ToxSci Advance Access originally published online on November 17, 2007
Toxicological Sciences 2008 102(1):15-32; doi:10.1093/toxsci/kfm286
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Published by Oxford University Press 2007.
Predicting Maternal Rat and Pup Exposures: How Different are They?
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* National Research Council Research Associateship Program at U.S. Environmental Protection Agency, Research Triangle Park, North Carolina
US EPA Human Studies Facility, 104 Mason Farm Road, Chapel Hill, North Carolina 27599
National Center for Computational Toxicology, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711
2 To whom correspondence should be addressed at National Center for Computational Toxicology, B205-1, Office of Research and Development, US Environmental Protection Agency, 109 TW Alexander Dr., Research Triangle Park, NC 27711. Fax: (919)-541-1994. E-mail: habarton{at}alum.mit.edu.
Received September 17, 2007; accepted November 14, 2007
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMETHODSRESULTSDISCUSSIONSUPPLEMENTARY DATAFUNDINGREFERENCES |
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Risk and safety assessments for early life exposures to environmental chemicals or pharmaceuticals based on cross-species extrapolation would greatly benefit from information on chemical dosimetry in the young. Although relevant toxicity studies involve exposures during multiple life stages, the mother's exposure dose is frequently used for extrapolation of rodent toxicity findings to humans and represents a substantial source of uncertainty. A compartmental pharmacokinetic model augmented with biological information on factors changing during lactation and early postweaning was developed. The model uses adult pharmacokinetics, milk distribution, and relevant postnatal biology to predict dosimetry in the young for chemicals. The model addressed three dosing strategies employed in toxicity studies (gavage, constant ppm diet, and adjusted ppm diet) and the impact of different pharmacokinetic properties such as rates of clearance, milk distribution, and volume of distribution on the pup exposure doses and internal dosimetry. Developmental delays in clearance and recirculation of chemical in excreta from the pup to mother were evaluated. Following comparison with data for two chemicals, predictions were made for theoretical chemicals with a range of characteristics. Pup exposure was generally lower than the mother's with a shorter half-life, lower milk transfer, larger volume of distribution, and gavage dosing, while higher with longer half-life, higher milk transfer, smaller volume of distribution, and dietary exposures. The present model demonstrated pup exposures do not always parallel the mother's. The model predictions can be used to help design early life toxicity and pharmacokinetic studies and better interpret study findings.
Key Words: early life dosimetry; biological modeling; lactational exposure.
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONSUPPLEMENTARY DATAFUNDINGREFERENCES |
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Evaluating potential risks from early life exposures is more challenging than evaluating risks in adults, in part, because the relevant toxicity studies including one- or two-generation reproductive, developmental, and developmental neurotoxicity studies involve multiple life stages (e.g., gestation, lactation, and postnatal growth of offspring). Currently, the average daily dose given to the mother is used for extrapolation to humans, even when the effects are observed in the offspring. To improve extrapolation of animal toxicity data to humans, information on chemical dosimetry in the young during critical developmental windows would be needed (Barton, 2005
). However, dosimetry data from early life exposures are scarce for environmental chemicals, and even for pharmaceuticals, in multigeneration studies. Poorly characterized pup dosimetry during lactational and early postweaning periods is a substantial source of uncertainty in the extrapolation of rodent toxicity findings to humans along with uncertainty in the identification of critical developmental windows. In recent years, predictions of perinatal internal exposures have been made using computational pharmacokinetic modeling for a number of environmental and pharmaceutical chemicals (reviewed in Corley et al. (2003)). However, it is generally difficult to develop a full physiologically based pharmacokinetic model because of limitations on pharmacokinetic information during the relevant periods as well as limited information regarding physiological parameters for early life stages (e.g., gestation, lactation, and early postweaning).
Knowledge of pup dosimetry can contribute not only to applying study results in evaluating risks but also for improving toxicity study designs. A critical factor determining chemical concentrations in pups would be the extent and pattern of maternal chemical exposure because it determines chemical concentrations in the adult animal in repeated dosing scenarios (Saghir et al., 2006; Yuan, 1993). Several different dosing approaches are used in toxicity studies including diet, drinking water, gavage, and, if appropriate, dermal and inhalation. Although dietary exposure often represents a relevant exposure method for chemicals, in some cases it is difficult to use due to technical problems preparing chemical-fortified diet or a need to accurately determine maternal dose levels leading to the use of gavage dosing. Only limited consideration has been given to potential differences in the amount of chemical transferred to the suckling neonates resulting from gavage versus dietary administration of a compound (Arnold et al., 2000). There has been a concern about the potential overexposure during lactation due to highly increased maternal food consumption during this period, which has been discussed as a potential cause of misinterpretation of increased neonatal toxicity during lactation (Hanley and Watanabe, 1985). To that end, a modified dietary administration regimen is sometimes employed in reproductive toxicity study, which adjusts the chemical concentration in diet based on historical food intake data during lactation to maintain relatively constant exposures during this period (Hanley et al., 2002).
The present study was intended to provide a tool to predict pup dosimetry using limited biological and pharmacokinetic properties of test compounds and, thus, to help design toxicity or pharmacokinetic studies in early postnatal periods as well as to help understand findings from such studies. The goals of this research were to evaluate whether one could use data on adult pharmacokinetics and milk transfer in conjunction with a biologically based model to predict pup dosimetry to a reasonable approximation and then evaluate how different pharmacokinetic properties (e.g., rates of clearance and milk distribution) would affect the pup exposure doses (e.g., from milk) and circulating concentrations. A classical compartmental pharmacokinetic modeling approach was employed, which was supported by biological information on changing factors (e.g., increasing pup body weight) during lactation and early postweaning period. Three dosing approaches employed in toxicity studies (i.e., unadjusted ppm diet, adjusted ppm diet, and gavage) were simulated to compare resulting maternal and neonatal dosimetry. Model performance was evaluated by comparing the model to previously reported lactational exposure data for two chemicals. Subsequently, exposures were simulated for 16 theoretical compounds with a variety of different characteristics benchmarked from environmental chemicals and/or pharmaceuticals. The properties of these theoretical test compounds are listed in Table 1, categorized in six cases varying elimination rate, volume of distribution, and milk transfer. The present model simulates pharmacokinetics in the dam and pups for the parent compound only. This model enables simultaneous consideration of several factors with potential effects on pup exposures and consequently provides a means to predict the overall impact of these factors on dosimetry in the young. From the results of this modeling exercise, we have begun to derive general insights about pup exposures and different study designs for chemicals with different properties.
