学术文献库

Efficacy for COVID-19 treatments can be enhanced significantly through targeting the nasopharynx, which has been shown to be the dominant preliminary infection site for SARS-CoV-2. Although intranasal drugs can be administered easily through drops or sprays, it is difficult to test whether current protocols will deliver the right amount of the drug to this location consistently. We are interested in developing an in silico prototyping tool to rapidly identify optimal parameters for intranasal delivery. In this study, we have applied computational fluid dynamics to simulate fluid flow through the nasal cavity and examined particle deposition for a drug formulation, mimicking different delivery methods. The nasal geometry models were derived using digitized and meshed computed tomography (CT) scans of human patients. Using the nasal geometries, we simulated two different airflows: a laminar model at 15 LPM (Liters/min) that simulated resting breathing rate and a Large Eddy Simulation (LES) model used to achieve a higher flow rate of 30 LPM. We were able to run particle tracking simulations for these two airflow schemes to test different drug properties such as particle size. The different injection methods used include surface injection which best replicates an inhaler-based release of particle droplets into the nostril and the cone injection method which best replicates a spray into the nostril. The results of the study suggest that the most optimal drug particle size for targeting the intranasal infection sites is around 6-14 microns.