Computational optimization of spatial drug release to enhance inhaled particle deposition in human upper and central airways

Abstract

Inhaled drug delivery is a promising strategy for the rapid treatment of respiratory diseases due to its direct targeting of the pulmonary system. Nevertheless, challenges remain in optimizing deposition efficiency, particularly in reaching deeper lung generations and achieving directional control of particle transport. To achieve effective deep-lung aerosol delivery, the present proof-of-concept study proposes computational optimization of particle release strategies. Both non-invasive and invasive approaches are explored, with particular emphasis on release concentration and spatial positioning. Numerical simulations are conducted using a previously validated subject-specific mouth-to-lung model reconstructed from high-resolution Computed Tomography (CT) scans, ensuring anatomical realism and geometrical reproducibility. The results show that concentrated non-invasive release at the mouth plane improves particle penetration through the constricted laryngeal region. Meanwhile, invasive strategies involving focused delivery (such as catheter-based injection) lead to enhanced deposition in the deeper lung regions. Notably, directional control of deposition was preliminarily achieved, with particles preferentially targeting either the left or right lung lobe based on the injection position, offering new potential for site-specific therapy. It is concluded that the presented computational framework can provide detailed insights for optimizing particle transport and deposition in specific lung regions. These detailed insights could provide valuable information for developing novel clinical treatments for respiratory diseases.