Enhancement of Biokinetics using Physiologically-Based Models for Internalized Radionuclides
Funding: National Institutes of Health – National Institute of Allergy and Infectious Diseases via Northwestern University (G. Woloschak), Award Number P01AI165380; Multi-Scale Evaluation and Mitigation of Toxicities Following Internal Radionuclide Contamination
Period of Performance: March 10, 2022-Feb. 28, 2027
Project Website: https://sites.northwestern.edu/allrems/
Following mass population exposures from radiological or nuclear (RN) events, radionuclide biokinetic models can be used to determine the time-dependent activity concentrations of internalized radionuclides in various tissues and organs of the body as needed for dose assessment during triage. RN events may include radionuclide releases from a radiological dispersion device, an improvised nuclear device, or a nuclear reactor accident event. Biokinetic models from the International Commission on Radiological Protection (ICRP) are currently implemented as deterministic (i.e., single “reference”) compartment-based models developed primarily for occupational radiation protection purposes. We hypothesize that new biokinetic models with realistic RN source term parameters and metabolic variability representative of an exposed population can be used to reliably predict radionuclide biodistribution and responses at different levels of biological organization. The overall goal of Project 2 is to integrate physiologically-based models of radionuclide intake and systemic biokinetics with stochastic probability distributions of key model parameters. The core challenge in constructing realistic biokinetic models representative of an exposed non-reference population is the lack of consideration of basic physiological processes, from defining realistic source terms from RN events and translation to mechanistic parameters that define inhalation intake kinetics, uptake into blood, and excretion. The proposed expansion in biokinetic modeling will for the first time allow in-vivo assay and prediction of the efficacy of novel decorporation agents in humans following an acute RN uptake for a representative population. Primary elements of innovation in Project 2 include: (1) Development of biokinetic models specific to realistic RN sources; (2) Conducting stochastic analysis of ICRP 133 Human Respiratory Tract Model for realistic RN source term and biokinetic behavior; (3) Development of inhalation dose coefficients for exposed population (age/sex/morphometry- specific) from realistic exposure source terms; (4) Construction of computational fluid and particle dynamics (CFPD)-based physiological mouth-lung model of particle intake using realistic source terms and measurement data of particulate distribution in the lungs; and (5) Employment of machine learning with physiologically-based pharmacokinetic models to determine the time-dependent uptake, retention, excretion, and reconstruction of radionuclides to evaluate the efficacy of decorporation countermeasure agents. The proposed work will support Project 1 software in providing non- reference inhalation dose coefficients, as well as detector efficiency whole body response functions for triage. Project 1 and 3 data will be leveraged to a create mesh-based CFPD model of inhalation kinetics. Project 4 animal data will be leveraged to propose animal-to-human scaling models of the efficacy of the decorporation agent, inclusive of age and sex variables where possible.