Preparation and characterization of sustained release pirfenidone loaded microparticles for pulmonary drug delivery: Spray drying approach
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Pirfenidone (PFD) is a drug of choice for the treatment of idiopathic pulmonary fibrosis. For the preparation of sustained release microparticles of PFD, Ethyl cellulose (EC 300) with Eudragit RS 100 in combination was used as encapsulating agents. The 3-level 2-factorial design was employed for the design of experiments (DoE). The spray dried microparticles were studied for their particle size distribution, surface topography, drug entrapment, in-vitro drug release, and aerodynamic performance. Compatibility between drug and excipients were evaluated by Fourier Transform Infrared (FTIR) Spectroscopy and Differential Scanning Calorimetry (DSC). Particle morphology and size distribution were performed using Field Emission Scanning Electron Microscopy (FESEM) and Dynamic light scattering (DLS). The average particle size of the optimized PFD loaded formulation was found to be 3.99 μm. The surface topography study of the optimized formulation showed that the microparticles are nearly spherical with a smooth surface. In addition, the in-vitro aerosol performance was studied by Anderson cascade impactor and developed microparticles showed favorable aerodynamic performance (MMAD 4.25 μm) with narrow particle diameter distribution (GSD 1.52), therefore developed microparticles can be used as a dry powder for inhalation (DPI) for the targeted delivery to the lungs. In conclusion, sustained release microparticles of PFD were successfully prepared by the spray drying technique.
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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 | 0.000 |
| 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 it