Relating in-device particle behaviour to aerosol metrics using high-speed imaging and NGI measurements
6 affiliations
- 1School of Engineering, Faculty of Science and Engineering, Macquarie University
- 2School of Aerospace, Mechanical and Mechatronic Engineering, The University of Sydney
- 3School of University Pharmacy, Faculty of Medicine and Health, The University of Sydney
- 4Division of Therapeutic Performance I, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration
- 5School of Mechanical and Materials Engineering, IIT Mandi
- 6Division of Quantitative Methods and Modelling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration
Abstract
This study introduces a combined optical–pharmacopoeial approach to link in-device particle dynamics with conventional aerosol performance metrics for dry powder inhalers (DPIs). High-speed imaging (HSI) was applied inside an optically accessible DPI to quantify particle/agglomerate size, velocity and turbulence across lactose-based blends and commercial formulations at flow rates between 20 and 70 L per minute (LPM). Complementary Next Generation Impactor (NGI) measurements provided aerodynamic parameters such as fine particle fraction (FPF), emitted fraction, mass median aerodynamic diameter (MMAD), and geometric standard deviation (GSD). Linear regression for the carrier-based formulations identified correlations between HSI and NGI metrics, notably: mean particle velocity with emitted fraction ( r 2 = 0.85) and FPF ( r 2 = 0.96); large-particle (D > 30 µm) turbulent kinetic energy with emitted fraction (r 2 = 0.90), FPF (r 2 = 0.96) and GSD (r 2 = 0.60); and small-particle (D < 30 µm) turbulent kinetic energy with FPF (r 2 = 0.65). Size-based metrics became predictive when evaluated over an early-phase time window, t 50 defined to characterise the size distribution before fines have evacuated from the device, correlating with MMAD (r 2 = 0.70) and GSD (r 2 = 0.77). These findings demonstrate that a small set of in-device descriptors, velocity, turbulent kinetic energy, and early-phase particle size, may serve as mechanistic predictors of downstream aerosol performance, offering a pathway to accelerate DPI design and formulation screening.
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BibTeX
@article{miltonmcgurk2026relating,
title = {{Relating in-device particle behaviour to aerosol metrics using high-speed imaging and NGI measurements}},
author = {Liam Milton-McGurk and Taye Tolu Mekonnen and Agisilaos Kourmatzis and Waiting Tai and Hak-Kim Chan and Susan Boc and Gajendra Singh and Ross Walenga and Elizabeth Bielski and Bryan Newman and Shaokoon Cheng},
journal = {International journal of pharmaceutics},
year = {2026},
month = sep,
doi = {10.1016/j.ijpharm.2026.127465},
url = {https://doi.org/10.1016/j.ijpharm.2026.127465},
note = {CC BY},
}
RIS
TY - JOUR
TI - Relating in-device particle behaviour to aerosol metrics using high-speed imaging and NGI measurements
AU - Liam Milton-McGurk
AU - Taye Tolu Mekonnen
AU - Agisilaos Kourmatzis
AU - Waiting Tai
AU - Hak-Kim Chan
AU - Susan Boc
AU - Gajendra Singh
AU - Ross Walenga
AU - Elizabeth Bielski
AU - Bryan Newman
AU - Shaokoon Cheng
PY - 2026
DA - 2026/09/25
JO - International journal of pharmaceutics
DO - 10.1016/j.ijpharm.2026.127465
UR - https://doi.org/10.1016/j.ijpharm.2026.127465
AB - This study introduces a combined optical–pharmacopoeial approach to link in-device particle dynamics with conventional aerosol performance metrics for dry powder inhalers (DPIs). High-speed imaging (HSI) was applied inside an optically accessible DPI to quantify particle/agglomerate size, velocity and turbulence across lactose-based blends and commercial formulations at flow rates between 20 and 70 L per minute (LPM). Complementary Next Generation Impactor (NGI) measurements provided aerodynamic parameters such as fine particle fraction (FPF), emitted fraction, mass median aerodynamic diameter (MMAD), and geometric standard deviation (GSD). Linear regression for the carrier-based formulations identified correlations between HSI and NGI metrics, notably: mean particle velocity with emitted fraction ( r 2 = 0.85) and FPF ( r 2 = 0.96); large-particle (D > 30 µm) turbulent kinetic energy with emitted fraction (r 2 = 0.90), FPF (r 2 = 0.96) and GSD (r 2 = 0.60); and small-particle (D < 30 µm) turbulent kinetic energy with FPF (r 2 = 0.65). Size-based metrics became predictive when evaluated over an early-phase time window, t 50 defined to characterise the size distribution before fines have evacuated from the device, correlating with MMAD (r 2 = 0.70) and GSD (r 2 = 0.77). These findings demonstrate that a small set of in-device descriptors, velocity, turbulent kinetic energy, and early-phase particle size, may serve as mechanistic predictors of downstream aerosol performance, offering a pathway to accelerate DPI design and formulation screening.
SN - 0378-5173
SN - 1873-3476
ER -