In Vivo Characterization of ONL1204, a Small Peptide Inhibitor of the Fas Receptor, as a Potential Neuroprotective Therapy for Geographic Atrophy and Dry Age-Related Macular Degeneration
Bibliographic record
Abstract
Background: Age-related macular degeneration (AMD) is a major cause of irreversible vision loss in the developed world, and the approved products for geographic atrophy (GA), a late-stage form of dry AMD, have shown limited efficacy and require frequent administration. Therefore, longer-lasting therapies with improved efficacy would be a welcome addition to AMD treatment. One potential therapeutic is ONL1204, a small peptide inhibitor of the Fas receptor that has prevented cell death and inflammation in retinal disease models. This study characterizes the pharmacokinetics (PK) and durability of protection conferred by ONL1204. Methods: Ocular pharmacokinetic profiles were generated over 3 months in rabbit and minipig following a single intravitreal (IVT) injection of ONL1204 at multiple doses. Ocular pharmacodynamics were evaluated in two models: a rabbit model using a single IVT injection of ONL1204 with a delayed sodium iodate challenge coupled with fluorescein angiography to quantify RPE loss, and a chronic mouse model that reflects key features of dry AMD disease pathology to assess the efficacy of repeat IVT administrations of ONL1204. Results: ONL1204 had prolonged residence in the ocular tissues of rabbit and minipig, with a vitreous humor half-life of over 100 days. ONL1204 demonstrated significant protection of the retinal pigment epithelium (RPE) in the rabbit sodium iodate model. In the chronic mouse model, two administrations of ONL1204 preserved RPE morphology, reduced caspase-8 activity, and decreased inflammation. Conclusions: These data represent key characteristics of ONL1204, highlighting its clinical potential as a therapeutic for chronic retinal diseases, including GA.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".