Evidence map›Paper›PMID 39897787›Full record

ReviewHeliyon2025

Drug delivery strategies to improve the treatment of corneal disorders.

Mahsa Fallah Tafti, Zeinab Fayyaz, Hossein Aghamollaei, Khosrow Jadidi, Shahab Faghihi

Abstract readReview
In one paragraph

Review in Heliyon, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Review
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Mahsa Fallah TaftiStem Cell and Regenerative Medicine Group, National Institute of Genetic Engineering and Biotechnology, Tehran 14965/161, Iran.
Zeinab FayyazEdison Biotechnology Institute, Ohio University, Athens, OH, 45701, USA.
Hossein AghamollaeiChemical Injuries Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran.
Khosrow JadidiVision Health Research Center, Semnan University of Medical Sciences, Semnan, Iran.
Shahab FaghihiStem Cell and Regenerative Medicine Group, National Institute of Genetic Engineering and Biotechnology, Tehran 14965/161, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Anterior eye disorders including dry eye syndrome, keratitis, chemical burns, and trauma have varying prevalence rates in the world. Classical dosage forms based-topical ophthalmic drugs are popular treatments for managing corneal diseases. However, current dosage forms of ocular drugs can be associated with major challenges such as the short retention time in the presence of ocular barriers. Developing alternative therapeutic methods is required to overcome drug bioavailability from ocular barriers. Nanocarriers are major platforms and promising candidates for the administration of ophthalmic drugs in an adjustable manner. This paper briefly introduces the advantages, disadvantages, and characteristics of delivery systems for the treatment of corneal diseases. Additionally, advanced technologies such as 3D printing are being considered to fabricate ocular drug carriers and determine drug dosages for personalized treatment. This comprehensive review is gathered through multiple databases such as Google Scholar, PubMed, and Web of Science. It explores information around "ocular drug delivery systems'', "nano-based drug delivery systems'', "engineered nanocarriers'', and "advanced technologies to fabricate personalized drug delivery systems''.

Indexed as

3D printingCorneal disordersDrug delivery systemsPersonalized medicine

Identifiers

PMID39897787
PMCPMC11783021

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.