Pharmaceutical aerosols deposition patterns from a Dry Powder Inhaler: Euler Lagrangian prediction and validation

Area of Science:

• Pulmonary drug delivery
• Computational fluid dynamics
• Respiratory system modeling

Background:

• Accurate prediction of drug deposition in the human lung is crucial for effective inhaled therapies.
• Computational Fluid Dynamics (CFD) offers a powerful tool for analyzing airflow and particle transport in respiratory models.
• Previous CFD studies often simplified lung geometry or included the inhaler device, increasing computational cost.

Purpose of the Study:

• To predict and validate Budesonide deposition patterns in human lung models using CFD.
• To compare deposition in a simplified trachea model versus an advanced model with anatomical features.
• To assess the impact of tracheal rings on drug deposition patterns.

Main Methods:

• Euler-Lagrangian CFD simulations were employed to model particle transport.
• Two lung models were used: a basic ring-less trachea and an advanced Human Zygote5 model.
• The inhaler device was excluded from the domain; its effect was mimicked by a conical particle jet inlet.

Main Results:

• CFD simulations successfully predicted enhanced Budesonide deposition in the tracheal and first-generation rings/ridges of the Zygote5 model.
• The advanced model demonstrated higher deposition due to vorticity created by the ring structures.
• The ring-less model did not show the same enhanced deposition patterns.

Conclusions:

• Anatomically accurate lung models, including tracheal ridges, are essential for physiologically consistent CFD deposition predictions.
• CFD simulations provide valuable insights into factors influencing inhaled drug deposition.
• Empirical models may need adjustments to account for lighter, recirculating particles.