Optimizing Aerosolization Using Computational Fluid Dynamics in a Pediatric Air-Jet Dry Powder Inhaler

Area of Science:

• Pharmaceutical Engineering
• Biomedical Engineering
• Computational Fluid Dynamics

Background:

• Pediatric dry powder inhalers (DPIs) require optimization for efficient aerosol drug delivery.
• Computational fluid dynamics (CFD) offers a powerful tool for simulating and optimizing inhaler performance.
• Traditional CFD simulations of powder aerosolization are computationally intensive.

Purpose of the Study:

• To optimize the performance of a pediatric air-jet DPI using CFD simulations and experimental validation.
• To identify key flow-field-based dispersion parameters correlating with aerosolization metrics.
• To develop an automated CFD process for optimizing inhaler design parameters.

Main Methods:

• Utilized CFD simulations to model the internal flow pathway of the pediatric air-jet DPI.
• Focused on flow-field-based dispersion parameters instead of full powder bed breakup simulations.
• Employed an automated CFD process to iterate over 100 designs, optimizing inlet and outlet capillary diameters.
• Supported CFD findings with experimental analysis of aerosol formation and performance metrics.

Main Results:

• Mass median aerodynamic diameter (MMAD) correlated with normalized turbulent kinetic energy and flow kinetic energy.
• Emitted dose (ED) correlated with input flow rate and capillary diameter ratio.
• Optimized designs achieved MMAD < 1.6 μm and ED > 90% of the loaded dose.
• Predicted low extrathoracic deposition (<10%, potentially <5%) at 15 L/min.

Conclusions:

• CFD-based dispersion parameters can effectively guide the optimization of pediatric DPIs.
• Automated CFD optimization successfully identified improved inhaler designs.
• The optimized pediatric air-jet DPI demonstrates significantly enhanced aerosol delivery efficiency for pediatric patients.