UNASSIGNED: Cigarette smoking can lead to a host of adverse health effects such as lung and heart disease. Increased lung cancer risk is associated with inhalation of carcinogens present in a puff of smoke. These carcinogenic compounds deposit in the lung at different sites and trigger a cascade of events leading to adverse outcomes. Understanding the site-specific deposition of various smoke constituents will inform the study of respiratory diseases from cigarette smoking. We previously developed a deposition model for inhalation of aerosol from electronic nicotine delivery systems. In this study, the model was modified to simulate inhalation of cigarette smoke consisting of soluble and insoluble tar, nicotine, and cigarette-specific constituents that are known or possible human carcinogens.
UNASSIGNED: The deposition model was further modified to account for nicotine protonation and other cigarette-specific physics-based mechanisms that affect smoke deposition. Model predictions showed a total respiratory tract uptake in the lung for formaldehyde (99%), nicotine (80%), and benzo[a]pyrene (60%).
UNASSIGNED: The site of deposition and uptake depended primarily on the constituent\'s saturation vapor pressure. High vapor pressure constituents such as formaldehyde were preferentially absorbed in the oral cavity and proximal lung regions, while low vapor pressure constituents such as benzo[a]pyrene were deposited in the deep lung regions. Model predictions of exhaled droplet size, droplet retention, nicotine retention, and uptake of aldehydes compared favorably with experimental data.
UNASSIGNED: The deposition model can be integrated into exposure assessments and other studies that evaluate potential adverse health effects from cigarette smoking.

OBJECTIVE: A combined in vitro - in silico methodology was designed to estimate pharmacokinetics of budesonide delivered via dry powder inhaler.
METHODS: Particle size distributions from three budesonide DPIs, measured with a Next Generation Impactor and Alberta Idealized Throat, were input into a lung deposition model to predict regional deposition. Subsequent systemic exposure was estimated using a pharmacokinetic model that incorporated Nernst-Brunner dissolution in the conducting airways to predict the net influence of dissolution, mucociliary clearance, and absorption.
RESULTS: DPIs demonstrated significant in vitro differences in deposition, resulting in large differences in simulated regional deposition in the central conducting airways and the alveolar region. Similar but low deposition in the small conducting airways was observed with each DPI. Pharmacokinetic predictions showed good agreement with in vivo data from the literature. Peak systemic concentration was tied primarily to the alveolar dose, while the area under the curve was more dependent on the total lung dose. Tracheobronchial deposition was poorly correlated with pharmacokinetic data.
CONCLUSIONS: Combination of realistic in vitro experiments, lung deposition modeling, and pharmacokinetic modeling was shown to provide reasonable estimation of in vivo systemic exposure from DPIs. Such combined approaches are useful in the development of orally inhaled drug products.

Fused deposition modeling (FDM™) 3-dimensional printing uses polymer filament to build objects. Some polymer filaments are formulated with additives, though it is unknown if they are released during printing. Three commercially available filaments that contained carbon nanotubes (CNTs) were printed with a desktop FDM™ 3-D printer in a chamber while monitoring total particle number concentration and size distribution. Airborne particles were collected on filters and analyzed using electron microscopy. Carbonyl compounds were identified by mass spectrometry. The elemental carbon content of the bulk CNT-containing filaments was 1.5 to 5.2 wt%. CNT-containing filaments released up to 1010 ultrafine (d < 100 nm) particles/g printed and 106 to 108 respirable (d ~0.5 to 2 μm) particles/g printed. From microscopy, 1% of the emitted respirable polymer particles contained visible CNTs. Carbonyl emissions were observed above the limit of detection (LOD) but were below the limit of quantitation (LOQ). Modeling indicated that, for all filaments, the average proportional lung deposition of CNT-containing polymer particles was 6.5%, 5.7%, and 7.2% for the head airways, tracheobronchiolar, and pulmonary regions, respectively. If CNT-containing polymer particles are hazardous, it would be prudent to control emissions during use of these filaments.

The performance of pressurized metered dose inhalers (MDIs) is affected by formulation and device variables that impact delivered dose, aerodynamic particle size distribution, and consequently lung deposition and therapeutic effect. Specific formulation variables of relevance to two commercially available products-Proventil® HFA [albuterol sulfate (AS) suspension] and Qvar® [beclomethasone dipropionate (BDP) solution]-were evaluated to determine their influence on key performance attributes measured experimentally with in vitro cascade impaction studies. These commercial MDIs, utilized as model systems, provided mid-points for a design of experiments (DoE) plan to manufacture multiple suspension and solution MDI formulations. The experimental results were utilized as input variables in a computational dosimetry model to predict the effects of MDI formulation variables on lung deposition. For the BDP solution DoE MDIs, increased concentrations of surfactant oleic acid (0-2% w/w) increased lung deposition from 24 to 46%, whereas changes in concentration of the cosolvent ethanol (7-9% w/w) had no effect on lung deposition. For the AS suspension DoE MDIs, changes in oleic acid concentration (0.005-0.25% w/w) did not have significant effects on lung deposition, whereas lung deposition decreased from 48 to 26% as ethanol concentration increased from 2 to 20% w/w, and changes in micronized drug volumetric median particle size distribution (X50, 1.4-2.5 μm) increased deposition in the tracheobronchial airways from 5 to 11%. A direct correlation was observed between fine particle fraction and predicted lung deposition. These results demonstrate the value of using dosimetry models to further explore relationships between performance variables and lung deposition.