Optimizing nasal spray parameters for efficient drug delivery using computational fluid dynamics

Abstract

Experimental images from particle/droplet image analyser (PDIA) and particle image velocimetry (PIV) imaging techniques of particle formation from a nasal spray device were taken to determine critical parameters for the study and design of effective nasal drug delivery devices. The critical parameters found were particle size, diameter of spray cone at a break-up length and a spray cone angle. A range of values for each of the parameters were ascertained through imaging analysis which were then transposed into initial particle boundary conditions for particle flow simulation within the nasal cavity by using Computational Fluid Dynamics software. An Eulerian-Lagrangian scheme was utilised to track mono-dispersed particles (10 and 20 microm) at a breathing rate of 10 L/min. The results from this qualitative study aim to assist the pharmaceutical industry to improve and help guide the design of nasal spray devices.