The Toxicologist - Society of Toxicology
The Toxicologist - Society of Toxicology
The Toxicologist - Society of Toxicology
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1930 DEVELOPMENT OF A RELATIVE SOURCE<br />
CONTRIBUTION FACTOR FOR DRINKING WATER<br />
CRITERIA: THE CASE OF HEXAHYDRO-1, 3, 5-<br />
TRINITRO-1, 3, 5-TRIAZINE (RDX).<br />
B. Gadagbui 1 , J. Patterson 1 , S. S. Kueberuwa 3 , A. Rak 2 , R. S. Kutzman 2 , G.<br />
Reddy 4 and M. S. Johnson 4 . 1 <strong>Toxicology</strong> Excellence For Risk Assessment, Cincinnati,<br />
OH, 2 Noblis Inc., Alexandria, VA, 3 U.S. Environmental Protection Agency,<br />
Washington, DC and 4 U.S. Army Center for Health Promotion and Preventive<br />
Medicine, Aberdeen Proving Ground, MD.<br />
In protecting human health, the application <strong>of</strong> fate, transport, and exposure data<br />
are essential in the development <strong>of</strong> chemical-specific criteria for drinking water.<br />
<strong>The</strong>re are few environmental regulations, standards, or guidance values for hexahydro-1,3,5-trinitro-1,3,5-triazine<br />
(RDX), but an increasing number <strong>of</strong> states are developing<br />
such for RDX. RDX is a synthetic chemical, which is not known to occur<br />
naturally. It is a military munitions explosive with limited civilian uses. Available<br />
data suggest that RDX is not anticipated to be a national exposure concern. This assessment<br />
presents a relative source contribution (RSC) factor for RDX. An RSC accounts<br />
for all sources and non-occupational exposures from RDX and apportions<br />
these amounts to each source so that an individual’s total dose does not exceed the<br />
reference dose. <strong>The</strong> application <strong>of</strong> the Exposure Decision Tree approach (subtraction<br />
method), recommended by the U.S. EPA, was used. An exposure model identified<br />
the relevant potential sources for highly exposed receptors proximate to an<br />
area where RDX was released. Potentially contaminated media include soil,<br />
groundwater, and surface water. Potential exposure pathways include ingestion <strong>of</strong><br />
soil, water, and contaminated local crops and fish; dermal contact with soil; and<br />
water used in bathing. <strong>The</strong>se pathways are limited to areas that are in close proximity<br />
to current or former military bases where RDX may have been released into the<br />
environment. Given the physical/chemical properties and the available environmental<br />
occurrence data on RDX (from military sites), there are adequate data to<br />
support a chemical-specific RSC for RDX <strong>of</strong> 50% for drinking water. <strong>The</strong> opinions<br />
are those <strong>of</strong> authors and do not necessarily reflect the opinions <strong>of</strong> the U.S. EPA or<br />
the Dept. <strong>of</strong> the Army.<br />
1931 ISSUES IN USING HUMAN VARIABILITY<br />
DISTRIBUTIONS TO ESTIMATE LOW-DOSE RISK.<br />
W. A. Chiu 1 , K. S. Crump 2 and R. Subramaniam 1 . 1 U.S. Environmental<br />
Protection Agency, Washington, DC and 2 Louisiana Tech University, Ruston, LA.<br />
Sponsor: K. Guyton.<br />
Background: A Committee <strong>of</strong> the National Academies <strong>of</strong> Science recommended<br />
using human variability distributions (HVDs) to estimate low-dose risks in certain<br />
situations. In this approach (HVD modeling) log-normal distributions are estimated<br />
from data on pharmacokinetic and pharmacodynamic variables that impact<br />
individual sensitivities to the toxic response. <strong>The</strong>se distributions are combined into<br />
an overall log-normal distribution by assuming the variables act independently and<br />
multiplicatively. This distribution is centered at a point <strong>of</strong> departure (POD) dose<br />
usually estimated from animal data. <strong>The</strong> resulting log-normal distribution is used<br />
to quantify low-dose risk. Objective: To examine the implications <strong>of</strong> various assumptions<br />
in HVD modeling. Methods: Assumptions and data used in HVD<br />
