Validation of In-Silico Lung Deposition Predictions for Inhaled Liposomal Amikacin Against Scintigraphy Data

Navid Monshi Tousi¹, Hosein Sadafi¹, Ana Costa¹ & Jan De Backer²

¹Fluidda N.V., Groeningenlei 132, Kontich, 2550, Belgium

² Fluidda Inc., 228 East 45^th street, 9^th Floor, Suite 9E, New York, NY10017, USA

Summary

This study presents an in-silico validation of lung deposition for liposomal amikacin delivered via the PARI LC STAR nebulizer. Building on previously published gamma scintigraphy data in healthy adults, we simulated aerosol deposition in three demographically matched subjects using functional respiratory imaging (FRI), which combines high-resolution CT-based airway modeling with computational fluid dynamics (CFD). The same particle characteristics and inhalation conditions used in the scintigraphy study were applied to approximate the experimental setup.

The simulations predicted a mean intrathoracic deposition of 29.09% ± 6.54%, closely aligning with the 32.33% ± 3.41% reported in vivo—demonstrating strong agreement despite the fact that different subjects were used and anatomical variability is naturally expected. Extrathoracic and exhaled fractions also showed reasonable correspondence, with observed differences attributable to inter-subject variability and the use of idealized breathing profiles in silico.

These findings reinforce the predictive capability of FRI-based CFD for nebulized drug products, including complex formulations such as liposomal suspensions. The results further support the accuracy of FRI in modelling aerosol deposition from nebulized liposomal formulations and support its application in the development and optimization of inhaled therapies.