Controlling Burst and Final Drug Release Times from Porous Polylactide Devices Derived from Co-continuous Polymer Blends
Bibliographic record
Abstract
This work has demonstrated that it is possible to exercise a wide range of control over both the initial burst release and the final drug release times from porous polylactide (PLA) devices derived from cocontinuous polymer blends. Two strategies were used: a layer-by-layer polyelectrolyte surface deposition approach on the porous PLA surface and the application of a partially closed-cell protocol. A PLA porous substrate with a pore size of 1.5 microm, derived from a blend of PLA and polystyrene (PS) via selective solvent extraction of the PS phase, was used as the drug delivery device. The surface area and pore dimensions were examined via BET nitrogen adsorption and image analysis. Porous PLA substrates with 0, 3, and 5 layers of polyelectrolytes and with open areas of 100, 12, and 2% were studied both separately and in combination. In vitro release tests were performed to study the release profile of bovine serum albumin (BSA) from the devices via UV spectrophotometry. It is shown that, while both are important, surface modification is more dominant in controlling the release rate than the partially closed cell approach. When a five layer surface modification of the PLA and a partially closed cell approach (2% open area) are combined, denoted as the L5C sample, the synergy is dramatic with a 5x reduction in the first two hour burst release amount and a total release time that is extended by 123x as compared to the 100% open cell, surface unmodified, reference sample. The L5C sample ultimately releases 89% of the total BSA loaded, demonstrating the high level of interconnectivity of the microchannels in the porous PLA. The mechanism of release in this system is clearly diffusion controlled with well-defined concentration gradients, as measured by X-ray photoelectron spectroscopy (XPS), observed in the direction of release. These results point toward a diffusion mechanism combined with a sorption/desorption interaction of the BSA with the modified PLA surface.
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) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".