Evidence map›Paper›PMID 39204340›Full record

ArticlePharmaceutics2024

Mesoporous Silica-Based Membranes in Transdermal Drug Delivery: The Role of Drug Loss in the Skin.

Frank Baumann, Theresa Paul, Susann Ossmann, Dirk Enke, Achim Aigner

Abstract read
In one paragraph

Article in Pharmaceutics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Frank BaumannRudolf-Boehm-Institute for Pharmacology and Toxicology, Clinical Pharmacology, Faculty of Medicine, Leipzig University, 04107 Leipzig, Germany.
Theresa PaulInstitute of Chemical Technology, Leipzig University, 04103 Leipzig, Germany.
Susann OssmannLeipzig Heart Center, University Department for Cardiac Surgery, 04289 Leipzig, Germany.ORCID 0000-0001-5218-3126
Dirk EnkeInstitute of Chemical Technology, Leipzig University, 04103 Leipzig, Germany.
Achim AignerRudolf-Boehm-Institute for Pharmacology and Toxicology, Clinical Pharmacology, Faculty of Medicine, Leipzig University, 04107 Leipzig, Germany.ORCID 0000-0002-2778-6256

Funding

Deutsche Forschungsgemeinschaft AI 24/29-1Deutsche Forschungsgemeinschaft EN 942/15-1
6 · The paper itself

Abstract

Compared to other forms of drug administration, the use of Transdermal Drug Delivery Systems (TDDSs) offers significant advantages, including uniform drug release profiles that contribute to lower side effects and higher tolerability, avoidance of direct exposure to the gastrointestinal tract, better patient compliance due to their non-invasive means of application and others. Mesoporous silica membranes are of particular interest in this regard, due to their chemical stability and their tunable porous system, with adjustable pore sizes, pore volumes and surface chemistries. While this allows for fine-tuning and, thus, the development of optimized TDDSs with high loading capacities and the desired release profile of a given drug, its systemic availability also relies on skin penetration. In this paper, using a TDDS based on mesoporous silica membranes in Franz cell experiments on porcine skin, we demonstrate surprisingly substantial drug loss during skin penetration. Drug passage through porcine skin was found to be dependent on the age and pre-treatment of the skin. pH and temperature were major determinants of drug recovery rates as well, indicating drug loss in the skin by enzymatic metabolization. Regarding the TDDS, higher loading obtained by SO

Indexed as

drug metabolizationdrug releaseFranz cellLC-MSmesoporous membraneporcine skin

Identifiers

PMID39204340
PMCPMC11358937

What OpenQuestion holds

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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.