modeling are subjected to rigorous analysis. Results: <strong>The</strong> assumption that the variables<br />
affecting human sensitivity vary log-normally is not scientifically defensible.<br />
Other distributions that are equally consistent with the data provide very different<br />
estimates <strong>of</strong> low-dose risk. HVD modeling <strong>of</strong>ten involves assuming that the threshold<br />
dose, defined by dichotomizing a continuous apical response, has a log-normal<br />
distribution. This assumption is incompatible (except under highly specialized conditions)<br />
with assuming that the apical response itself is log-normal. However, the<br />
two assumptions can lead to very different estimates <strong>of</strong> low-dose risk. <strong>The</strong> assumption<br />
in HVD modeling that risk can be expressed as a function <strong>of</strong> a product <strong>of</strong> independent<br />
variables lacks phenomenological support. An example is provided that<br />
shows that this assumption is generally invalid. Conclusion: In view <strong>of</strong> these problems,<br />
we recommend caution in the use <strong>of</strong> HVD modeling as a general approach to<br />
estimating low-dose risks from human exposures to toxic chemicals. Disclaimer:<br />
<strong>The</strong> views expressed in this poster represent those <strong>of</strong> the authors and do not reflect<br />
the views or policies <strong>of</strong> the U.S. EPA.<br />
1932 PROPOSED MODES OF ACTION FOR<br />
NEUROTOXICITY INDUCED BY VARIOUS<br />
CHLORINATED SOLVENTS.<br />
A. Bale, S. Barone, C. S. Scott and G. S. Cooper. NCEA/ORD, U.S. EPA,<br />
Washington, DC.<br />
Several health assessments <strong>of</strong> chlorinated solvents, including trichloroethylene<br />
(TCE), perchloroethylene (PERC), and dichloromethane (DCM), are underway by<br />
the U.S. EPA’s Integrated Risk Information System (IRIS) Program. <strong>The</strong>se solvents<br />
have been shown to produce similar central nervous system (CNS) effects in animals<br />
and humans. <strong>The</strong> observed neurotoxicological effects for this chemical class<br />
are general CNS effects (e.g., locomotor activity changes and anxiolytic effects), visual<br />
effects, ototoxicity, cognitive deficits, sleep cycle disturbances, imbalance, and<br />
decrements in nerve function. Since neurotoxicological effects are consistent among<br />
the three solvents, we hypothesized that mechanisms producing these neurological<br />
effects may be similar. Available neuropathological and mechanistic studies were<br />
evaluated in order to determine which molecular systems may be involved in production<br />
<strong>of</strong> neurotoxicological outcomes. <strong>The</strong> mechanistic studies indicate that the<br />
chlorinated solvents have several molecular targets which may, in part, explain the<br />
observed neurobehavioral effects. PERC and TCE have been demonstrated to interact<br />
directly with several different classes <strong>of</strong> neuronal receptors by inhibiting excitatory<br />
receptors/channels and potentiating inhibitory receptors/channel function.<br />
Most <strong>of</strong> the mechanistic studies evaluated effects following acute exposure durations.<br />
Given the mechanistic information for TCE, DCM, and PERC, we provide<br />
hypotheses for primary targets (e.g. ion channel targets) that appear to be influential<br />
in producing the resultant neurological effect. As a result there is uncertainty in<br />
extrapolating the acute exposure mechanistic data to chronic neurotoxicological effects<br />
following exposures to chlorinated solvents since the molecular targets may be<br />
affected differently following a chronic exposure. This analysis <strong>of</strong> data from multiple<br />
chlorinated solvents underscores the need for more research to develop a model<br />
<strong>of</strong> low level chronic human exposures to this class <strong>of</strong> compounds. <strong>The</strong>se authors’<br />
views do not necessarily reflect the views or policies <strong>of</strong> the U.S. EPA.<br />
