Abstract
Physiologically based pharmacokinetic (PBPK) models can be used to develop frameworks for risk assessment and predictive toxicology testing routines. However, the predictive power of these models is only as good as the confidence in the parameters within the model itself. Sensitivity analysis, or the study of the effect of propagated error on the predictive power of the model, can be used to determine which model parameters are most likely to affect change in the model. This is important when considering optimization routines, as optimizing non-sensitive parameters may lead to biologically incorrect parameter estimates. This study explores the sensitivity of physiological, metabolic, and chemical-specific parameters for a published dermal exposure PBPK model of bromochloromethane.
Acknowledgments
The authors would like to thank Dr. Marina V. Evans of the U.S. EPA for her helpful comments and the students in the Spring 2019 BIG Problems course at Southern New Hampshire University for their contributions to this work.
Citation
Megan E. Sawyer. Jessica McElwain. John W. Kenney. "Applications of Global Sensitivity Analysis to the Optimization of a Dermal PBPK Model of Bromochloromethane." Missouri J. Math. Sci. 33 (2) 137 - 150, November 2021. https://doi.org/10.35834/2021/3302137
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