Enzyme‐Triggered <scp>l</scp>‐<i>α</i>/<scp>d</scp>‐Peptide Hydrogels as a Long‐Acting Injectable Platform for Systemic Delivery of HIV/AIDS Drugs
Bibliographic record
Abstract
Abstract Eradicating HIV/AIDS by 2030 is a central goal of the World Health Organization. Patient adherence to complicated dosage regimens remains a key barrier. There is a need for convenient long‐acting formulations that deliver drugs over sustained periods. This paper presents an alternative platform, an injectable in situ forming hydrogel implant to deliver a model antiretroviral drug (zidovudine [AZT]) over 28 days. The formulation is a self‐assembling ultrashort d or l ‐ α peptide hydrogelator, namely phosphorylated (naphthalene‐2‐ly)‐acetyl‐diphenylalanine‐lysine‐tyrosine‐OH (NapFFKY[p]‐OH), covalently conjugated to zidovudine via an ester linkage. Rheological analysis demonstrates phosphatase enzyme instructed self‐assembly, with hydrogels forming within minutes. Small angle neutron scattering data suggest hydrogels form narrow radius (≈2 nm), large length fibers closely fitting the flexible cylinder elliptical model. d ‐Peptides are particularly promising for long‐acting delivery, displaying protease resistance for 28 days. Drug release, via hydrolysis of the ester linkage, progress under physiological conditions (37 °C, pH 7.4, H 2 O). Subcutaneous administration of Napffk(AZT)Y[p]G‐OH in Sprague Dawley rats demonstrate zidovudine blood plasma concentrations within the half maximal inhibitory concentration (IC 50 ) range (30–130 ng mL −1 ) for 35 days. This work is a proof‐of‐concept for the development of a long‐acting combined injectable in situ forming peptide hydrogel implant. These products are imperative given their potential impact on society.
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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) | 0.001 | 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".