Chitosan-based Polymer Matrix for Pharmaceutical Excipients and Drug Delivery
Bibliographic record
Abstract
The development of innovative drug delivery systems, versatile to different drug characteristics with better effectiveness and safety, has always been in high demand. Chitosan, an aminopolysaccharide, derived from natural chitin biomass, has received much attention as one of the emerging pharmaceutical excipients and drug delivery entities. Chitosan and its derivatives can be used for direct compression tablets, as disintegrant for controlled release or for improving dissolution. Chitosan has been reported for use in drug delivery system to produce drugs with enhanced muco-adhesiveness, permeation, absorption and bioavailability. Due to filmogenic and ionic properties of chitosan and its derivative(s), drug release mechanism using microsphere technology in hydrogel formulation is particularly relevant to pharmaceutical product development. This review highlights the suitability and future of chitosan in drug delivery with special attention to drug loading and release from chitosan based hydrogels. Extensive studies on the favorable non-toxicity, biocompatibility, biodegradability, solubility and molecular weight variation have made this polymer an attractive candidate for developing novel drug delivery systems including various advanced therapeutic applications such as gene delivery, DNA based drugs, organ specific drug carrier, cancer drug carrier, etc.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".