Page 175 - Veterinary Toxicology, Basic and Clinical Principles, 3rd Edition

142 SECTION | I General

VetBooks.ir composition, and physiological processes that influence could then be used as an hypothesis, and tested using skin
with varying layers of cells in the stratum corneum in
the concentration/time course of xenobiotic chemicals.
flow-through cell experiments.
Toxicologists are often faced with situations where the
adverse health risk from chemical exposure must be esti-
mated without access to data obtained under the condi-
tions of the exposure being analyzed. An advantage of CONCLUDING REMARKS AND FUTURE
well-designed, appropriately detailed, and adequately DIRECTIONS
understood PBPK models is that different exposure sce-
PBPK modeling is an evolving frontier in toxicokinetic
narios can be simulated using the same base model by
modeling. As our understanding of the systems and pro-
varying the mathematical descriptions of the dosing regi-
cesses involved in toxicokinetics improve and expand, so
men. These may include single, repeated, or continuous
does our ability to use newly gained knowledge in mod-
oral ingestion, single or repeated intravenous boluses,
els. PBPK models allow for the adaptability needed to
constant intravenous infusion, single or repeated injec-
simulate varied physiological processes and system condi-
tions at various body sites, inhalation, and topical expo-
tions. PBPK models are therefore likely to assume an
sures under various conditions. As long as the influences
ever more important role in our efforts to understand and
of dependent parameters on the reference concentration/
predict the consequences of exposure to toxicants, and its
time curve can be reliably identified, the model can be
application in veterinary toxicology can be expected to
used to simulate the effects of variations in parameter
expand.
values. It can also be used to do limited hypotheses test-
ing related to key parameters. An example of this
approach is the use of a PBPK model to describe the REFERENCES
transdermal absorption of organophosphate insecticides in
flow-through diffusion cells (Fig. 8.9)(Van der Merwe Andersen, M.E., Green, T., Frederick, C.B., Bogdanffy, M.S., 2002.
et al., 2006). Detailed independent parameter estimations, Physiologically based pharmacokinetic (PBPK) models for nasal
in a relatively simple physiological system, reduced the tissue dosimetry of organic esters: assessing the state-of-
knowledge and risk assessment applications with methyl
dependent parameters to three—each with an identifiable
methacrylate and vinyl acetate. Reg. Toxicol. Pharmacol. 36,
influence on the concentration/time curve in the receptor
234 245.
chamber of the flow-through cell. Sensitivity analyses
Andersen, M.E., Lutz, R.W., Liao, K.H., Lutz, W.K., 2006. Dose-
were used to identify important parameters and to gener-
incidence modeling: Consequences of linking quantal measures of
ate hypotheses regarding the effects of changes in the response to depletion of critical tissue targets. Toxicol. Sci. 89,
skin related to those parameters. This approach can be 331 337.
used to discover important parameters in silico, which can Audoly, S., Bellu, G., D’Angio, L., et al., 2001. Global identifiability of
be used to generate testable hypotheses. For example, the nonlinear models of biological systems. IEEE Transact. Biomed.
number of cell layers in the stratum corneum was identi- Eng. 48, 55 65.
fied as an important parameter and the effect of changing Brocklebank, J.R., Namdari, R., Law, F.C.P., 1997. An oxytetracycline
numbers of cell layers was simulated. The simulation residue depletion study to assess the physiologically based pharmo-
kinetic (PBPK) model in farmed Atlantic salmon. Can. Vet. J. 38,
645 646.
Buur, J., Baynes, R., Smith, G., Riviere, J., 2006. Use of probabilistic
Solvent evaporation Drug evaporation modeling within a physiologically based pharmacokinetic model to
predict sulfamethazine residue withdrawal times in edible tissues in
swine. Antimicrob. Agents Chemother. 50, 2344 2351.
Buur, J.L., Baynes, R.E., Craigmill, A.L., Riviere, J.E., 2005.
Skin surface Drug
Development of a physiologic-based pharmacokinetic model for
estimating sulfamethazine concentrations in swine and application to
Stratum corneum Drug prediction of violative residues in edible tissues. Am. J. Vet. Res.
66, 1686 1693.
Colburn, W.A., 1988. Physiologic pharmacokinetic modeling. J. Clin.
Viable skin Drug
Pharmacol. 8, 673 677.
Craigmill, A.L., 2003. A physiologically based pharmacokinetic model
Q Q for oxytetracycline residues in sheep. J. Vet. Pharmacol. Ther. 26,
b in b out
55 63.
Evans, M.V., Andersen, M.E., 2000. Sensitivity analysis of a physiologi-
FIGURE 8.9 Schematic diagram of a physiologically based pharmaco- cal model for 2,3,7,8-tetrachlorocdibenzo-p-dioxin (TCDD): asses-
kinetic model used to describe the transdermal absorption of organophos- sing the impact of specific model parameters on sequestration in
phate insecticides in flow-through diffusion cells. liver and fat in the rat. Toxicol. Sci. 54, 71 80.