Influence of Inspiratory Flow Rate, Particle Size, and Airway Caliber on Aerosolized Drug Delivery to the Lung
Bibliographic record
Abstract
A number of studies in the literature support the use of fine aerosols of drug, inhaled at low IFRs to target peripheral airways, with the objective of improving clinical responses to inhaled therapy (Fig. 8). Attempts have been made to separate response due to changes in total administered dose or the surface concentration of the dose from response due to changes in site of deposition--both are affected by the particle size of the aerosol, with IFR additionally influencing the latter. The tools for measuring dose and distribution have improved over the last 10-15 years, and thus we should expect greater accuracy in these measurements for assessing drug delivery to the lung. There are still issues, though, in producing radiolabeled (99m)technetium aerosols that are precise markers for the pharmaceutical product being tested and in quantitating absolute doses deposited in the lung. PET isotopes may provide the means for directly labelling a drug and perhaps can offer an alternative for making these measurements in the future, but deposition measurements should not be used in isolation; protocols should incorporate clinical tests to provide parallel therapeutic data in response to inhalation of the drug by the various patient populations being studied.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".