Evidence map›Paper›PMID 32079348›Full record

ArticlePharmaceutics2020

Impact of Mucin on Drug Diffusion: Development of a Straightforward in Vitro Method for the Determination of Drug Diffusivity in the Presence of Mucin.

Margherita Falavigna, Paul C Stein, Gøril Eide Flaten, Massimiliano Pio di Cagno

Open access · goldAbstract read
In one paragraph

Article in Pharmaceutics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
2.5field-weighted citation impact, top 12% 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

22 citing papers in PubMed, 44 citations in OpenAlex.

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  13. In Vitro Models of Biological Barriers for Nanomedical Research.International journal of molecular sciences · 2022
    Review
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  19. HumanPharmaceutics · 2022
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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 3 institutions in 2 countries.

Margherita FalavignaDrug Transport and Delivery Research Group, Department of Pharmacy, UiT The Arctic University of Norway, Universitetsvegen 57, 9037 Tromsø, Norway.
Paul C SteinDepartment of Physics, Chemistry & Pharmacy, University of Southern Denmark, Campusvej 55, 5230 Odense, Denmark.
Gøril Eide FlatenDrug Transport and Delivery Research Group, Department of Pharmacy, UiT The Arctic University of Norway, Universitetsvegen 57, 9037 Tromsø, Norway.
Massimiliano Pio di CagnoDrug Transport and Delivery Research Group, Department of Pharmacy, UiT The Arctic University of Norway, Universitetsvegen 57, 9037 Tromsø, Norway.
UiT The Arctic University of Norway · NOUniversity of Oslo · NOUniversity of Southern Denmark · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mucosal drug delivery accounts for various administration routes (i.e., oral, vaginal, ocular, pulmonary, etc.) and offers a vast surface for the permeation of drugs. However, the mucus layer which shields and lubricates all mucosal tissues can compromise drugs from reaching the epithelial site, thus affecting their absorption and therapeutic effect. Therefore, the effect of the mucus layer on drug absorption has to be evaluated early in the drug-development phase, prior to in vivo studies. For this reason, we developed a simple, cost-effective and reproducible method employing UV-visible localized spectroscopy for the assessment of the interaction between mucin and drugs with different physicochemical characteristics. The mucin-drug interaction was investigated by measuring the drug relative diffusivity (D

Indexed as

diffusionmucinmucin–drug interactionmucosal drug deliverypermeabilityUV-visible localized spectroscopy

Identifiers

PMID32079348
PMCPMC7076515
OpenAlexW3006568135

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.