Evidence map›Paper›PMID 27194165›Full record

ReviewDrug delivery and translational research2016

Lipid-based drug delivery systems in the treatment of wet age-related macular degeneration.

Joanne D Du, Wye-Khay Fong, Suzanne Caliph, Ben J Boyd

Abstract readReview
PubMed Publisher
In one paragraph

Review in Drug delivery and translational research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
1.5field-weighted citation impact, top 18% of its field
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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 22 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Review
  4. Review
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

4 authors at 2 institutions in 2 countries.

Joanne D DuDrug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University (Parkville Campus), 381 Royal Parade, Parkville, VIC, 3052, Australia.
Wye-Khay FongDrug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University (Parkville Campus), 381 Royal Parade, Parkville, VIC, 3052, Australia.
Suzanne CaliphDrug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University (Parkville Campus), 381 Royal Parade, Parkville, VIC, 3052, Australia.
Ben J BoydDrug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University (Parkville Campus), 381 Royal Parade, Parkville, VIC, 3052, Australia. ben.boyd@monash.edu.
Monash University · AUETH Zurich · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent advances in drug delivery technology have amplified potential opportunities to treat the debilitating diseases that affect the posterior segment of the eye in a less invasive and more efficient manner. Current methods for effective drug delivery to the back of the eye are hindered by many barriers and limitations. As a consequence, considerable efforts have been directed towards developing new materials to selectively deliver drug directly to the target site. This review focuses on lipid-based delivery systems which show promise in improving treatment for the most common disease of the posterior segment of the eye in the developed world, age-related macular degeneration, with an emphasis upon on-demand delivery systems as they have greater potential to overcome the current limitations.

Indexed as

Drug Delivery SystemsAnimalsHumansLipidsLiposomesWet Macular DegenerationLipidsLiposomesAge-related macular degenerationIntravitrealLipidsLiposomesStimuli responsive

Identifiers

PMID27194165
OpenAlexW2402454829

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.