Dose delivery characteristics and lung deposition of indacaterol/glycopyrronium/mometasone furoate (IND/GLY/MF) and IND/MF via Breezhaler® device: An Alberta Idealised Throat (AIT) evaluation
Bibliographic record
Abstract
Background: Once-daily, fixed-dose combinations (FDC) of IND/GLY/MF and IND/MF, delivered via Breezhaler® dry powder inhaler, are approved for maintenance treatment of asthma. The AIT model provides an in vitro measure of oropharyngeal and lung deposition of aerosolised particles delivered from inhalation devices. This study evaluated lung deposition of IND/GLY/MF and IND/MF delivered via Breezhaler® using the AIT. Methods: AIT connected to Next Generation Impactor was used to evaluate oropharyngeal and lung deposition, device retention, and stage-by-stage distribution of the individual drug components (IND, GLY, MF) at various flow rates (50, 75, 100 and 120 L/min). Results: AIT-simulated lung deposition of both IND/GLY/MF and IND/MF FDC products showed a good match across dosage strengths (high- and medium-dose). At lower flow rates, a lower deposition in oropharynx balanced with higher inhaler device retention of drug particles was observed and vice versa at higher flow rates, which subsequently lead to consistently high lung delivery of all the drug components across all flow rates investigated (Table). Conclusion: Both IND/GLY/MF and IND/MF FDC products demonstrated similar lung deposition and highly consistent doses over the wide range of investigated flow rates, despite differences in the composition of the formulations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".