The Toxicologist - Society of Toxicology

897 DEVELOPMENT AND DEMONSTRATION OF A
COMPUTATIONAL FRAMEWORK FOR FORWARD AND
REVERSE DOSIMETRY OF ORGANOPHOSPHORUS
INSECTICIDE MIXTURES.
J. H. Ivy 1, 2 , J. M. Wright 1 , A. N. Mayeno 1, 3 , M. A. Lyons 1, 2 and B. Reisfeld1, 2,
3
. 1 Quantitative & Computational Toxicology Research Group, Colorado State
University, Fort Collins, Co., 2 Department of Chemical and Biological Engineering,
Colorado State University, Fort Collins, CO and 3 Department of Environmental and
Radiological Health Sciences, Colorado State University, Fort Collins, CO.
Although various biomarkers have been used to assess exposure to and poisoning
from organophosphorus (OP) insecticides, the complexity of OP absorption distribution,
metabolism, and elimination warrants integration of computer-assisted
modeling tools with the biomarker data for more accurate quantitation and assessment
of target tissue dosimetry. Here we describe the development and current capabilities
of a novel computational framework for dosimetry of OP insecticide mixtures,
DoseSim:OP. This framework has features for both forward dosimetry, in
which a calibrated model is used to predict biomarker data from known exposures,
and reverse dosimetry, in which a calibrated model is used to reconstruct dose and
exposure from collected biomarker data. To this end, DoseSim:OP implements a
graphical user interface to tools for Monte Carlo and Bayesian analyses, statistical
post-processing and visualization of results. As a first step toward a general OP mixture
dosimetry model, we have implemented a physiologically-based pharmacokinetic
(PBPK) model for a mixture of chlorpyrifos [O,O-diethyl-O-(3,5,6-trichloro-
2-pyridyl)-phosphorothioate] and diazinon [O,O-diethyl-O-(2-isopropyl-6-
methyl-4-pyrimidinyl)-phosphorothioate], including both specific and non-specific
metabolites. Using this model in DoseSim:OP, we found good agreement between
reconstructed and experimental dosing scenarios using in vivo biomarker
data for rodents as input. Future developments of DoseSim:OP will include additional
validation from targeted in vivo studies, validation using human exposure
data, and dose reconstruction using biomarker levels from human epidemiological
databases. This project was supported by EPA STAR Grant #R833451.
898 A SYSTEMS MODEL OF BILE SALT METABOLISM AND
ITS APPLICATIONS TO CHOLESTASIS.
M. K. Narasimha, R. Nalini and K. Subramanian. Strand Life Sciences,
Bangalore, India.
Predicting the cholestatic potential of drugs is difficult since most drugs affect multiple
cellular mechanisms making the combined impact difficult to forecast.
Genetic polymorphisms only add to the complexity of making individual level predictions.
The multi-factorial origin of cholestasis, each factor not necessarily capable
of causing cholestasis by itself, raises the difficult question of what combination
of factors does cause cholestasis, and to what extent. The ability to answer such
questions provides insight into who develops what complications on exposure to a
particular drug or drug-combination thus helping in individualized therapy. To address
this issue, we have developed a dynamic systems model of bile formation and
metabolism that simulates such complex scenarios and provide insights into
cholestatic disease at an individual level. To illustrate the principle, we input the
role of estrogens into the model. We considered the alteration of multiple cellular
mechanisms such as Na+ dependent cellular uptake at the basolateral membrane,
ATP -dependent transport at the canalicular membrane and the membrane fluidity
often observed in higher doses of ethinyl estradiol. We overlaid pharmacokinetics to
this picture. For example, we applied the trans-inhibitory effect of estradiol-17
beta-glucuronide, a metabolite of estrogen on BSEP, after its excretion by MRP2
into the canalicular lumen. To account for individual variations in response, we
studied the effect of mutations at highly conserved loci such as D676Y and G855R
in BSEP that are associated with drug induced liver injury and V444A implicated
for predisposition to estrogen mediated-cholestasis. The model predictions of the
advent and the extent of cholestatic disease were well in concordance with experimental
observations. In addition the model clarified the role of each of the above
mentioned mechanisms in disease. We thus illustrated the application of a dynamical
systems approach which allows the study of complex biological factors responsible
for cholestasis and allows one to understand mechanisms and treatments.
899 A PHYSIOLOGICALLY BASED PHARMACOKINETIC
MODLE FOR PRALIDOXIME IN THE GUINEA PIG
AND HUMAN.
K. O. Yu, C. D. Ruark, E. C. Hack, T. R. Sterner, T. R. Covington and J. M.
Gearhart. Applied Biotechnology, U.S. Air Force, Wright-Patterson AFB, OH.
