Date of Award


Document Type


Degree Name

Master of Science


Department of Mathematics and Statistics

First Advisor

Dennis Quinn, PhD


Dermal penetration of chemicals and drugs is important to both toxicologists and pharmacologists. Drug developers try to enhance and environmental professionals try to limit penetration of chemicals through the skin. Both can use predictive biologically-based mathematical models to assist in understanding the processes involved. When these models are based on physiological and biochemical parameters which can be measured in the laboratory, they can be extremely useful. Appropriately validated models based on first principles can be predictive of human exposures when the processes involved are adequately understood. In this thesis we develop four new physiologically-based pharmacokinetic (PBPK) models to predict blood concentrations of dibromomethane (DBM) in rats after neat liquid and vapor exposure. These four new models expand previously developed homogeneous models by adding skin subcompartments. These new models improve the prediction of the blood concentrations especially early in the exposure. Sensitivity analysis shows that one of the permeability constants followed by the blood air partition coefficient have the most impact on blood concentration predictions. With proper validation the new models could be used to improve species, dose, and duration extrapolations of chemical or drug penetration. They could also be used to investigate and predict concentrations of drugs or chemicals in different parts of the skin.

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