Understanding the performance of pressurized metered dose inhalers formulated with low Global warming potential propellants
Bibliographic record
Abstract
Switching to low-global warming potential (GWP) propellants for pressurized metered dose inhalers (pMDIs) is crucial in current inhalation product development, as it is crucial to safeguard patient access. This paper provides both theoretical and experimental evidence to advance the understanding of the relative performance of pMDIs using traditional HFA propellants (HFA-134a, HFA-227ea) versus new low-GWP propellant (HFO-1234ze, HFO-1234yf, HFC-152a) across three stages of pMDI actuation: discharge of propellant from the spray orifice, atomization of the bulk liquid into droplets, and interaction with the surrounding environment. The acoustic profiles, which represent the propellant discharge from the spray orifice, revealed that the plume duration and audio amplitude were mostly influenced by the diameter of the orifice and to a lesser extent by propellant type. The initial propellant droplet size produced after atomization of the discharged bulk liquid was evaluated by measuring content equivalent diameters at different ethanol concentrations and spray orifice diameters. Through a 0.32 mm spray orifice, propellant-only pMDIs produced droplets in the 9.0–13.5 µm range, with HFC-152a yielding the largest droplets and HFO-1234yf the smallest, while all exhibited comparable dependence on ethanol concentration and spray orifice size. Modeling of moisture condensation on propellant droplets indicated that the amount of condensed water and droplet lifetime both depend strongly on ambient humidity and ethanol concentration and only weakly on the propellant type. Three suspension formulations in HFA-134a, HFO-1234ze, or HFC-152a, were tested under varying relative humidities to evaluate the impact of ambient humidity on the in vitro aerosol performance of suspension pMDIs.Copyright © 2024 American Association for Aerosol Research
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".