Computational Fluid Dynamics Research Corp. (CFDRC) and Philip Morris International (PMI) presented details of novel computational models of the human lung at the 10th International Aerosol Conference (IAC), which took place Sept. 2-7 in St. Louis, Missouri, USA.
The personalized models, based on advanced mathematical modeling of the human body and lung geometry, can be used to predict how aerosols will be inhaled, deposited on airway walls, and absorbed and cleared by lung physiology.
Combining high-performance computing, high-fidelity modeling and high-resolution medical imaging, the simulations have significant potential to contribute to new diagnostic tools and treatment options for respiratory disease.
“Environmental exposures, tobacco smoke, and air pollution are common risk factors for acute and chronic respiratory diseases,” said Andrzej Przekwas, chief technology officer, CFDRC.
“However, each human is unique and responds differently to exposure to these compounds. Respiratory health depends on the properties of the inhaled aerosol, the evolution of compounds in the airways, and their deposition, transport, absorption and elimination based on the specific physiology of the individual. We are now able to accurately model these complex paradigms of exposure at the level of both the individual and, by extension, the population.”
The models presented at IAC use algorithms, developed by PMI, that combine physics, chemistry, and thermodynamics to predict the behavior of aerosol mixtures. These algorithms build on the open-source computational fluid dynamics tool AeroSolved for the simulation of the generation, transport, evolution, and deposition of aerosols.
AeroSolved can be used in the development of aerosol generators and inhalation devices, and for the validation of aerosol delivery systems for in vitro and in vivo inhalation studies. In addition, it can be applied to the environmental and atmospheric sciences. Academics, research institutions, and relevant industries can download AeroSolved for their own research purposes, and in doing so contribute to its further development and application.
In the models presented at IAC, PMI’s algorithms work alongside CFDRC software to predict and quantify the behavior and effects of aerosols on the human body. The software combines analyses of pharmacokinetics, assessing how aerosols move through the airways during distribution, absorption, metabolism, and excretion, with a system biology pharmacodynamics tool to determine how the aerosols interact with cells and metabolic pathways.
Models are based on lung and body measurements taken from human respiratory system imaging datasets (computerized tomography, or CT, scans), with templates modified based on individual-specific factors (e.g. height). They have been validated against previously published models and experimental data.
“The models presented at the International Aerosol Conference are extending the frontiers of inhalation toxicology and personalized medicine,” said Arkadiusz Kuczaj, associate professor, industrial computational modeling, University of Twente, The Netherlands, and manager, aerosol research and dosimetry, PMI. “Advanced mathematical modeling of aerosol inhalation, evolution, deposition, and uptake is complex. We have demonstrated the validity of our state-of-the-art aerosol physics, high-performance computing, and big data analytics to investigate these phenomena. These computational models provide a window into the individual’s personal respiration biology, and we look forward to developing them further and to exploring their application in collaboration with our partners.”
CFDRC specializes in developing innovative simulations for industries including biotechnology, energy, materials and aerospace. They have pioneered multi-scale, multi-physics simulations of fluid, thermal, chemical, biological, electrical, and mechanical phenomena for real-world applications.
PMI is developing a portfolio of reduced-risk products, products with the potential to reduce individual risk and population harm in comparison with cigarettes.
Predicting inhalation
