Your browser doesn't support javascript.
Prediction of Transport, Deposition, and Resultant Immune Response of Nasal Spray Vaccine Droplets using a CFPD-HCD Model in a 6-Year-Old Upper Airway Geometry to Potentially Prevent COVID-19 (preprint)
biorxiv; 2022.
Preprint in English | bioRxiv | ID: ppzbmed-10.1101.2022.11.08.515673
ABSTRACT
This study focuses on the transport, deposition, and triggered immune response of intranasal vaccine droplets to the Angiotensin-converting enzyme 2-rich region (i.e., the olfactory region (OR)) in the nasal cavity of a 6-year-old female to possibly prevent COVID-19. To investigate how administration strategy can influence nasal vaccine efficiency, a validated multiscale model (i.e., computational fluid-particle dynamics (CFPD) and host-cell dynamics (HCD) model) was employed. Droplet deposition fraction, size change, residence time, and the area percentage of OR covered by the vaccine droplets and triggered immune system response were predicted with different spray cone angles, initial droplet velocities, and compositions. Numerical results indicate that droplet initial velocity and composition have negligible influences on the vaccine delivery efficiency to OR. In contrast, the spray cone angle can significantly impact vaccine delivery efficiency. The triggered immunity was not significantly influenced by the administration investigated in this study, due to the low percentage of OR area covered by the droplets. To enhance the effectiveness of the intranasal vaccine to prevent COVID-19 infection, it is necessary to optimize the vaccine formulation and administration strategy so that the vaccine droplets can cover more epithelial cells in OR to minimize the available receptors for SARS-CoV-2.
Subject(s)

Full text: Available Collection: Preprints Database: bioRxiv Main subject: Carcinoma, Renal Cell / COVID-19 Language: English Year: 2022 Document Type: Preprint

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: Preprints Database: bioRxiv Main subject: Carcinoma, Renal Cell / COVID-19 Language: English Year: 2022 Document Type: Preprint