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  • 2000-2004  (3)
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  • 1
    Electronic Resource
    Electronic Resource
    350 Main Street , Malden , MA 02148 , USA , and 9600 Garsington Road , Oxford OX4 2DQ , UK . : Blackwell Publishing, Inc.
    Risk analysis 24 (2004), S. 0 
    ISSN: 1539-6924
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Notes: One measure of the potency of compounds that lead to the effects through ligand-dependent gene transcription is the relative affinity for the critical receptor. Endocrine active compounds that are presumed to act principally through binding to the estrogen receptor (e.g., estradiol, genistein, bisphenol A, and octylphenol) comprise one class of such compounds. For making simple comparisons, receptor-binding affinity has been equated to in vivo potency, which consequently defines the dose-response characteristics for the compound. Direct extrapolation of in vitro estimated affinities to the corresponding in vivo system and to specific species or life stages (e.g., neonatal, pregnancy) can be misleading. Accurate comparison of the potency of endocrine active compounds requires characterization of biochemical and pharmacokinetic factors that affect their free concentration. Quantitative in vitro and in vivo models were developed for integrating pharmacokinetics factors (e.g., serum protein and receptor-binding affinities, clearance) that affect potency. Data for parameterizing these models for several estrogenic compounds were evaluated and the models exercised. While simulations of adult human or rat sera were generally successful, difficulties in describing early life stages were identified. Exogenous compounds were predicted to be largely ineffective at competing estradiol off serum-binding proteins, suggesting this was unlikely to be physiologically significant. Discrepancies were identified between relative potencies based upon modeling in vitro receptor-binding activity versus in vivo activity in the presence of clearance and serum-binding proteins. The examples illustrate the utility of this approach for integrating available experimental data from in vitro and in vivo studies to estimate the relative potency of these compounds.
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    350 Main Street , Malden , MA 02148 , USA , and 9600 Garsington Road , Oxford OX4 2DQ , UK . : Blackwell Publishing, Inc.
    Risk analysis 24 (2004), S. 0 
    ISSN: 1539-6924
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Notes: Proposed applications of increasingly sophisticated biologically-based computational models, such as physiologically-based pharmacokinetic models, raise the issue of how to evaluate whether the models are adequate for proposed uses, including safety or risk assessment. A six-step process for model evaluation is described. It relies on multidisciplinary expertise to address the biological, toxicological, mathematical, statistical, and risk assessment aspects of the modeling and its application. The first step is to have a clear definition of the purpose(s) of the model in the particular assessment; this provides critical perspectives on all subsequent steps. The second step is to evaluate the biological characterization described by the model structure based on the intended uses of the model and available information on the compound being modeled or related compounds. The next two steps review the mathematical equations used to describe the biology and their implementation in an appropriate computer program. At this point, the values selected for the model parameters (i.e., model calibration) must be evaluated. Thus, the fifth step is a combination of evaluating the model parameterization and calibration against data and evaluating the uncertainty in the model outputs. The final step is to evaluate specialized analyses that were done using the model, such as modeling of population distributions of parameters leading to population estimates for model outcomes or inclusion of early pharmacodynamic events. The process also helps to define the kinds of documentation that would be needed for a model to facilitate its evaluation and implementation.
    Type of Medium: Electronic Resource
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  • 3
    Publication Date: 2004-09-01
    Print ISSN: 1570-0232
    Electronic ISSN: 1873-376X
    Topics: Chemistry and Pharmacology
    Published by Elsevier
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