Evidence map›Paper›PMID 33920816›Full record

ReviewPolymers2021

Polymer-Based Smart Drug Delivery Systems for Skin Application and Demonstration of Stimuli-Responsiveness.

Louise Van Gheluwe, Igor Chourpa, Coline Gaigne, Emilie Munnier

Open access · goldAbstract readReview
In one paragraph

Review in Polymers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 1 pooled it
6.2field-weighted citation impact, top 2% 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

35 citing papers in PubMed, 1 synthesis or guideline pooled it, 102 citations in OpenAlex.

  1. Pooled it
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  17. Plant Extract-Derived Carbon Dots as Cosmetic Ingredients.Nanomaterials (Basel, Switzerland) · 2023
    Review
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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 1 institution in 1 country.

Louise Van GheluweEA 6295 Nanomédicaments et Nanosondes, Faculté de Pharmacie, Université de Tours, 31 Avenue Monge, 37200 Tours, France.
Igor ChourpaEA 6295 Nanomédicaments et Nanosondes, Faculté de Pharmacie, Université de Tours, 31 Avenue Monge, 37200 Tours, France.
Coline GaigneEA 6295 Nanomédicaments et Nanosondes, Faculté de Pharmacie, Université de Tours, 31 Avenue Monge, 37200 Tours, France.
Emilie MunnierEA 6295 Nanomédicaments et Nanosondes, Faculté de Pharmacie, Université de Tours, 31 Avenue Monge, 37200 Tours, France.ORCID 0000-0002-6691-4484
Université de Tours · FR

Funding

Conseil Régional du Centre-Val de Loire 2017-00118114
6 · The paper itself

Abstract

Progress in recent years in the field of stimuli-responsive polymers, whose properties change depending on the intensity of a signal, permitted an increase in smart drug delivery systems (SDDS). SDDS have attracted the attention of the scientific community because they can help meet two current challenges of the pharmaceutical industry: targeted drug delivery and personalized medicine. Controlled release of the active ingredient can be achieved through various stimuli, among which are temperature, pH, redox potential or even enzymes. SDDS, hitherto explored mainly in oncology, are now developed in the fields of dermatology and cosmetics. They are mostly hydrogels or nanosystems, and the most-used stimuli are pH and temperature. This review offers an overview of polymer-based SDDS developed to trigger the release of active ingredients intended to treat skin conditions or pathologies. The methods used to attest to stimuli-responsiveness in vitro, ex vivo and in vivo are discussed.

Indexed as

cosmeticsdermatologypolymerssmart drug delivery systems

Identifiers

PMID33920816
PMCPMC8071137
OpenAlexW3152810395

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.