Sustained-release alginate-chitosan pellets prepared by melt pelletization technique
Bibliographic record
Abstract
CONTEXT: Alginate-chitosan pellets prepared by extrusion-spheronization technique exhibited fast drug dissolution. OBJECTIVE: This study aimed to design sustained-release alginate pellets through rapid in situ matrix coacervation by chitosan during dissolution. METHODS: Pellets made of alginate with chitosan and/or calcium acetate were prepared using solvent-free melt pelletization technique which prevented reaction between processing materials during agglomeration and allowed such reaction to occur only in dissolution phase. RESULTS: Drug release was retarded in pH 2.2 medium when pellets were formulated with calcium acetate or chitosan till a change in medium pH to 6.8. The sustained-release characteristics of calcium alginate pellets were attributed to pellet dispersion and rapid cross-linking by soluble Ca(2+) during dissolution. The slow drug release characteristics of alginate-chitosan pellets were attributed to polyelectrolyte complexation and pellet aggregation into swollen structures with reduced erosion. The drug release was, however, not retarded when both calcium acetate and chitosan coexisted in the same matrix as a result of chitosan shielding of Ca(2+) to initiate alginate cross-linkages and rapid in situ solvation of calcium acetate induced fast pellet dispersion and chitosan losses from matrix. CONCLUSION: Similar to calcium alginate pellets, alginate-chitosan pellets demonstrated sustained drug release property though via different mechanisms. Combination of alginate, chitosan and calcium acetate in the same matrix nevertheless failed to retard drug release via complementary drug release pattern.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 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".