Systematic Studies on Surface Erosion of Photocrosslinked Polyanhydride Tablets and Data Correlation with Release Kinetic Models
Bibliographic record
Abstract
Photocrosslinkable polyanhydrides that undergo surface erosion are suitable materials for controlled-release drug delivery systems. Investigating the impact of different parameters on their erosion behavior is essential before use in drug delivery systems. Although their synthesis is well-established, parameters that may substantially affect the erosion of thiol-ene polyanhydrides including temperature and pH of the media, the geometry of the polymers, and the media shaking rate (the convective force for the polymer erosion), have not yet been studied. This study explores the effects of different environmental and geometric parameters on mass loss (erosion) profiles of polyanhydrides synthesized by thiol-ene photopolymerization. A comparative study on several release kinetic models fitting is also described for a better understanding of the polymer erosion behavior. The results demonstrated that although the temperature was the only parameter that affected the induction period substantially, the mass-loss rate was influenced by the polymer composition, tablet geometry, temperature, pH, and mass transfer (shaking) rate. With regard to geometrical parameters, polymers with the same surface area to volume ratios showed similar mass loss trends despite their various volumes and surface areas. The mass loss of polyanhydride tablets with more complicated geometries than a simple slab was shown to be non-linear, and the kinetic model study indicated the dominant surface erosion mechanism. The results of this study allow for designing and manufacturing efficient delivery systems with a high-predictable drug release required in precision medicine using surface-erodible polyanhydrides.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".