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METHODS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONSUPPLEMENTARY DATAFUNDINGREFERENCES |
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Model Structure
The model was coded and all the simulations were performed using acslXtreme (version 2.0.1.7, Aegis, Inc., Huntsville, AL). The structure of the biologically based pharmacokinetic model for chemical exposures of the dam and pups is illustrated in Figure 1. Simulation of chemical exposures was performed for 28 days after birth, of which the first 21 days were the lactational period followed by 1 week postweaning. The model describes changes in body weight, milk production and consumption, and food consumption during those 4 weeks as well as exposure by three methods—gavage, unadjusted feeding, or adjusted feeding. All abbreviations and symbols used in describing the model structure are listed in the legend of Figure 1. Equations for parameter values that change over the duration of simulation are presented in Table 2. Values for two other parameters, BWd and Vm, which change during the simulation period were incorporated in the model using TABLE functions in acslXtreme as explained later in this section. All other chemical parameters are listed in Table 3.
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Model Structure for the Dam
The present model uses a one-compartment pharmacokinetic model structure, in which the dam and pups were each represented as one central compartment. Elimination of a test chemical (e.g., metabolic or urinary) was described as a first-order process with a rate constant, Ked (per hour); saturable metabolism was not modeled. Elimination of chemical from the dam through milk was modeled as a separate process determined by another elimination rate constant, KL (per hour) (Fig. 1). The chemical absorption process of the dam was a first-order process described by Kad (per hour). The model structure for dosing is detailed in a following section. The volume of distribution of the dam compartment (Vd) was defined as a product of the body weight–normalized volume of distribution (Vdd, l/kg) with the body weight of the dam (BWd, kg).
Changes in the amount of the test chemical in the dam (mg/h) are described in Equations 1–3, where Ad represents the amount of chemical in the dam (mg). The overall chemical change in the dam was a function of the chemical absorbed from the absorption site (RABd), elimination (Ked x Ad), and secretion via milk (KL x Ad) (Equation 1).
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 | (2) |
 | (3) |
Equation 2); the amount of chemical available for absorption (AGd) was defined by the total amount of chemical available for absorption (Fd x Dosed) minus the amount of chemical absorbed into the dam (ABd) (Equation 3). Fd represents systemic availability of a given chemical, which was set to 1 in the current model. Dosed indicates the amount of chemical given to dam via the selected dosing method. The chemical concentration in the dam was obtained by dividing the amount of chemical by the volume of distribution (Cd = Ad/Vd, mg/l).
Model Structure for the Pups
All the pups from a single litter, eight pups per litter, were combined together as one compartment within the model structure. Exposure of pups to chemical was modeled as occurring either through milk during lactation or by direct dosing after weaning (e.g., unadjusted feeding or gavage). Total elimination of chemical due to metabolism and/or urinary excretion was described as a single first-order process with a rate constant, Kep (per hour). Saturable metabolism was not modeled in the pups. A first-order rate constant Kap (per hour) was utilized to describe the chemical absorption process of the pups. The volume of distribution of the pup compartment (Vp) was defined as a product of body weight–normalized volume of distribution (Vdp, l/kg) with body weight of an individual pup (BWp, kg) multiplied by the litter size (N = 8).
The Equations 4–6 describe changes in the amount of the test chemical in the litter (mg/h). Ap represents the amount of chemical in the N pups.
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Equation 6 and will be described in the following section. The chemical concentration in the pups was the amount of chemical in the total litter divided by the volume of distribution of an individual pup multiplied by the number of pups per litter (Cp = Ap/(Vp x 8)). When modeling developmental delays in elimination, Kep was modeled to be proportionally related with the mother's value, i.e., following Kep = R x Ked, where R indicates the developmental pattern of pups’ elimination capacity. Delayed development of elimination was modeled using a Michaelis-Menten type curve (Table 2).
Structure for Lactational Transfer
The dam and pup compartments were connected with a conceptual milk compartment, the volume of which (Vm, l) does not refer to actual existing volume as a separate compartment, but rather represents the postnatal day (PND)–dependent volume of milk produced per day. It was assumed that the pups consume all the milk produced without any delay between production and ingestion. The rate of milk production and suckling was assumed to be constant without any circadian variation. A simplified description of milk intake was used that did not describe separate suckling episodes throughout the day, but rather used a continuous input to the pups at a constant rate.
The rate constant for lactational transfer/secretion of chemical (KL) was derived from two predetermined factors, the Vm and the milk partition coefficient or ratio of the chemical concentration in milk to the dam's central compartment (Pm). Pm was employed in the model as an index of the extent of chemical transfer into milk relative to the levels of chemical in plasma (i.e., mother's central compartment). It was assumed that the chemical concentration in milk was in instant equilibration with maternal blood and consequently parallels her concentration. Pm was assumed to be constant during the whole lactational period. By definition,
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equal and rearranging terms obtains:
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Equation 11 and available for absorption to the pups in Equation 6.
Model Structure for Dosing
The model included exposure of the dam by three dosing approaches—gavage, unadjusted feeding (constant ppm in diet), or adjusted feeding (weekly changes in ppm in diet). All these were intended to provide the same target dose, 15 mg/kg/day either throughout the study (gavage, adjusted feeding) or at the appropriate baseline period (unadjusted feeding). After weaning, direct dosing to the pups by gavage or unadjusted feeding was included in the model for 1 week. The dosing to the pup was modeled for an individual pup, rather than for the combined litter of eight pups. In the case of dietary exposure, the pup started eating the same diet as the dam on PND17 as described later. After weaning, the pups were assumed to consume unadjusted diet.
Gavage.
Gavage dosing was modeled as a bolus dose scheduled once a day (coded in a DISCRETE block in acslXtreme) at the target dose of 15 mg/kg/day (ODOSE0). For gavage dosing, the daily dose to the dam or pups (Dosed or Dosep in Equations 3 and 6) was defined as:
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Dietary exposure.
To simulate feeding exposure, two factors that determine the amount and rate of chemical input via diet were incorporated in the model, the amount of food intake per day (FOOD, g/day) and the diurnal pattern of food consumption using the mean percentage of total food intake during 1-h intervals (FOODPC, %/h). Feeding exposure for each consecutive simulation day was modeled as a continuous addition of the chemical to the absorption site of the dam or pups at a specific rate (RFC, g/h) using the TABLE function in acslXtreme.
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Equation 13 gives the amount of food consumed (AFC, g). The amount of feed consumed per day (FOOD) was introduced using the DISCRETE block for the dam and when applicable, for the pups, to accommodate daily changes. The values for FOOD were determined by the equations in Table 2.
The chemical concentration in diet (FEED0, mg/g diet) to achieve the target dose (TARGET, 15 mg/kg/day) was derived using the mean food consumption (FID, g/kg/day) by the dam during gestation or during the first week of lactation as a reference point, depending on the simulation scenarios.
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) for which the intake by the dam and pups was not discriminated, as is typical in toxicity studies. Adjustment of chemical concentration in food was modeled on a weekly basis and only for lactation period, so AJ = 1 was used for the postweaning period returning the concentration in food to the initial concentration. Consequently, adjusted and unadjusted feed concentrations were the same after weaning (Table 2). Although the direct dosing of the pups through food during the first week after weaning was expressed as unadjusted feeding, some toxicity studies also adjust the diet during this period.
