Retinitis Pigmentosa: Novel Therapeutic Targets and Drug Development
Bibliographic record
Abstract
Retinitis pigmentosa (RP) is a heterogeneous group of hereditary diseases characterized by progressive degeneration of retinal photoreceptors leading to progressive visual decline. It is the most common type of inherited retinal dystrophy and has a high burden on both patients and society. This condition causes gradual loss of vision, with its typical manifestations including nyctalopia, concentric visual field loss, and ultimately bilateral central vision loss. It is one of the leading causes of visual disability and blindness in people under 60 years old and affects over 1.5 million people worldwide. There is currently no curative treatment for people with RP, and only a small group of patients with confirmed RPE65 mutations are eligible to receive the only gene therapy on the market: voretigene neparvovec. The current therapeutic armamentarium is limited to retinoids, vitamin A supplements, protection from sunlight, visual aids, and medical and surgical interventions to treat ophthalmic comorbidities, which only aim to slow down the progression of the disease. Considering such a limited therapeutic landscape, there is an urgent need for developing new and individualized therapeutic modalities targeting retinal degeneration. Although the heterogeneity of gene mutations involved in RP makes its target treatment development difficult, recent fundamental studies showed promising progress in elucidation of the photoreceptor degeneration mechanism. The discovery of novel molecule therapeutics that can selectively target specific receptors or specific pathways will serve as a solid foundation for advanced drug development. This article is a review of recent progress in novel treatment of RP focusing on preclinical stage fundamental research on molecular targets, which will serve as a starting point for advanced drug development. We will review the alterations in the molecular pathways involved in the development of RP, mainly those regarding endoplasmic reticulum (ER) stress and apoptotic pathways, maintenance of the redox balance, and genomic stability. We will then discuss the therapeutic approaches under development, such as gene and cell therapy, as well as the recent literature identifying novel potential drug targets for RP.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| 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".