Gene Therapy for Inherited Retinal Disease: Current Strategies, Personalized Medicine, and Future Implications—A Comprehensive Review
Bibliographic record
Abstract
Gene therapy represents a transformative frontier in ophthalmology, offering the potential to address inherited and acquired retinal diseases at their genetic origin rather than through symptomatic management. By introducing exogenous genetic material to restore or modulate gene expression, gene therapy aims to preserve or even restore vision in patients with mutations that disrupt normal retinal function. The eye’s small, compartmentalized structure, relative immune privilege, and direct accessibility through subretinal or intravitreal routes make it an ideal target for localized delivery with minimal systemic exposure. The approval of voretigene neparvovec-rzyl for RPE65-mediated retinal dystrophy marked a pivotal milestone, establishing proof of concept for durable and safe gene replacement therapy. Looking ahead, continued refinements in vector design, CRISPR-based editing strategies, and delivery platforms are expected to expand the therapeutic reach of gene therapy beyond monogenic disorders. With multiple early-phase clinical trials underway for inherited and acquired retinal diseases, the coming decade is poised to bring broader applicability, improved durability, and more accessible gene-based treatments across the spectrum of retinal pathology.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".