The rate of chemical dosing via feeding (RFD, mg/h) is:
 | (17) |
Equations 3 and 6 when dietary administration was simulated.
Recirculation of excreta.
Neonatal rats are known to be unable to eliminate wastes without maternal stimulation for several days after birth (Henning, 1981). Hence, it was expected that much of the chemical eliminated from the pups returned to the dam through this process. In order to simulate the recirculation of excreta between the dam and pups, the amount of chemical eliminated from the pups (AEP, g) was modeled as an additional chemical input to the dam without loss for the first 2 weeks of postnatal period (Fig. 1). AEP was added to the Dose in Equation 3 during those 2 weeks, where AEP was obtained by integrating the pup's elimination rate (REP = Kep x Ap).
Model Parameterization
The present model incorporated known changes in biological parameters during lactation and the early postweaning period. Modeled kinetic properties for the test compounds were benchmarked using data from real chemicals. The rationale for biological and chemical parameterization of the current model is detailed in the Supplementary section. Parameter values were obtained from literature when possible, but several assumptions were made due to limited data availability for these early life stages in rats. Efforts were made to obtain values within the same study and/or for the same species of rats whenever possible. Biological/pharmacokinetic parameters changing during lactation and early postweaning were modeled with either linear interpolations between reported time points of measurements using the TABLE function in acslXtreme or curve fitting to reported data points using nonlinear regression tools in Prism 4 (GraphPad Software, Inc., San Diego, CA). Equations from fitted curves are listed in Table 2. The values used in TABLE functions for BWd and Vm are reported in the Supplementary section. The equation for consumption of food and the equation for utilizing the TABLE value for daily milk volume were written in a DISCRETE block, so that they varied on a daily basis, but stayed constant during each of the 24 h. When converting data points from previously published figures in the literature into numbers in order to incorporate them in the model, DigitizeIt software was used (version 1.5, www.digitizeit.de).
Biological Parameters
The biological data incorporated in the present model are shown in Figures 2 and 3.
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Body weights.
Maternal body weight (BWd) changes during lactation and postweaning periods were incorporated into a TABLE function based on published values for Sprague-Dawley rats (Shirley, 1984
). The growth rate of the neonates was derived from pup body weight data for Sprague-Dawley rats (Doerflinger and Swithers, 2004) as shown in Figure 2 and Table 2.
Food consumption.
Food intake for the dam was adapted from the same study from which the body weight data were obtained (Shirley, 1984). Shirley reported the total observed intake as maternal intake, although food consumption by the pups in later part of lactation was observed. In order to calculate food intake solely by the dam, an estimated amount of food eaten by a whole litter (average size reported as 9.5 pups) was subtracted from the total reported intake. For this purpose, the amount of food consumed per day by an individual pup (g/pup/day) reported in another study with Sprague-Dawley rats (Redman and Sweney, 1976) was multiplied by 9.5. The onset of diet consumption by the pups was introduced as PND17 in the present model. The estimated mother-only intake values (g/dam/day) incorporated in the model are plotted in Figure 2 along with the observed total intake values during the last 5 days of lactation for comparison purposes. The pattern of feeding by the pups was modeled with intake starting on PND17 and rapidly increasing until PND21, followed by a continuous increase over the postweaning period (Redman and Sweney, 1976)(Fig. 2).
Dietary dose adjustment.
To simulate the adjusted diet dosing regimen by reducing the chemical concentration on a weekly basis, the feeding dose adjustment factor AJ described in Equations 15 and 16 was included in the model as shown in Table 2. Values for FID and Intakei were derived from gestational and lactational food intake data using Sprague-Dawley rats (Shirley, 1984).
Diurnal variation in feeding behavior.
The diurnal feeding behavior of the dam and its changing pattern during the lactation and postweaning periods were included in the model based on data for Wistar rats (Strubbe and Gorrisen, 1980). It was incorporated in the model as % total daily intake per hour (FOODPCd, %/h) as described earlier, for which four different patterns were defined for each week of lactation and postweaning using TABLE functions applied sequentially for the corresponding simulation week.
The diurnal fluctuation of feeding rates was also applied in modeling food intake by the pups. From PND17 to weaning, it was assumed that the pups follow the same feeding pattern as the dam during this period, i.e., circadian variations in feeding were not yet obvious (Doerflinger and Swithers, 2004; Redman and Sweney, 1976). The diet consumption pattern in Sprague-Dawley rat pups on PND25 was adapted to represent the feeding pattern during the postweaning periods in the current model (Redman and Sweney, 1976). As in the case of the dam, the feeding pattern was incorporated in the model as hourly rates of food intake (FOODPCp%, total daily intake/h) using a TABLE function.
Milk consumption.
In this model, the maternal milk yield equals the milk intake by the pups with no losses. Daily milk intake by the pups was incorporated in the model as a combination of experimentally measured values for early lactation and theoretical values based on the energy requirement for growing rat pups for the later part of lactation. Milk consumption was simplified using continuous suckling, rather than attempting to capture its episodic occurrence. Since pup intake of milk and food were not available from a single study, multiple sources were utilized to create estimates that were also evaluated to insure that the caloric intake was consistent with the growth of the pups.
In order to construct a milk intake curve for the early period of lactation, milk yield data determined from Wistar rats with a litter size of 10 were utilized (Knight et al., 1984). We adopted the values for PNDs2 and 6 determined by the tritiated water dilution technique for the TABLE function for milk intake during the first week of lactation. For the later part of lactation, theoretically derived milk intake values were incorporated in the model, based on the suggested caloric requirement of pups (Stolc et al., 1966), calories provided by independent feeding from PND17 and onwards (Redman and Sweney, 1976), and the observed ability of neonatal rats to respond to caloric deficit and consume either milk or diet at appropriate levels to match their energy needs (Henning, 1981). The milk intake in the second and third weeks of lactation was set to meet the suggested caloric requirement of 45 kcal/100 g body weight (Stolc et al., 1966), either provided solely by milk from PND7 to PND16 or provided both by milk and diet from PND17 onwards, i.e., milk volume suckled by the pups during these last 5 days was estimated to fulfill the energy requirement not already provided by the diet. The overall milk intake pattern in the current model consists of two experimental data points for PND2 and PND6 and 15 estimated values for PNDs7–21 that were utilized in the TABLE function. A smooth transition from the experimentally measured milk intake to the calculated values was possible because the milk intake values calculated using the two approaches were very similar for PND6 (Fig. 3). Since the Knight et al. (1984) data were for milk intake by 10 pups, daily milk intake per kilogram pup body weight was calculated using the reported body weight in the same paper, and then the daily milk yield for 8 pups was calculated using pup body weight simulated in the model (Doerflinger and Swithers, 2004). Caloric values of rat milk were derived from the milk composition data and the energy value of its components (Bornschein et al., 1977; Luckey et al., 1954). Physiological fuel energy value of 3.41 kcal/g for Certified Rodent Diet5002, which is often used in multigeneration toxicity studies (Hanley et al., 2002; Hinderliter et al., 2005), was utilized to calculate caloric value of rat chow (www.labdiet.com). Sometimes a different diet (e.g., Diet5008), which has higher calories (i.e., 3.50 kcal/g) than Diet5002, is used for lactating dams and the diet switched after weaning (Howdeshell et al., 2007; Rayner et al., 2007). However, these small differences in energy value of diets were not expected to make a substantial difference either in milk intake estimation or food intake by the pups during late lactation and postweaning period. For instance, only 2.5% less Vmilk value was estimated at most using Diet5008 in the simulation. The constructed curve for changing milk intake was incorporated in the model to simulate the daily milk intake for the eight pups (l/day, Vm). Circadian variation in milk intake was not modeled, i.e., constant suckling throughout a day was assumed as suggested from a few studies (Godbole et al., 1981; Redman and Sweney, 1976).
