Equation 18)

( ) ( )ii

ip

pi

iii CAbndKunb

CAKmBCA

KmB

CABVRabnd ×−

+

+×

×=)1(

max

(Equation 19)( ) ( )iii CAIncorpKDeiodCTbndKSecrRaIncorp ×−×=

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