Size Analysis of a Pressurized Metered Dose Inhaler-Delivered Solution Formulation by an Aerosizer <sup>®</sup> -LD Time-of-Flight Aerosol Particle Size Spectrometer
Bibliographic record
Abstract
In a previous study, an Aerosizer-LD time-of-flight (TOF) aerosol spectrometer was shown to underestimate significantly the aerodynamic size of airborne particles produced following actuation of a suspension-based formulation delivered from a pressurized metered-dose inhaler (pMDI) via a nonelectrostatic valved holding chamber (VHC). It was postulated that the nonspecific nature of the particle detection system in terms of chemical composition was responsible for the inclusion of smaller non-drug-containing excipient particles in the measured size distribution data from this analyzer. This limitation may not apply to certain solution formulations in which the only particles remaining after the evaporation of propellant and volatile excipient (solubilizer) are composed of pure drug substance. Such a formulation (QVAR, HFA-formulated beclomethasone di-propionate [BDP]) has recently become available, and the present investigation was therefore designed to test this hypothesis. Aerosizer-LD measured mass-weighted size distribution data for QVAR had a mass median aerodynamic diameter (MMAD) close to 1.1 microm, very similar to published data for this parameter, based on measurement of the aerosol by cascade impactor followed by drug-specific assay. However, the Aerosizer-LD underestimated the spread of the size distribution significantly. The causes are believed to be a combination of two separate effects: (1) lack of sensitivity of the particle detection system to particles finer than about 0.7 microm aerodynamic diameter and (2) preferential removal of particles larger than the MMAD, either by evaporation of residual solvent (ethanol) or by inertial/gravitational deposition in the sampling arrangement upstream of the measurement zone.
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".