Chemical Properties of Theoretical Test Compounds
The present model was run for a series of hypothetical chemicals with different characteristics denoted as six categories (Table 1). A total of 16 different chemicals were simulated incorporating different chemical parameters and conditions in the model (Table 3). These chemical parameter values were either benchmarked from actual chemicals or derived from a few assumptions detailed here.
Oral bioavailability.
Oral bioavailability of the test chemical administered via gavage, feeding, and milk transfer was assumed to be 100% by setting the value of F (used in Equations 3 and 6) as 1.
Absorption.
The absorption of the chemical was simulated as a rapid process both in the dam and pups. The absorption constants for the dam and pups were assumed to be the same (Kad = Kap) and to be constant over the duration of simulation.
Distribution.
The volumes of the distribution for the dam (Vd, l) or pups (Vp, l) were calculated by multiplying the body weight–normalized volume of distribution scaler (Vd, l/kg) for the dam or pups with its body weight (kg). The same Vd values were used both for the dam and the individual pup (Vdd = Vdp) and kept constant during the whole simulation. Three values of Vd were used to simulate different distribution scenarios: limited distribution to tissues (Vd = 0.2), distribution to total body water (Vd = 0.7), and distribution to a storage depot (Vd = 2.5).
Extent of milk transfer.
A ratio of the concentration in dam's plasma to her milk (Pm) was used to describe the extent of chemical transfer to milk (Equation 7) since milk was assumed to be in instant equilibrium with the mother's concentration in her central compartment. The ratio was constant during the whole lactational period. Four Pm values were adopted in the present model: Pm = 0.1 (milk < plasma), Pm = 1 (milk = plasma), Pm = 3, and Pm = 10 (milk > plasma). Milk concentrations compared to the dam's plasma or blood for several environmental chemicals and pharmaceuticals in rats fall into the Pm ranges used, including perfluorooctanoate (ratio 
0.1), 2,4-dichlorophenoxyacetic acid (2,4-D, ratio 1), tetrachloroethylene (milk to blood partition coefficient 10), zidovudine (milk to serum ratio 1), and ranitidine (milk to serum ratio 10) (Alcorn and McNamara, 2002; Byczkowski et al., 1994; Hinderliter et al., 2005; McNamara et al., 1996; Sturtz et al., 2006). Biologically, milk concentration can reflect distribution dependent on physical chemical properties (e.g., partition coefficient) and also biochemical properties (e.g., active transport and protein binding). In the present model, Pm was varied with a fixed Vd, i.e., 0.7 l/kg, so high Pm cases would reflect chemicals actively transferred into milk rather than highly lipophilic chemicals for which a higher Vd would be expected as well as high Pm.
Elimination.
The elimination rate constants in the dam (Ked) and pup (Kep) were set to the same values and treated as constant, except when investigating the impact of developmental delays. The elimination rate constants were chosen to give half-lives (t1/2 = 0.693/Ke) of 1 and 24 h, representing rapid and slower elimination, respectively, in nonlactating rats. During lactation, the half-life in the dam can differ because the total elimination includes excretion via milk which can shorten the overall half-life. A half-life of 24 h was considered the longest reasonable to consider in the current model structure because it does not directly include gestational exposures, which would be expected to result in a substantial body burden carrying over into lactation.
Allometric scaling was not employed when incorporating the elimination constant in the model, so the half-life does not change with age. Hence, Ked and Kep were constant, independent of body weight or corresponding age over the period of simulation, except when modeling developmental delays in the pups (Table 2). Kep was expressed as proportion of Ked using R = Kep/Ked. When R = 1, the pups’ overall elimination capability was at adult levels at birth. Alternatively, a delayed pattern of elimination was modeled, with half maximum activity reached on PND7. This development pattern was based on critical changes in neonatal kidney morphology and function observed within the first postnatal week (Kavlock and Gray, 1982). However, it should be noted that it only represents one possible scenario of changes in elimination capacity during rat development, and this formula does not refer to any specific metabolic or renal process (see Supplementary section for other possible developmental patterns).
Defining base cases.
It was necessary to set a point of reference to which other simulation results could be compared. This was indicated as a "base case". The pharmacokinetic parameters for the base chemicals are shown in Table 3. Two base chemicals were defined, one for short half-life and the other for longer half-life compounds. For the base case simulations, elimination capacity in the pups was assumed to have already reached an adult level at birth (R = 1), milk concentrations were equal to maternal plasma concentrations, and distribution was to total body water. Recirculation of excreta between the dam and pups was not included in the base case simulation. To evaluate the impact of selected biological or chemical factors on the extent of neonatal exposure, these factors were varied one factor at a time using alternative values listed in Table 3, and the simulation results were compared to those from the base case. Each chemical property was varied with all other properties fixed to base case values in the current study to explore the range of model predictions. Alternatively, one can run the model with different sets of chemical parameters based on the properties of actual chemicals. This approach is required for the model evaluation by comparison with measured data for specific compounds.
