ReviewDrug delivery and translational research2026
Emerging innovations in ophthalmic drug delivery for diabetic retinopathy: a translational perspective.
Review in Drug delivery and translational research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Hydrogel-Based Ocular Drug Delivery Systems: A Bibliometric and Visualization Analysis of Research Trends and Hotspots (1991-2025).Pharmaceutics · 2026Article
- Exosome-based therapies for corneal disorders: current status and future perspectives.MedScience · 2026Review
- Emerging ophthalmic drug delivery.Drug delivery and translational research · 2026Article
- Hydrogel-based delivery of MSCs and derivatives for improved diabetic retinopathy therapy.Stem cell research & therapy · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Diabetic retinopathy (DR) is a progressive microvascular complication of diabetes and a leading cause of vision impairment worldwide. Despite advancements in pharmacotherapy, challenges such as poor intraocular bioavailability, rapid drug clearance, and the restrictive blood-retinal barrier hinder effective treatment. Recent innovations in ophthalmic drug delivery systems offer promising solutions to these limitations. This review explores advanced drug delivery strategies, including biodegradable intravitreal implants, nanoparticle-based carriers, and gene therapy approaches, which enhance targeted drug delivery, prolong therapeutic effects, and reduce adverse systemic exposure. Sustained-release formulations of corticosteroids and anti-vascular endothelial growth factor (anti-VEGF) agents have demonstrated improved clinical outcomes in DR management. Additionally, novel biomaterial-based hydrogels, microneedle arrays, and cell-based therapies are emerging as potential game-changers in retinal drug delivery. Cutting-edge approaches such as CRISPR Cas9 gene editing, stem cell-derived exosome therapies, and artificial intelligence (AI) -driven precision medicine are further expanding the therapeutic landscape. While these advancements show significant potential, challenges such as drug stability, biocompatibility, and patient adherence must be addressed to ensure translational success. Future research should focus on optimizing pharmacokinetic properties, integrating nanotechnology with personalized medicine, and developing minimally invasive delivery platforms. A multidisciplinary approach combining biomedical engineering, molecular biology, and computational modelling will be essential for advancing DR therapeutics. This review provides a comprehensive analysis of the evolving landscape of ophthalmic drug delivery, highlighting the potential of next-generation technologies to transform DR treatment and improve patient outcomes.
Indexed as
Identifiers
40685494What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.