<i>In Vitro</i> Investigation of the Effect of Ambient Humidity on Regional Delivered Dose with Solution and Suspension MDIs
Bibliographic record
Abstract
BACKGROUND: Existing literature has shown that high relative humidity (RH) affects in vitro aerosol drug delivery of nebulizer and pressurized metered dose inhaler (pMDI) formulations. The aim of this study is to investigate in vitro mouth-throat deposition and lung delivery of selected solution and suspension pMDI formulations, under a range of RH, temperature, and flow rate conditions. METHODS: The Alberta Idealized Throat was connected to a collection filter and placed in an environmental control chamber. The formulations selected were beclomethasone dipropionate (BDP) in 13% w/w ethanol/1.3% w/w glycerol and HFA-134a propellant solution ("BDP HFA134a"), BDP in 13% w/w ethanol and HFA-227 propellant solution ("BDP HFA227"), and Flixotide Evohaler (fluticasone propionate 250 μg/dose in HFA-134a suspension). Each of these pMDI formulations was dispersed into the mouth-throat and filter assembly in triplicate, according to an experimental matrix consisting of the following conditions: air flow rates of 28.3, 60, and 90 L/min; 0%, 35%, and 80% RH; operating temperatures of 20°C and 40°C. RESULTS: There was a general increase in mouth-throat deposition and corresponding decrease in filter deposition (representing lung dose fraction), with increasing RH for both BDP HFA134a and Flixotide pMDIs. Increasing temperature from 20°C to 40°C resulted in decreased mouth-throat deposition and increased lung dose fraction for the solution pMDIs, but generally no effect for the suspension pMDI. CONCLUSIONS: Not only is the dose delivery of pMDI formulations affected by environmental conditions (in some cases causing up to 50% reduction in lung delivery), but solution and suspension formulations also behave differently in response to these conditions. These results have implications during dosage form design, testing, and for usage patient use.
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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 | 0.000 |
| 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) | 0.002 | 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".