Fit for the Eye: Aptamers in Ocular Disorders
Bibliographic record
Abstract
For any new class of therapeutics, there are certain types of indications that represent a natural fit. For nucleic acid ligands in general, and aptamers in particular, the eye has historically been an attractive site for therapeutic intervention. In this review, we recount the discovery and early development of three aptamers designated for use in ophthalmology, one approved (Macugen), and two in late-stage development (Fovista and Zimura). Every one of these molecules was originally intended for other indications. Key improvements in technology, specifically with regard to libraries used for in vitro selection and subsequent chemical optimization of aptamers, have played an important role in allowing the identification of development candidates with suitable properties. The lessons learned from the selection of these molecules are valuable for informing us about the many remaining opportunities for aptamer-based therapeutics in ophthalmology as well as for identifying additional indications for which aptamers as a class of therapeutics have distinct advantages.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".