Model Evaluation
The model performance was evaluated using previously published lactational transfer studies for 2,4-D and ochratoxin A (OTA) in rats. Model-predicted concentrations of these chemicals in the dam, pups, and milk were compared to published values. All the model assumptions and parameters described earlier were applied in the two benchmarking simulations (e.g., milk consumption and pup growth) except 2,4-D or OTA-specific pharmacokinetic parameters and the reported experimental conditions were applied instead of theoretical values and study designs. (Table 4)
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Simulation of OTA Exposure via Milk in Rats
Placental and lactational transfer of OTA in Sprague-Dawley rats were measured in a cross-fostering study (Hallen et al., 1998
). The model was used to simulate exposure of the dam to OTA during lactation and the first week after weaning; the predicted concentrations in the dam, pups, and milk were compared to the published values for PNDs14 and 21. We benchmarked the model to the data from one of the cross-fostering groups in which the pups were born from an unexposed dam and nursed by a foster mother exposed to the toxin throughout premating, gestation, and lactation. Therefore, it was necessary to consider the chemical in the dam resulting from the prelactational exposure. It was reported that OTA was given to the dam by gastric intubation at 50 µg/kg/day five times per week during five consecutive weeks including 2 weeks of premating and 3 weeks of gestation followed by 7 days/week for the 3 weeks of lactation (Hallen et al., 1998). Since the present model does not have either premating or gestational periods, the amount of OTA still in the dam resulting from the 5 weeks of exposure before birth was assumed to be equal to that from 5 weeks of repeated exposure for an adult female. Hence, the prelactational exposure was simply modeled as repeated oral gavage of OTA to the adult female following the dosing regimen described above. To simulate this repeated OTA exposure in the adult female, selected parameter values were changed, i.e., the milk yield was set to zero, and the body weight of the dam was held constant at early gestational weight, 0.25 kg (Shirley, 1984). OTA pharmacokinetic parameters were adapted from the two-compartment model structure of Li et al. (1997) using adult female Sprague-Dawley rats. The beta phase elimination constant and steady-state volume of distribution were adopted as Ke and Vd for the current one-compartment model. The rapid absorption constant, Ka = 2, was utilized for OTA simulation based on observation of efficient absorption of OTA from the gastrointestinal tract after oral administration in F344 rats (Zepnik et al., 2003). A developmental delay in elimination was also modeled (Table 4).
Simulation of 2,4-D Exposure via Milk in Rats
Sturtz et al. (2006) administered 2,4-D to Wistar rat dams with eight pups per litter during lactation using an adjusted feeding method. 2,4-D concentrations in the serum of the dam and pups and in the milk were determined on PND16. In this study, the 2,4-D concentration was adjusted by comparing the extent of food intake to the most recent intake for the two preceding days during lactation. Lacking details, we approximated this study design and modeled the diet concentration adjustment as a weekly event using the food intake in the first week of lactation. The model was evaluated for predicting the dosimetry for the lowest exposure dose only, i.e., 15 mg/kg/day, because elimination of 2,4-D in rats has been shown to saturate at higher exposure levels, e.g., 50 mg/kg and above (Gorzinski et al., 1987). The value for Pm was 1.1 according to the findings by Sturtz et al. (2006) at 15 mg/kg/day. As listed in Table 4, two different simulations were performed to compare the model with the experimental data. The first simulation (adult female Vd) used the 2,4-D pharmacokinetic parameters derived from the nonlactating adult female rats (Griffin et al., 1997; Timchalk, 2004). In the second simulation (smaller Vd), the volume of distribution (Vd) was shifted to a value, which was the lower end reported for 2,4-D (Timchalk, 2004), while keeping the elimination rate constant unchanged.
Dose Metric Calculation
Daily dose metrics simulated include the maximum concentration of the chemical (Cmax, mg/l), 24-h cumulative area under the curve (AUC, mg x h/l), and daily dose (mg/kg/day). The percentage of AUCp to AUCd was also reported as a dose metric of relative risk for the pups, as suggested in Corley et al. (2003). All the dose metrics were calculated for three selected PNDs—4, 16, and 28—representative for early lactation, (moderately) late lactation, and early postweaning.
The differences between the values on PNDi and PNDi–1 were referred to as the daily dose metrics on ith PND for the 24-h AUC, the relative risk, and Cmax. The daily dose for gavage dosing was a fixed value of 15 mg/kg/day. In the case of dietary exposure, the daily dose on PNDi is given by the Equation 18.
 | (18) |
Equation 19.
 | (19) |
Equation 18), which is applicable only for the last 5 days of lactation (i.e., PNDs17–21). |
RESULTS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONSUPPLEMENTARY DATAFUNDINGREFERENCES |
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Evaluation of Model Performance
The model performance was assessed using the published data for 2,4-D and OTA. Figure 4 compares model simulations with previously reported OTA data (Hallen et al., 1998
). The reported Cd and Cm values fell in the predicted concentration ranges either simulated with adult female pharmacokinetic parameters (Fig. 4A) or with delayed development of pup elimination incorporated (Fig. 4B). The Cp was reasonably predicted in both cases showing 13% underestimation and 20% overestimation compared to the measured value on PND14, respectively.
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Table 5 reports the simulated 2,4-D concentrations in the dam, pups, and milk on PND16 from two different simulations with varying Vd. The predicted 2,4-D levels in the dam, pups, and milk were consistently about one-third of reported values with the adult female Vd (Table 5). With a smaller Vd, higher values were achieved that were closer to the measured values (Table 5). Incorporating recirculation and delayed development of elimination in the model made little differences compared to the predicted 2,4-D levels with adult Vd (data not shown).
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These two limited tests indicate that the model can reasonably approximate pup exposures when data on milk transfer and kinetics in the nonlactating female are available.
Predicted Dose Metrics for Theoretical Chemicals
Exposure levels in the dam and pups were predicted and several internal or external dose metrics were calculated as indicated in "Methods" section. Since it was not practical to report all the predictions from the simulations, selected results are highlighted below. Complete listings of predicted dose metrics (Cmax, AUC, and daily exposure dose) as well as figures showing all the simulated concentration profiles over time are in the Supplementary section.
Base Case Comparison of Alternative Exposure Methods, Short Half-life
The concentrations in the dam and her pups predicted during the 4 weeks simulation and the resulting 24-h AUC values on selected PNDs for the short half-life base case compound are shown in Figure 5A. In the dam, gavage dosing resulted in higher peak concentrations compared to the two dietary exposures. For dietary exposures, the peak levels reflected the changing pattern of food intake during lactation and after weaning. When the dam was dosed via unadjusted feeding (i.e., constant ppm in diet), the peak levels were observed to increase during the first week of lactation as expected from a rapid increase in dam's food consumption in this period, while the peaks in the second and third week of lactation increased only slightly. This behavior differed from the expectation based on food intake by the dam which increased during these latter two weeks, although not as extensively as in the first week (Fig. 2). The similarity of the peak concentrations is attributable to the altered feeding pattern of the dam during lactation which results in less fluctuation in feeding rates during the day. Although the peak concentrations were approximately constant during the second and third weeks, internal exposure (AUCd) on PND16 was higher than on PND4 indicating that the dam's increased food intake indeed resulted in greater exposure (Fig. 5A). If the chemical concentration in diet was adjusted during lactation, peak values were lower than those from the unadjusted dosing regimen. As intended for the adjusted diet protocol, the internal exposure was maintained at approximately constant levels during lactation as implied by the similar predicted AUCd for PNDs4 and 16 (Fig. 5A). Since the adjustment was simulated only for the lactational period and thus the chemical concentration was the same for adjusted and unadjusted exposures, the concentration profiles and AUCd of the dam for postweaning period were identical for the two dietary dosing methods (Fig. 5A).