Chemical warfare agents such as organophophorus compounds inhibit hydrolysis
of acetylcholinesterase (AChE) at the synaptic junctions by phosphorylation of
ester group. This will result in accumulation of acetylcholine in the synapses, causing
seizures to muscle paralysis, and even death due to respiratory failure. To prevent
overstimulation of acetylcholine at the synapses, AChE breaks down acetylcholine
into inactive forms. Pralidoxime (2-PAM) reactivates AChE by removing
the phosphoryl group bound to the ester moiety of the enzyme. The objective of
this study was to provide quantitative dose-response relationships of Pralidoxime
(2-PAM) across multiple species and multiple routes of chemical warfare nerve
agent (CWNA) exposures using a physiologically based pharmacokinetic model.
The model developed in this study accurately simulated blood concentrations of 2-
PAM in the guinea pig and human. Quantitative structure-activity relationship
(QSAR) algorithms were used to develop PBPK model parameters for 2-PAM,
based on the basic physicochemical properties and the octanol-water partition coefficient
data collected. Predicted tissue/blood partition coefficients of 2-PAM in
guinea pig and human were used as preliminary values to simulate the model. Data
from the literature were used to predict blood time course in the guinea pig after intramuscular
injection of 2-PAM (3.5 and 25 mg/kg). The model predictions of
blood kinetic data were in good agreement with experimental values. Human blood
kinetic data was also simulated with this model using human physiological parameters.
There was a good agreement between a model simulation and experimental
data after injection of 5 mg/kg 2-PAM intravenously. Oral uptakes in human will
be included in this investigation. A PBPK model developed in this study adequately
predicted blood kinetics of 2-PAM in guinea pig and human. This study was supported
by the Defense Threat Reduction Agency.
900 ADAPTIVE RESPONSES TO PROCHLORAZ EXPOSURE
IN THE HYPOTHALAMIC-PITUITARY-GONADAL AXIS
OF FATHEAD MINNOWS.
M. Breen 2, 1 , D. L. Villeneuve 3 , G. T. Ankley 3 , K. H. Watanabe 4 , M. S. Breen 5 ,
A. L. Lloyd 2 and R. Conolly 1 . 1 NHEERL, U.S. EPA, Research Triangle Park, NC,
2
Biomathematics Program, Department of Statistics, North Carolina State University,
Raleigh, NC, 3 Mid-Continent Ecology Division, U.S. EPA, Duluth, MN, 4 Division
of Environmental and Biomolecular Systems, Oregon Health & Science University,
Beaverton, OR and 5 National Exposure Research Laboratory, U.S. EPA, Research
Triangle Park, NC.
Exposure to endocrine disrupting chemicals can affect reproduction and development
in both humans and wildlife. We are developing a mechanistic mathematical
model of the hypothalamic-pituitary-gonadal (HPG) axis in female fathead minnows
to predict dose-response and time-course (DRTC) behaviors for endocrine effects
of the fungicide prochloraz. The model includes several feedback regulatory
loops within the HPG axis that mediate adaptive responses to endocrine stress.
Fathead minnows were exposed to prochloraz at 30 or 300 μg/L for 8 days followed
by an 8-day recovery phase. Adaptive changes in plasma estradiol levels occurred
during exposure and treatment-related oscillations occurred post-exposure.
Computer simulations were performed to compare the model-predicted DRTC
with experimental data and to gain insight into how the feedback control mechanisms
embedded in the HPG axis mediate these changes. As this work progresses
we will obtain a refined understanding of how adaptive responses within the HPG
axis of fathead minnows affect DRTC behaviors for prochloraz. This work was reviewed
by the U.S. EPA and approved for publication but does not necessarily reflect
Agency policy. M. Breen was supported by the NCSU/EPA Cooperative Training
Program in Environmental Sciences Research, Training Agreement CT833235-01-
0 with North Carolina State University.
901 DEVELOPMENT OF A PHYSIOLOGICALLY BASED
PHARMACOKINETIC MODEL FOR TRIADIMEFON
AND TRIADIMENOL IN RATS AND HUMANS.
S. R. Crowell 1 , W. M. Henderson 2 , J. F. Kenneke 2 and J. W. Fisher 1 .
1
Environmental Health Science, University of Georgia, Athens, GA and 2 National
Exposure Research Laboratory, U.S. Environmental Protection Agency, Athens, GA.
A physiologically based pharmacokinetic (PBPK) model was developed for the
conazole fungicide triadimefon and its primary metabolite, triadimenol. Rat tissue:blood
partition coefficients and metabolic constants were measured in vitro for
both compounds. Kinetic time course data for parent and metabolite were collected
from several tissues after intravenous administration of triadimefon to male
Sprague Dawley rats. The model adequately simulated peak blood and tissue concentrations
but failed to predict the observed slow terminal clearance of both triadimefon
and triadimenol from blood and tissues. Low capacity protein binding of
parent and metabolite in blood and tissues was speculated as a possible explanation
of clearance patterns, and model predictions were significantly improved by the addition
of optimized binding parameters. Human models with and without blood
and tissue binding were constructed for triadimefon and triadimenol using human
derived in vitro metabolic constants. Human equivalent doses (HEDs) were calculated
for both models for a rat NOAEL dose of 11.57 μmol triadimefon/kg/day
192 SOT 2010 ANNUAL MEETING