<i>In Vitro</i> Aerosol Deposition in the Oropharyngeal Region for Staccato <sup>®</sup> Loxapine
Bibliographic record
Abstract
BACKGROUND: The Staccato system employs a thermal vaporization technology to generate pure drug aerosols with a particle size optimized for alveolar deposition, leading to rapid absorption of the drug into the systemic circulation. Unlike most traditional aerosol-generation techniques, the particle size of the thermally generated aerosols is significantly affected by the airflow rate going through the device. The objective of this study was to determine the effects of flow rate and other operating conditions on predicted oropharyngeal and lung deposition when using the Staccato system. METHODS: In vitro oropharyngeal deposition was measured at airflow rates of 15-80 L/min through the device. Oropharyngeal deposition was also measured for different inhalation profiles, different ambient temperatures and humidities, and device orientations. Deposition was measured using the Alberta geometry model, which was derived based on information available in the literature, CT scans of patients, and observations of living subjects. RESULTS AND CONCLUSIONS: Deposition in the oropharyngeal geometry was consistently approximately 11% of the emitted dose throughout the entire range of flow rates. Such consistency in deposition was due to the fact that mass median aerodynamic diameter (MMAD) varied inversely as the square root of the flow rate, resulting in an approximately constant value for the inertial deposition parameter. Thus, an increase in flow rate, which would increase the momentum of a fixed particle size and generally lead to higher oropharyngeal deposition, was almost exactly counterbalanced by the accompanying decrease in MMAD. Results also showed that deposition in the oropharyngeal region was unaffected by other potentially relevant factors such as different airflow ramp rates, inhalation time, ambient temperature and relative humidity, and device orientations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".