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The concentration in the pups (Cp) during lactation was substantially lower than in the mother (Cd) for all three dosing approaches (Fig. 5A). Gavage dosing was predicted to have the greatest difference, with the pup's peak concentrations about 50 fold lower than the mother's (see Supplementary tables). The time profile for the chemical concentration in the pups during lactation did not parallel the mother's. When the dam was gavaged, the pup concentration was predicted to continuously decrease as they grew, while the mother's concentration stayed constant. The rate of chemical input through milk appeared not to be fast enough to prevent chemical dilution by growth of the pup, i.e., increasing pup volume of distribution. In simulations of feeding exposure, the profiles of peak concentrations in mother and pup were very different from PND17 and onwards, which was attributable to the initiation of consumption of dosed-feed by the pups (Fig. 5A). During the 4th week of simulation, the pups and dam were either dosed directly by gavage or ate the unadjusted diet. The pups’ internal exposure during this postweaning period was the same as the mother's exposure when gavaged. Pups fed chemical via diet had higher peak concentrations and a larger AUC than their mother's (Fig. 5A), which was attributable to the higher food consumption per kg body weight of the pups compared to adults. Compared to lactational exposure, the postweaning exposure of pups was much higher for both gavage and feeding. The differences in pup peak concentrations between lactation and postweaning exposures were greater for gavage dosing, but in terms of AUC, the extent of the lactation versus postweaning differences were similar in gavage and feeding.
Base Case Comparison of Alternative Exposure Methods, Long Half-life
Figure 5B shows the predicted concentration profiles in the dam and pups for the long half-life compound. The daily peak concentrations were the highest with unadjusted feeding exposure, and the AUCd from this dosing method was also greater than gavage or adjusted feeding approaches in the dam. Similar to the short half-life case, the predicted AUCd levels indicated that the exposures to the dam via gavage and adjusted feeding were to be very similar. The slight increase in concentration in the gavaged dam after weaning was due to cessation of chemical excretion in milk. The concentration profiles in the pups roughly parallel the mother's for the three dosing methods though lower and showing smaller daily fluctuations (although this partially may be due to modeling continuous suckling, rather than episodic behavior). In the case of long half-life chemical exposure, the concentrations in the pups, Cp, approached the mother's levels, especially for the first week, but were still lower. Adjusted feeding and gavage produced very similar lactational exposure in the pups in terms of both peak concentrations and AUCp during the later part of lactation until the pups initiated their own feeding (Fig. 5B). The impact on Cp of the pups’ independent feeding on treated diet was not as great as that observed for the short half-life compound exposure. Postweaning exposure of the pups was the same as the dam for gavage, while higher than mother's for feeding exposure. When compared to the lactational exposure, the postweaning exposures were observed to be higher for both gavage and feeding, but the difference between the two periods was not as great as was the case for the short half-life compound in terms of peak concentration and the predicted AUCp (Figs. 5A and 5B). When comparing the lactation and postweaning exposures, the greatest difference was caused by adjusted feeding followed by gavage and then unadjusted feeding. It should be noted that the exposure to the dam determines the pup's exposure during lactation, while the pups’ own exposure determines their exposure level after weaning. It was also noticeable that dietary exposure produced higher peak concentrations in the postweaning pups compared to gavage, in the long half-life chemical exposure simulations, while it resulted in lower peak concentrations than gavage for the short half-life chemicals (Fig. 5B).
Changes in Volume of Distribution
Simulations were performed to determine the impact of changing chemical properties on the extent of pup exposure. By changing Vd and Pm, the exposures of the dam and pups varied to different extents from the base case predictions, but some of the patterns remained similar to those for the base cases (see Figures in Supplementary section). Only distinctive features resulting from these variations are described here. The AUC values were utilized to compare the pups’ exposure to the dam's and among different periods of postnatal life. The impact of varying chemical properties on the dose metrics other than AUC including the concentration profiles over time and Cmax can be found in the Supplementary section. The predicted AUCp and AUCd values were compared with the volume of distribution (Vd) varying from the base case scenarios. Results from gavage dosing are shown for a short half-life compound as an example and unadjusted feeding for long half-life compound (Fig. 6). The smaller the Vd, the higher the relative level of AUCp compared to AUCd. The impact of varying Vd on AUCp was observed both for lactation and postweaning period, in terms of absolute values. However, it should be noted that the relative levels of AUCp and AUCd during postweaning were the same regardless of Vd values, although the absolute values were different (Fig. 6). The impact of changing Vd on the relative AUCp to AUCd during lactation was more pronounced for the case of the long half-life compound. With the smallest Vd used in the model, AUCp values were greater than AUCd during lactation by more than twofold (Fig. 6B). Similar trends were observed for the other two dosing methods (data in Supplementary section). Comparing dosing methods, the relative level of AUCp to AUCd was greater in gavage dosing simulations, though to only a small extent, compared to the two dietary methods for all Vd cases. Unadjusted and adjusted feeding methods resulted in similar relative exposure levels for the pups compared to the mother for all Vd used.
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Changes in Milk Partitioning
Three Pm values in addition to the base case with milk concentrations equal to maternal concentrations (Pm = 1) were assessed—milk concentrations 10-fold lower (Pm = 0.1), threefold higher (Pm = 3), and 10-fold higher (Pm = 10) than mother's plasma concentrations. Predicted AUC values using gavage dosing for the short half-life compounds and adjusted feeding for the long half compounds are illustrated in Figure 7, while predictions for the other two dosing regimen are listed in the Supplementary section. The impact of varying Pm on the pup exposure was observed mostly during lactation as shown by increased (or decreased) AUCp values observed on PNDs4 and 16 with higher (or lower) Pm, while PND28 values were unaffected as this is 7 days after exposure to milk ceased. For short half-life compounds, increasing Pm resulted in less difference in internal exposures for dams (AUCd) and pups (AUCp) (Fig. 7A). The AUCd values decreased with increasing Pm, which also contributed to reducing the difference between mother and pups though the extent of this decrease was smaller than the corresponding increase in AUCp. Long half-life compounds exhibited pup exposures ranging from much lower than maternal to much greater than maternal with increasing Pm, which substantially contributed to the decline in the maternal exposure with increasing milk transfer (Fig. 7B). The other two dosing methods produced similar trends (see Supplementary section). When comparing dosing strategies, the relative level of AUCp to AUCd was greater in gavage dosing simulations, although to a small extent, compared to the two dietary methods, for all varied Pm cases. The relative level of AUCp to AUCd was almost the same for unadjusted feeding and adjusted feeding methods for each simulation case (see Supplementary section).
