Evidence map›Paper›PMID 36365167›Full record

ArticlePharmaceutics2022

Development of In Vitro Evaluation System for Assessing Drug Dissolution Considering Physiological Environment in Nasal Cavity.

Daisuke Inoue, Ayari Yamashita, Hideto To

Abstract read
In one paragraph

Article in Pharmaceutics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Article
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

3 authors.

Daisuke InoueDepartment of Medical Pharmaceutics, School of Pharmacy and Pharmaceutical Sciences, University of Toyama, 2630 Sugitani, Toyama 930-0194, Japan.ORCID 0000-0003-0219-4331
Ayari YamashitaMolecular Pharmaceutics Laboratory, College of Pharmaceutical Sciences, Ritsumeikan University, 1-1-1 Noji-higashi, Kusatsu, Shiga 525-8577, Japan.
Hideto ToDepartment of Medical Pharmaceutics, School of Pharmacy and Pharmaceutical Sciences, University of Toyama, 2630 Sugitani, Toyama 930-0194, Japan.

Funding

Japan Society for the Promotion of Science 19K16465Japan Society for the Promotion of Science 22K06709
6 · The paper itself

Abstract

Estimating the dissolution behavior of a solid in the nasal mucus is challenging for solid dosage forms designed for the nasal application as the solid dissolves into nasal mucus and permeates through the mucosa. In the current study, the dissolution behavior of powders in the artificial nasal fluid was investigated using a 3D-printed chamber system to establish in vitro evaluation system for the dissolution of solid formulations that can simulate the intranasal environment in vivo. The dissolution rates of the five model drugs correlated with their solubility (r2 = 0.956, p < 0.01). The permeation rate of drugs across the Calu-3 cell layers after powder application depends on the membrane permeability of the drug. An analysis of membrane permeability considering the dissolution of powders showed the possibility of characterizing whether the drug in the powder was dissolution-limited or permeation-limited. This suggests that critical information can be obtained to understand which mechanism is more effective for the improvement of drug absorption from powders. This study indicates that the elucidation of drug dissolution behavior into nasal mucus is an important factor for the formulation of nasal powders and that the in vitro system developed could be a useful tool.

Indexed as

3D-printingCalu-3 cell linedissolutionin vitro evaluationmucosal permeationnasal absorptionnasal formulationnasal mucuspowder formulation

Identifiers

PMID36365167
PMCPMC9697526

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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.