Factors Controlling Drug Release in Cross-linked Poly(valerolactone) Based Matrices
Bibliographic record
Abstract
There is keen interest in the development of biocompatible and biodegradable implantable delivery systems (IDDS) that provide sustained drug release for prolonged periods in humans. These systems have the potential to enhance therapeutic outcomes, reduce systemic toxicity, and improve patient compliance. Herein, we report the preparation and physicochemical characterization of cross-linked polymeric matrices from poly(valerolactone)- co-poly(allyl-δ-valerolactone) (PVL- co-PAVL) copolymers for use in drug delivery. A series of well-defined PVL- co-PAVL copolymers (PDI < 1.5) that vary in terms of MW and AVL content were prepared by ring opening polymerization catalyzed by 1,5,7-triazabicyclo[4.4.0]dec-5-ene. A subsequent cross-linking reaction using 1,6-hexanedithiol led to solid cylindrical amorphous or semicrystalline matrices as potential IDDS. High loading levels (up to 20% (w/w)) of several model drugs that vary in physicochemical properties, including paclitaxel, triamcinolone acetonide and hexacetonide, curcumin, and acetaminophen, were achieved using a postloading method in organic solvent. Drug-IDDS interactions were evaluated via the group contribution method and X-ray diffraction as well as calorimetric, spectroscopic, and microscopic techniques. Results indicate superior drug-matrix compatibility for drugs bearing phenyl groups. In vitro release studies under distinct sink conditions highlight the key factors (i.e., state and loading level of drug, solubility of drug in external media, and composition of release media) that impact drug release.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 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".