1933 MODELS USED TO SUPPORT EXPOSURE AND RISK<br />
ANALYSES BY THE U.S. ENVIRONMENTAL<br />
PROTECTION AGENCY.<br />
P. R. Williams 1 , B. J. Hubbell 2 , E. Weber 3 , C. Fehrenbacher 4 , D. Hrdy 5 and V.<br />
Zartarian 6 . 1 E Risk Sciences, LLP, Boulder, Co., 2 Office <strong>of</strong> Air Quality Planning and<br />
Standards, U.S. EPA, Research Triangle Park, NC, 3 National Exposure Research<br />
Laboratory, U.S. EPA, Athens, GA, 4 Office <strong>of</strong> Pollution Prevention and Toxics, U.S.<br />
EPA, Washington, DC, 5 Office <strong>of</strong> Pesticide Programs, U.S. EPA, Washington, DC<br />
and 6 National Exposure Research Laboratory, U.S. EPA, Research Triangle Park, NC.<br />
In this presentation, we provide an overview <strong>of</strong> 35 models currently supported and<br />
used by the U.S. EPA to assess exposures to human or ecological receptors. An understanding<br />
<strong>of</strong> these models is important because they are <strong>of</strong>ten used in addition to<br />
or in lieu <strong>of</strong> monitoring data to estimate environmental concentrations and exposures<br />
for use in risk assessments or epidemiology studies and to support regulatory<br />
standards and voluntary programs. Information on each models was obtained from<br />
several sources, including available model documentation (e.g., user manuals, staff<br />
papers, external peer reviews), interviews with model developers, and running <strong>of</strong><br />
the model using real or hypothetical data. <strong>The</strong> models generally represent the first<br />
half <strong>of</strong> the source-to-outcome continuum and include 12 fate/transport models, 5<br />
exposure models, and 8 integrated fate/transport and exposure models. Many <strong>of</strong> the<br />
exposure models also incorporate cancer or non-cancer risk estimates, including<br />
margin <strong>of</strong> exposure (MOE), hazard index, or toxicity equivalency factors. Each<br />
model is summarized with respect to its intended purpose and potential applications,<br />
level <strong>of</strong> analysis and routes <strong>of</strong> exposure, key data inputs and exposure/risk<br />
outputs, temporal and spatial resolution, treatment <strong>of</strong> variability and uncertainty,<br />
degree <strong>of</strong> model evaluation, level <strong>of</strong> internal and external peer review, and interactions<br />
with other models. A discussion is also provided regarding recent and ongoing<br />
efforts to develop integrated modeling approaches and to perform lifecycle evaluations<br />
and retrospective analyses <strong>of</strong> existing U.S. EPA models. <strong>The</strong> information presented<br />
here should provide a useful up-to-date resource to exposure and risk modelers<br />
and practitioners.<br />
1934 RISK ASSESSMENT OF METALS IN CONSUMER<br />
PRODUCTS INTENDED FOR CHILDREN.<br />
M. Wade, E. Sciullo, K. Day, R. Sarala, D. Chand, M. DeGuzman, J. Garcha,<br />
F. Hussain, M. Snider and T. Behrsing. Toxic Substances Control, Cal EPA,<br />
Sacramento, CA.<br />
Recently concerns have been raised about toxic chemicals, especially metals, found<br />
in consumer products (CPs). An example is lead (Pb) in children’s toys and jewelry.<br />
We encountered numerous challenges and uncertainties in attempting to perform<br />
risk assessments on CPs containing toxic metals. Risk assessment protocols, and<br />
toxicity and toxicokinetic (TK) data developed for evaluating chronic exposure are<br />
<strong>of</strong>ten inadequate for assessing short-term exposure to CPs; and, risk assessments for<br />
some CPs were developed years ago. We developed a general framework for CP risk<br />
assessment by evaluating risk and identifying uncertainties on a product-specific<br />
basis. Potential hazards from multi-component CPs designed for children and advertised<br />
as lead-free were evaluated by testing metal content, and extractability in<br />
saline and dilute acid solutions mimicking mouthing and swallowing, respectively.<br />
SOT 2010 ANNUAL MEETING 411