Use of Extrathoracic Deposition Models for Patient-Specific Dose Estimation during Inhaler Design
Bibliographic record
Abstract
The lung dose of inhaled pharmaceutical aerosol that an individual will receive from an inhaler can now be more accurately estimated in light of recent extrathoracic deposition modeling that has correlated characteristic airway dimensions with deposition. This paper first summarizes the current state of extrathoracic deposition models, including recent developments that have quantified the effects of aerosol electrostatics and inhaler mouthpiece diameter on deposition. A generalized equation for predicting extrathoracic deposition in different subjects is then developed and average characteristic airway dimensions representative of different age groups are indicated. A methodology is then presented to predict the lung dose per unit body surface area individuals will receive from an inhaler. A sample calculation shows that a typical 10-year-old child subject would receive a lower lung dose per unit body surface area than an adult subject inhaling through the same inhaler at the same 90 L min-1 flow rate, due to greater extrathoracic deposition in the child. In order to provide an equivalent lung dose per unit body surface area to the child as to the adult, an inhaler particle size adjustment is specified. Finally, the use of idealized geometries for developing inhaler-specific empirical correlations and improving upon inhaler design is outlined. Keywords: Dose adjustment and selection, empirical upper airway deposition model, extrathoracic deposition fraction, inhaled pharmaceutical aerosol, inhaler design and formulation development, particle size, pediatric lung dose, respiratory drug delivery.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".