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Developmental Delay in Elimination
In order to compare the base case with a different pattern for postnatal development of elimination capacity, one possible scenario of a developmental delay was simulated (DevKe in Supplementary section). The delay was described with a Michaelis-Menten profile (i.e., a rectangular hyperbola) with half maximal capacity on PND7. Figure 8 shows the concentration profiles over time in pups with delayed development of elimination compared with those born with adult capacity (base case) for unadjusted feeding exposures. The delay in elimination capacity in the pups resulted in higher concentrations and AUCp compared to the base case. The greatest impact was predicted to occur during the first week with a two- to threefold increase in AUCp for the short half-life chemical (Fig. 8A) and a smaller increase for the long half-life chemical (Fig. 8B). The impact was reduced as the elimination capacity approached adult levels for both half-life cases. The impact on peak concentrations appeared to be more persistent. Other dosing approaches showed similar trends, in terms of the timing of the maximum effect on AUC, the profiles of the impact over time, and greater impacts in the short half-life case, though the extent of maximum effect varies according to the different dosing methods and half-life of a chemical.
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Role of Excreta Recirculation
Concentrations in the pups with or without recirculation were compared using predictions from adjusted feeding simulations in Figure 9. Excreta recirculation between the dam and pups had a small impact, with a maximum effect of a 10–30% increase in AUCp for the long half-life case only (Fig. 9B). Cp was higher than in the base case during the second week for the long half-life chemical simulation. The impact of recirculation on concentrations and thus AUCp for the short half-life chemical was negligible (Fig. 9A). Results for other exposure methods were similar (see Supplementary section).
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Predicted Pups’ Daily Dose
Daily doses to the pup (mg/kg/day) were calculated using the model and compared to the daily dose administered to the dam for three selected PNDs (Fig. 10). Daily doses to the pup (mg/kg/day) from six different cases were graphed and compared to the predicted dam's daily doses, with gavage providing the targeted 15 mg/kg/day. Overall, the amount of chemical delivered per kilogram body weight of pups per day was smaller than that of the dam during lactation for short half-life compounds for all simulation cases (Fig. 10A). Differences between the dam's and the pup's doses during lactation were smaller with a smaller Vd or a higher Pm for short half-life chemicals (Fig. 10A). For long half-life compounds, pups received comparable doses as the dam. The daily doses to the pups were predicted to be higher than the dam's on PND4 when Vd was smaller or Pm was greater than 1 during the first week of lactation, while in the later period of lactation these cases were predicted to have similar levels as the dam's (Fig. 10B). After weaning, gavage dosing was predicted to provide the same dose to the dam and pups, while feeding was predicted to result in a higher chemical dose to the pups (Figs. 10A and 10B).
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DISCUSSION |
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The purpose of this study was to answer the question, to how much chemical are pups exposed during lactation and early postweaning? Although pharmacokinetic information on lactational transfer and dosimetry in developing rat pups has been noted as a critical data need in extrapolating early life toxicity studies to humans, only limited information is available (Barton et al., 2006
). Pharmacokinetic studies involving early life stages are technically challenging and approaches are less standardized than for adults, even for pharmaceuticals. The current model demonstrated that it could provide insights into what dosimetry would be during lactation and early postweaning periods in dams and pups. These insights can be applied to pharmacokinetic and toxicity study design, interpretation of toxicity study results, and risk assessment applications. The present model for rats was based on known changes in biology and exposure characteristics during early postnatal periods together with chemical kinetics adapted from adults. Model evaluation against limited published lactational transfer data for OTA and 2,4-D indicated that reasonable predictions could be made using this information whether the chemical was given via diet (2,4-D) or by gavage (OTA). While two- or threefold discrepancies were observed by comparison with some data, this was considered acceptable for obtaining plausible initial estimates for a range of chemicals.
Model predictions were obtained to derive insights for a range of considerations important in one-generation toxicity settings, such as characterizing exposures during lactation, comparison of pup exposures to the mother's, comparison of exposures via milk to direct exposure after weaning, and evaluation of alternative dosing approaches. The present study clearly showed that exposure of the pups frequently does not parallel maternal exposure. However, it was possible to delineate several general features of the neonatal exposure pattern. The extent of lactational exposure of the pups to short half-life compounds was generally lower than that of the dam, while it was often comparable or even higher than maternal levels for longer half-life compounds. Factors such as a lower concentration in milk than in maternal blood and a volume of distribution larger than total body water tended to result in lower pup exposures compared to dam and consequently greater differences between maternal and neonatal exposures for both half-life compounds. Less difference was predicted between the maternal and neonatal exposures when the milk concentrations were greater than maternal blood levels, and the volume of distribution was smaller than total body water level. With these characteristics, the pup exposure level could exceed that of the dam for long half-life compounds. But, it also needs to be noted that even when the test compound's half-life is short, the pup exposure level could be comparable to the mother, if there are factors that tend to elevate exposure, e.g., smaller volume of distribution, delay in development of elimination, and recirculation. Pup exposures comparable to the mother's for a short half-life compound would be more likely with a dietary exposure regimen rather than gavage because gavage tended to result in more pronounced differences between maternal and neonatal exposure. Recirculation of excreta between the dam and the pups can contribute to pup exposure for longer half-life compounds when elimination is largely renal clearance, rather than by metabolism, by raising maternal exposure. Recirculation would be a particularly important factor to consider in cross-fostering studies where the pups would expose the "nonexposed" foster mother.
Predictions from the present model can be used as initial estimates for better designing and interpreting toxicity studies. Current findings suggest that there are some cases for which one should think about alternative exposure methods other than milk to achieve exposure to the pups. Particular attention would be needed when the pup exposure was predicted to be extremely low, e.g., less than 1% of maternal exposure, which was observed when the milk concentration was much less than the mother's blood concentration or when the volume of distribution was large for a short half-life compound. In these cases, one would need to be careful determining the windows of susceptibility or interpreting the potency of the chemical. If pup exposure was estimated from maternal levels for such a chemical, then the period of lactation could be interpreted incorrectly as not being a susceptible period when instead there was simply a lack of adequate exposure in the pups and the lactational period had effectively not been evaluated. If this were the case, an alternative study design such as direct dosing of the pups would need to be considered (Moser et al., 2005). Conversely, if the chemical exhibited toxicity with this very low level of milk transfer, then it can be suspected as a very potent compound. Model predictions also could help in amending the study design by providing information as to whether toxicities seen at certain doses may be related to excessively high pup exposure. During lactation, a notable example of this case is high milk transfer of a chemical with a long half-life.
The model predictions could be informative about whether abrupt changes in exposure levels after weaning, due to the initiation of direct dosing of pups, result in toxicity. For example, predictions from the current modeling showed that postweaning exposure was much higher than lactational exposure when gavaging short half-life chemicals. This abrupt increase in concentration in the pup could produce premature death or other toxicities in the neonates right after weaning, which could be misinterpreted as a critical window for the test chemical. Long half-life chemicals tended to show a greater similarity between lactational and postweaning exposures, though not in every case (e.g., low Pm). In the postweaning period, the pup exposure is predicted to be even higher than adult exposure under dietary exposure conditions due to the higher feeding rate of pups on a body weight basis compared to adults, while the same when gavage dosing is used. Collectively, initial estimates of pup exposure from the current model could provide valuable information to understand a chemical's effect based upon limited information on adult pharmacokinetics and milk transfer to facilitate design of follow-up pharmacokinetic or toxicity studies.
