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Updated: Jun 20, 2025

Modeling and Simulations of Olfactory Drug Delivery with Passive and Active Controls of Nasally Inhaled Pharmaceutical Aerosols
Published on: May 20, 2016
Influencing factors of particle deposition in the human nasal cavity
Yingke Guo1, Yuanyuan Tang1, Yingfeng Su1
1Department of Otolaryngology Head and Neck Surgery Second Affiliated Hospital of Dalian Medical University Dalian Liaoning Province China.
Objective:
To review the existing literature on the application of computational fluid dynamics methods to study nasal particle deposition and to summarize and analyze the factors affecting nasal particle deposition in order to provide theoretical references for the development of future transnasal drug delivery devices and the prevention of respiratory-related diseases.
Data Source:
PubMed and CNKI databases.
Methods:
A search of all current literature (up to and including February 2023) was conducted. Search terms related to the topic of factors influencing nasal particle deposition were identified, and queries were conducted to identify relevant articles.
Results:
Both the properties of the particles themselves and the environmental conditions external to the particles can affect particle deposition in the nasal cavity, with particle deposition showing a positive correlation with particle size, particle density, and airflow velocity, with increasing subject age leading to a decrease in deposition, and with the relationship between airflow temperature and humidity still requiring more research to further explore.
Conclusions:
With the popularity of computational fluid dynamics, more and more scholars have applied computational fluid dynamics technology to explore the influence of different parameters on particle deposition. By summarizing and analyzing the influence law of various factors on deposition, it can provide a theoretical basis for the future development and application of transnasal drug delivery devices and the prevention of respiratory-related diseases, which makes a significant contribution to the optimization of clinical disease prevention and treatment.
Level Of Evidence:
NA.
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