Self-aggregating long-acting injectable microcrystals
Bibliographic record
Abstract
Abstract Injectable drug depots have transformed our capacity to enhance medication adherence through dose simplification. Central to patient adoption of injectables is the acceptability of needle injections, with needle gauge as a key factor informing patient discomfort. Maximizing drug loading in injectables supports longer drug release while reducing injection volume and discomfort. Here, to address these requirements, we developed self-aggregating long-acting injectable microcrystals (SLIM), an injectable formulation containing drug microcrystals that self-aggregate in the subcutaneous space to form a monolithic implant with a low ratio of polymer excipient to drug (0.0625:1 w/w). By minimizing polymer content, SLIM supports injection through low-profile needles (<25 G) with high drug loading (293 mg ml −1 ). We demonstrate in vitro and in vivo that self-aggregation is driven by solvent exchange at the injection site and that slower-exchanging solvents result in increased microcrystal compaction and reduced implant porosity. We further show that self-aggregation enhances long-term drug release in rodents. We anticipate that SLIM could enable low-cost interventions for contraceptives.
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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) | 0.000 | 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".