Sign in
BioengineeringPhysics of Fluids
Peer-reviewed journal article

Eulerian-Lagrangian and thin film modeling of drug delivery under physiologically varying breathing in a realistic lung model

Sameer Kumar VermaiD, Saurabh BhardwajiD, Kishore Singh PateliD, Bukke Kiran NaikiD

Abstract

This work presents a computational approach to investigate antiviral aerosol deposition in anatomically realistic human airways under various physiological inhalation conditions. Antiviral drugs are represented as fine liquid droplets that form a thin coating on airway surfaces, primarily targeting early infection sites. The suggested method combines an Eulerian-Lagrangian discrete phase model (DPM) to track droplet motion and an Eulerian wall film (EWF) model to mimic the evolution of deposited liquid films. This combination effectively addresses the shortcomings of previous studies that employed DPM exclusively, which ignored the post-deposition redistribution dynamics of liquid drugs on airway surfaces. Furthermore, the effects of the distressed breathing of patients with chronic obstructive pulmonary disease (COPD) are compared with both idealized and physiologically realistic breathing patterns in healthy individuals. The study assesses airflow parameters, film thickness, deposition efficiency, and surface area coverage for aerosol particles from 1 to 10 {micro}m. Results reveal that distressed breathing patterns of COPD patients significantly alter the deposition preferences between the upper (~5.28%) and lower lobes (~2.52%) compared to the equivalent ideal and realistic healthy inhalations. Moreover, the distressed breathing also limits the drug penetration into deeper generations, as the highest surface coverage is observed at the carinal region rather than the usual left lower lobe (LLL) found in ideal and realistic healthy breathing cases. Such deposition contrasts highlight the importance of optimizing inhalation therapy and device designs for individuals with obstructive airway diseases.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISYi '26Bartlett '21Zhang '26Ben-Porat '21García-Mout '26Hayati '22
74% semantic matchBioengineering
Hang Yi, Yu Feng·bioRxiv·Oct 16, 2026