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Updated: Jan 10, 2026

A System to Create Stable Nanoparticle Aerosols from Nanopowders
Published on: July 26, 2016
An integrated analytical approach to evaluate powder aggregation and predict the aerodynamic performance of
Cíntia Veiga1, Mário Rodrigues2, Luís Almeida E Sousa3
1R&D Analytical Development, Hovione Farmaciência S.A., Campus do Lumiar, Building S, 1649-038 Lisboa, Portugal; Departamento de Física, Faculdade de Ciências, Universidade de Lisboa, Campo Grande, 1749-016 Lisboa, Portugal.
Abstract:
Dry Powder Inhaler (DPI) formulations generally consist of drug particles with a size between 1 and 5 µm, ideal for targeting the lower respiratory tract. However, particles within this size range are highly cohesive and prone to agglomeration, hindering effective deep-lung deposition. Despite the significant impact of particle agglomeration on aerodynamic particle size distribution (aPSD), this relationship remains poorly understood. Early-stage development often involves testing DPI performance with cascade impactors for numerous candidate formulations, making the process time-intensive and costly, which is an obstacle in DPI development. To improve and speed up the formulation screening stage, an integrated approach is proposed to evaluate particle agglomeration and predict aerodynamic performance using alternative analytical techniques. In this study, various excipients relevant to inhalation were tested, and their aggregation levels were modified by varying mixing times in a mini ball-mixer. Powder agglomeration was characterized through Laser Diffraction (LD) and Solution Calorimetry (SolCal). LD provided model descriptors which, together with particle density and surface area, correlated well with Fine Particle Fraction (FPF) measured by Fast Screening Impactor (FSI). Additionally, SolCal detected differences in energy between the different materials, correlating with their aggregation levels. Interestingly, no direct correlation emerged between the aggregation state alone and aerodynamic performance by FSI. Instead, performance depended on a combination of particle density, surface area, size, and agglomeration state. These results validate the proposed methodology for early-stage formulation development, enabling FPF prediction based on intrinsic particle properties. This approach applies only to homogeneous formulations and excludes complex heterogeneous systems like carrier-based formulations.
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