A Physiologically Based Pharmacokinetic Model Study of the Biological Fate, Transport and Behavior of Engineered Nanoparticles

Abstract

Though the use of engineered nanoparticles has been exponentially increasing, little attention has been given to the nanoparticles biodistribution in the body. This thesis aims to establish a physiologically based pharmacokinetic (PBPK) model that accounts for nano-specific biobehaviors in order to understand the biodistribution of various types of nanoparticles. I start with experimental data for polyethylene glycol-coated polyacrylamide (PAA-peg) nanoparticles intravenously injected to rats. By accounting for the phagocytosis process, the PBPK model successfully predicts the dynamics of PAA-peg nanoparticles between and within organs. According to the model, phagocytizing cells (PCs) quickly capture nanoparticles until saturation and constitute a major reservoir for nanoparticles. The PBPK framework is then adapted to address cerium oxide (CeO2) nanoparticles. A system of experimental apparatus is designed to integrate the generation, aging, and inhalation exposure of CeO2 nanoparticles to rats. The amounts found in organs are further analyzed with a mass balance approach to gain a holistic understanding of the biodistribution. The PBPK model is then slightly modified to accommodate unique phenomenon for inhaled nanoparticles including mucociliary clearance and entry into the systemic circulation by penetrating the alveolar wall. The recovered amount is predominantly in lungs and feces, with extrapulmonary organs contributing less than 2% in recovery rate. No differences in biodistribution patterns are found between fresh and aged CeO2 nanoparticles. The model predicts the biodistribution well and finds PCs in the pulmonary region are accountable for most of the nanoparticles not eliminated by feces. To expand the model’s applicability, additional biodistribution data of nanoparticles collected from literatures are used for parameterization, including three polymers nanoparticles, three different sizes of silver nanoparticles, and one CeO2 nanoparticles. Only parameters physiologically linked with the characteristics of nanoparticles are changed. Overall the model maintains its robustness by having a R2 of 0.69 – 0.97 between the log10 of measured and predicted results. The changes of certain parameters also offer insights on the relationship between nanoparticles’ characteristics and biodistribution. In summary, this work highlights the importance of phagocytosis as a major determinant of nanoparticles biodistribution and provides a tool for better evaluating the human health risks posed by nanoparticles.