Sustained Drug Release in Nanomedicine: A Long-Acting Nanocarrier-Based Formulation for Glaucoma
Bibliographic record
Abstract
Therapeutic nanomedicine has concentrated mostly on anticancer therapy by making use of the nanosize for targeted therapy. Such nanocarriers are not expected to have sustained release of the bioactive molecule beyond a few days. There are other conditions where patients can benefit from sustained duration of action following a single instillation, but achieving this has been difficult in nanosized carriers. An important prerequisite for sustained delivery over several months is to have sufficiently high drug loading, without disruption or changes to the shape of the nanocarriers. Here we report on successful development of a drug-encapsulated nanocarrier for reducing intraocular pressure in a diseased nonhuman primate model and explain why it has been possible to achieve sustained action in vivo. The drug is a prostaglandin derivative, latanoprost, while the carrier is a nanosized unilamellar vesicle. The mechanistic details of this unique drug-nanocarrier combination were elucidated by isothermal titration calorimetry. We show, using Cryo-TEM and dynamic light scattering, that the spherical shape of the liposomes is conserved even at the highest loading of latanoprost and that specific molecular interactions between the drug and the lipid are the reasons behind improved stability and sustained release. The in vivo results clearly attest to sustained efficacy of lowering the intraocular pressure for 120 days, making this an excellent candidate to be the first truly sustained-release nanomedicine product. The mechanistic details we have uncovered should enable development of similar systems for other conditions where sustained release from nanocarriers is desired.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".