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VISUALIZATION-BASED ANALYSIS FOR A MIXED-INHIBITION BINARY PBPK MODEL: DETERMINATION OF INHIBITION MECHANISM
Citation:
Isaacs, K K., M V. Evans, AND T. R. Harris. VISUALIZATION-BASED ANALYSIS FOR A MIXED-INHIBITION BINARY PBPK MODEL: DETERMINATION OF INHIBITION MECHANISM. Presented at Fifth Tennessee Conference on Biomedical Engineering, Memphis, TN, April 4-6, 2002.
Impact/Purpose:
Research will be conducted to develop and apply integrated microenvironmental, and physiologically-based pharmacokinetic (PBPK) exposure-dose models and methods (that account for all media, routes, pathways and endpoints). Specific efforts will focus on the following areas:
1) Develop the Exposure Related Dose Estimating Model (ERDEM) System.
Includes: Updating the subsystems and compartments of the ERDEM models with those features needed for modeling chemicals of interest to risk assessors;
Designing and implementing the graphical user interface for added features.
Refining the exposure interface to handle various sources of exposure information;
Providing tools for post processing as well as for uncertainty and variability analyses;
Research on numerical and symbolic mathematical/statistical solution methods and computational algorithms/software for deterministic and stochastic systems analysis.
2) Apply ERDEM and other quantitative models to understand pharmacokinetics (PK) and significantly reduce the uncertainty in the dosimetry of specific compounds of regulatory interest.
Examples of the applications are:
exposure of children to pesticides
study design
route-to-route extrapolation
species extrapolation
experimental data analysis
relationship between parametric uncertainty and the distribution of model results
validity of scaling methods within species
validity of scaling methods from one species to another species
reduction of uncertainty factors for risk assessment
Description:
A physiologically-based pharmacokinetic (PBPK) model incorporating mixed enzyme inhibition was used to determine mechanism of the metabolic interactions occurring during simultaneous inhalation exposures to the organic solvents chloroform and trichloroethylene (TCE).
Visualization-based sensitivity and identifiability analyses of the PBPK model were performed to determine the conditions under which four inhibitory constants (describing enzyme-inhibitor enzyme/substrate complex-inhibitor interactions) could be estimated. The sensitivities of the model output parameters to all four inhibitory constants were visualized at many parameter space points for several sets of experimental conditions. The local identifiability of the parameters was also analyzed at many parameter space points by testing the parameter sensitivities for linear dependence.
The sensitivity analysis predicted ideal experimental conditions for estimation of the inhibitory parameters. The inhibitory constants were graphically determined from multiple closed-chamber gas-uptake experiments performed on rats under these optimal conditions. The estimated values of the four inhibitory constants predicted that chloroform and TCE interact in a purely competitive manner.
Based on our model analysis, we present recommendations for the design of future experiments for determination of inhibition mechanism in binary chemical mixtures. We assert that a thorough analysis of the parameter-dependent sensitivity and identifiability characteristics can be used to plan efficient experimental protocols for the quantitative analysis of inhalation pharmacokinetics.
This work has been funded (wholly) or (in part) by the United States Environmental Protection Agency. It has been subjected to Agency review and approved for publication.