Evidence map›Paper›PMID 36839849›Full record

ArticlePharmaceutics2023

Rapidly Dissolving Microneedles for the Delivery of Steroid-Loaded Nanoparticles Intended for the Treatment of Inflammatory Skin Diseases.

Hala Dawud, Aiman Abu Ammar

Abstract read
In one paragraph

Article in Pharmaceutics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

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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

2 authors.

Hala DawudDepartment of Pharmaceutical Engineering, Azrieli College of Engineering Jerusalem, 26 Yaakov Shreibom Street, Ramat Beit HaKerem, Jerusalem 9103501, Israel.
Aiman Abu AmmarDepartment of Pharmaceutical Engineering, Azrieli College of Engineering Jerusalem, 26 Yaakov Shreibom Street, Ramat Beit HaKerem, Jerusalem 9103501, Israel.ORCID 0000-0002-2556-3120

Funding

CSRD VA 1
6 · The paper itself

Abstract

Drug delivery through the skin has immense advantages compared to other routes of administration and offers an optimal way to treat inflammatory skin diseases, where corticosteroids are the cornerstone of topical therapy. Still, their therapeutic efficiency is limited due to inadequate skin permeability, potential side effects, and reduced patient compliance. To overcome these drawbacks, we propose a drug delivery system consisting of dexamethasone (DEX)-loaded poly(lactic-co-glycolic acid) (PLGA) nanoparticles (NPs) incorporated in sodium alginate (SA) microneedles (MNs) as a minimally invasive dosage form for controlled drug release. Drug-loaded PLGA NPs were prepared by a nanoprecipitation method with a high encapsulation yield. They exhibited a controlled release pattern over 120 h. A modified vacuum-deposition micromolding method was used to load the obtained DEX-NPs into the tips of dissolving MNs. The NP-MNs showed improved insertion capabilities into the skin-simulant parafilm model and enhanced mechanical strength when tested against different static forces compared to their counterparts (SA-MNs). The results of an MN dissolution study following application to ex vivo chicken skin and agarose gel indicate that the NP-loaded segments of MNs dissolve within 15 s, in which the NPs are released into the skin. Taken together, the incorporation of DEX-NPs into SA-MNs could be a promising approach to bypass the limitations of conventional topical treatment of skin diseases, allowing for self-administration, increased patient compliance, and controlled drug release.

Indexed as

controlled releasedissolving microneedlesinflammatory skin diseasesnanoparticlesPLGA (poly lactic-co-glycolic acid)steroids

Identifiers

PMID36839849
PMCPMC9967926

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Registered trials

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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.