Ocular Gene Therapy with Adeno-associated Virus Vectors: Current Outlook for Patients and Researchers
Bibliographic record
Abstract
In this “Perspective”, we discuss ocular gene therapy – the patient’s perspective, the various strategies of gene replacement and gene editing, the place of adenoassociated virus vectors, routes of delivery to the eye and the remaining question - “why does immunity continue to limit efficacy?” Through the coordinated efforts of patients, researchers, granting agencies and industry, and after many years of pre-clinical studies, biochemical, cellular, and animal models, we are seeing clinical trials emerge for many previously untreatable heritable ocular disorders. The pathway to therapies has been led by the successful treatment of the RPE65 form of Leber congenital amaurosis with LUXTURNATM. In some cases, immune reactions to the vectors continue to occur, limiting efficacy. The underlying mechanisms of inflammation require further study, and new vectors need to be designed that limit the triggers of immunity. Researchers studying ocular gene therapies and clinicians enrolling patients in clinical trials must recognize the current limitations of these therapies to properly manage expectations and avoid disappointment, but we believe that gene therapies are well on their way to successful, widespread utilization to treat heritable ocular disorders.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".