Relating in-device particle behaviour to aerosol metrics using high-speed imaging and NGI measurements.

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 (r2 = 0.85) and FPF (r2 = 0.96); large-particle (D > 30 µm) turbulent kinetic energy with emitted fraction (r2 = 0.90), FPF (r2 = 0.96) and GSD (r2 = 0.60); and small-particle (D < 30 µm) turbulent kinetic energy with FPF (r2 = 0.65). Size-based metrics became predictive when evaluated over an early-phase time window, t50 defined to characterise the size distribution before fines have evacuated from the device, correlating with MMAD (r2 = 0.70) and GSD (r2 = 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.