Characterization of Aerosol Deposition in Children and Infants Using Idealized Extrathoracic Geometries
Bibliographic record
Abstract
This thesis describes a number of experimental studies performed with the common goal of characterizing pharmaceutical aerosol deposition in children and infants using idealized extrathoracic geometries. First, an in vitro study of the recently proposed Alberta Idealized Child Throat showed that this idealized child oral extrathoracic airway model accurately replicates average deposition of pharmaceutical aerosol from pressurized metered dose inhalers and dry powder inhalers in school age children. This successful validation confirms that the Alberta Idealized Child Throat may indeed fulfill the existing requirement for a standardized platform in which benchtop testing of delivery devices and therapeutic formulations developed for children can be examined. Second, a joint in vitro – in silico methodology was employed to characterize deposition in an idealized infant nasal extrathoracic airway geometry. Using a novel flow system, total lung dose from two pressurized metered dose inhalers, delivered via valved holding chamber and facemask under a realistic breath profile, was approximated by the dose delivered distal to the idealized geometry. In silico simulations using this estimate of total lung dose provided insight on regional deposition in the lungs and on the concentration of drug in the airway surface liquid. From a clinical perspective, this in vitro – in silico methodology provides valuable guidance on the dosing required for efficacious use of aerosolized medications in infants. Finally, a comparison of in vitro deposition measured in two idealized geometries representative of the oral extrathoracic airways of children is described, illustrating the importance of considering the physics governing aerosol behavior in the human airways when developing idealized geometries meant to mimic in vivo deposition. It is hoped that the experiments undertaken as part of this thesis will aid in the development of new delivery devices and inhalation therapies for the treatment of disease in children and infants.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".