Background Accurate evaluation of regional drug deposition within the respiratory tract is essential for optimizing inhalation therapy efficacy and minimizing adverse effects. However, non-invasive, real-time quantitative methods for site-specific drug delivery assessment remain limited. Objective To develop mathematical models to predict site-specific drug deposition from a dry powder inhaler (DPI) using a non-invasive, real-time photo reflection method (PRM). Methods Using Symbicort ® Turbuhaler ® as a model DPI, four inhalation patterns varying in peak flow rate (PFR: 30–60 L/min) and flow increase rate (FIR: 3.2–9.6 L/s 2 ) were simulated using a human inhalation flow simulator. Aerodynamic particle deposition of budesonide was quantified as the fine particle fraction for the whole lung (FPF WL ), peripheral airways (FPF PA ), and oropharyngeal region using an Andersen Cascade Impactor. Particle emission signals were monitored via PRM. The relationship between particle emission signals and deposition performance was analyzed using four univariate models: linear, logarithmic, Hill, and Emax. Results Increased PFR and FIR enhanced drug deposition in both the lungs and oropharyngeal region. FPF WL and FPF PA were strongly correlated with total particle emission intensity over time with the Hill model ( R 2 = 0.86 and 0.74 for FPF WL and FPF PA , respectively), reflecting nonlinear deagglomeration. Oropharyngeal deposition correlated with flow rate at particle emission peak, fitting a linear model ( R 2 = 0.82), consistent with inertial impaction mechanisms. Conclusion Using an in-vitro model, particle emission signals enable the prediction of site-specific drug deposition from DPI, providing non-invasive, real-time indices and offering personalized inhalation performance assessment beyond conventional flow rate metrics.
Hatazoe et al. (Fri,) studied this question.