Development of high-dose carrier-free inhalable heparin sodium microparticles using co-jet-milling technology
Bibliographic record
Abstract
Pulmonary drug delivery represents a non-invasive and efficient alternative to traditional routes of administration, with benefits including enhanced absorption and better patient adherence. This study focuses on the design of inhalable heparin sodium (HS) particles tailored for managing pulmonary infectious diseases and associated complications like pulmonary thromboembolism. A carrier-free dry powder formulation has been developed using co-jet-milling technique, utilizing magnesium stearate (MgSt) as an excipient to optimize particle properties. MgSt demonstrated the ability to modify particle characteristics, enhance aerosolization performance, and improve formulation stability. Experimental results showed that co-milling with MgSt significantly improved the emitted rate (ER) and emitted fine particle fraction (E-FPF) and stability of the formulation. These findings underscore MgSt's dual functionality in stabilizing and enhancing the aerosolization performance of carrier-free HS formulations for dry powder inhalers (DPIs), presenting an approach for high-dose carrier-free DPI formulation design.
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) | 0.000 | 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 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".