Preparation and Characterization of Spray-Dried Inhalable Powders Containing Polymeric Micelles for Pulmonary Delivery of Paclitaxel in Lung Cancer
Bibliographic record
Abstract
PURPOSE: Local delivery of chemotherapeutic drugs to the lungs offers many advantages for lung cancer treatment compared to conventional systemic chemotherapy. In the present study, novel mixed polymeric micelles based on tocopheryl succinate-polyethylene glycol 1000 and 5000 Da (TPGS1K and TPGS5K) were synthesized and loaded with paclitaxel (PTX). Then, the optimized micelles were incorporated as colloidal drug delivery system into lactose carrier particles using a spray drying technique. METHODS: The mixed micelles of TPGS5K and TPGS1K in different molar ratios (10:0, 7:3, 5:5, 3:7, 0:10) were prepared and physicochemical properties including: particle size, zeta potential, critical micelle concentration (CMC), drug loading, drug release rate, and in vitro cytotoxicitywere investigated in details. The optimized nanoparticles were co-spray dried with lactose carriers to produce the spherical particle morphology of the inhalable particles. RESULTS: Particle sizes and zeta potentials of the different formulations varied in the range of 102 to 196 nm and -9.4 to -13.8 mV, respectively. The lowest CMC values were calculated for 5:5 and 7:3 combinations (16.33 and 17.89 µM, respectively). The drug release rate from different formulations were very slow and only 30% of the drug was released during 72 h. Cytotoxicity assay demonstrated increased cytotoxic activity of PTX-loaded mixed micelles compared to the free drug. The in vitro deposition data indicated that spray drying of PTX-loaded micelles with lactose resulted in the production of inhalable powders with the high fine particle fraction (60%). CONCLUSION: These results demonstrate that this novel PTX-loaded micelles embedded in dry powder inhalation aerosol platform has a great potential to be used in lung cancer treatment.
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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 | 0.001 | 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) | 0.000 | 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".