Extended release peptide delivery systems through the use of PLGA microsphere combinations
Bibliographic record
Abstract
The purpose of this study was to evaluate the utility of combining polymer matrices to overcome extended lag periods or unacceptably short durations of action intrinsic in the individual polymer systems. Leuprolide, an LHRH superagonist, was incorporated into a variety of poly(lactide-co-glycolide) (PLGA) matrices using a solvent extraction/evaporation method. The in vitro release of Leuprolide from these matrices was evaluated at pH 7.0 and 37 degrees C in phosphate buffer. The formulations were administered to an animal model at 3 or 9 mg kg(-1) doses and serum testosterone levels were followed using a RIA method. A two-part system was made by combining microspheres made from a 75:25 acid terminated PLGA and microspheres made from a 75:25 ester terminated PLGA. This combination elicited chemical castration from 10-100 days. A three-part combination composed of an ester terminated 75:25 PLGA formulation, an ester terminated 50:50 PLGA formulation and an acid terminated 50:50 PLGA formulation also provided a composite profile with an onset of 10 days and a duration of approximately 100 days. Additionally, a single polymer system composed of a high molecular weight ester terminated 75:25 PLGA was employed to produce release over the desired 90-day release period. This study demonstrates that microsphere combinations can potentially provide effective therapies over extended intervals when combined at the proper ratio.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".