Although different dosing methods can lead to very different pharmacokinetic outcomes (Saghir et al., 2006), there have been few direct studies of the potential differences when the dam is given a chemical via gavage versus dietary administration. Arnold et al. (2000) reported that similar doses of hexaclorobenzene or Aroclor 1254 administered by two different dosing methods, gavage or feeding, did not result in similar exposures in suckling neonates. The marked increase in maternal food consumption during lactation was suggested to account for the difference, which was also supported by the current model predictions. The administration of chemicals at different dose rates, as exemplified by gavage versus dietary administration, could result in differences in the developmental outcomes, particularly those dependent upon peak concentration.
The amount and pattern of lactational exposure from adjusted dietary dosing for longer half-life compounds were predicted to be more similar to gavage than unadjusted diet as shown by similar internal exposure levels and peak concentrations before the onset of pup's independent feeding on solid diet. Unadjusted feeding generally produced higher pup exposure than these two approaches. These predictions will help not only to choose an appropriate dosing approach to achieve a pup exposure level similar to its mother's but also to provide insight into what to expect when different dosing methods are applied. Dietary exposure is often considered to be the most relevant dosing approach for life-stage testing, unless there is a technical problem, so we sought to determine for what chemicals this dosing method would be most relevant. When the chemical is rather slowly eliminated and the milk transfer is moderate (i.e., the Pm being between 1 and 3) and/or the volume of distribution is slightly smaller than the total body water, then one can expect that the dam and pups would be exposed at similar levels via feeding. Again, it should be taken into consideration that the unadjusted diet exposure in a number of cases for long half-life compounds will lead to higher exposures than expected from the predetermined target dose due to the increased maternal food intake during lactation.
Current modeling highlighted some critical data needs in predicting postnatal dosimetry; time-dependent changes in milk partitioning are one example. The milk concentration was assumed to parallel maternal plasma levels by a constant proportionality, the milk to plasma ratio, throughout lactation. Known changes in milk during lactation may call into question this assumption for at least some classes of chemical (Luckey et al., 1954). This would matter especially for chemicals whose partition to milk is highly affected by milk composition. Such chemicals include highly fat-soluble compounds due to significantly higher fat content in milk the first few days after birth and its rapid decline thereafter. Ingestion of highly lipophilic compounds such as hexachlorobenzene and polychlorinated biphenyls by suckling pups was observed to be elevated shortly after birth correlated with high milk fat content (Arnold et al., 2000). Secretion of chemicals that bind to milk proteins may also be affected by such time-dependent changes in milk composition. Thus, more accurate estimation of milk to blood ratios for test compounds would be obtained by measuring them experimentally throughout lactation. It also would be important to determine milk composition throughout lactation because currently available information is very limited. With additional data, methods could be developed to predict passive distribution of chemicals based upon milk composition and the physical chemical properties of the chemical.
While the current model has value as a tool to make initial predictions, it is also plausible that adult pharmacokinetics during lactation would differ from those in nonlactating adults or that there were major age-dependent changes in the pups that could impact a specific chemical. There are changes in fluid handling during lactation in the dam, so distribution characteristics or renal clearance of a chemical could be affected although rats do not show decreased circulating albumin levels until the final days of pregnancy, in contrast to humans (Stock et al., 1980). Developmental pharmacokinetic changes in pups can be extensive during the first weeks of life as exemplified by changes in enzymes and transporters (Li et al., 2002; Yoon et al., 2006). The developmental pattern of elimination capacity was one possible example of developmental delay in elimination capacity based on critical changes during neonatal kidney maturation (Kavlock and Gray, 1982). If one knew important pharmacokinetic determinants in the adult, e.g., metabolism by a specific enzyme, binding to a specific protein, or movement via a transporter, this could potentially be incorporated into the current model (See Supplementary section for examples). As the complexity and detail increase, it would be necessary to shift to using a physiologically based pharmacokinetic model in place of the one-compartment model used here. Collecting data to evaluate the model predictions for any specific compound would be essential.
It will be necessary to modify the model to expand its general uses as well. Examples would include accounting for metabolism or transport and related saturation kinetics as well as lactational transfer of metabolites, modeling very long half-life compounds, and modeling premating and pregnancy periods. The activity of saturable active transport systems can be important for the pharmacokinetics of pharmaceutical and environmental chemicals, including for distribution to milk. For example, high lipophilicity is not the only factor that can lead to high milk concentrations. The milk concentration of the lipophilic carboxylic acid herbicide 2,4-D was shown to be similar to maternal blood (Sturtz et al., 2006), while less lipophilic (or more water soluble) compounds like antiviral drugs have shown several fold higher milk concentrations compared to mother's blood due to active transport in rats (Alcorn and McNamara, 2002). Early life toxicity testing usually involves the dam's exposure to the test chemical prior to impregnation and continued exposure during gestation and lactation. As a result, the neonate (and the fetus) is exposed to the test chemical and its metabolites prenatally and during lactation. Hence, simulation of the gestational carry over would be critical in predicting lactational exposure accurately for very long half-life compounds.
We have demonstrated a modeling approach to predict maternal and pup external and internal exposures by combining biological information in the literature on body weight changes, milk production, and food consumption with adult nonpregnant rat pharmacokinetics and information on milk distribution. The resulting predictions can be used to (1) design pharmacokinetic studies to evaluate the predictions, (2) evaluate early life toxicity study design choices (e.g., exposure method), and (3) develop hypotheses to interpret toxicity study findings. Extending this approach by incorporating more pharmacokinetic determinants in the model for distribution to milk and early postnatal pharmacokinetics would improve predictions for specific chemicals as well as facilitate development of further generalizations concerning the extent of pup exposures for chemicals with different pharmacokinetic characteristics. The current modeling analyses predicted substantial differences between maternal and pup external and internal exposures indicating that risk assessment approaches based upon maternal exposure doses are of limited utility when considering early childhood exposures.
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SUPPLEMENTARY DATA |
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Supplementary section are available online at http://toxsci.oxfordjournals.org/.
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FUNDING |
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National Research Council Research Associateship Award at the US Environmental Protection Agency to M.Y. (EPA-NRC # CR82879001).
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NOTES |
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1 Present address: The Hamner Institutes of Health Sciences, 6 Davis Drive, Research Triangle Park, NC 27709.
Disclaimer: This work was reviewed by EPA and approved for publication, but does not necessarily reflect official Agency policy. Mention of trade names or commercial products does not constitute endorsement or recommendation by EPA for use.
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ACKNOWLEDGMENTS |
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The authors acknowledge Dr. Suzanne Fenton for her review and comments.
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