Evidence map›Paper›PMID 40584779›Full record

ReviewInternational journal of nanomedicine2025

Intranasal and Pulmonary Lipid Nanoparticles for Gene Delivery: Turning Challenges into Opportunities.

Yaman Tayyar, Adi Idris, Hadi Yassine

Abstract readReview
In one paragraph

Review in International journal of nanomedicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

3 authors.

Yaman TayyarBiomedical Research Centre, QU Health, Qatar University, Doha, Qatar.ORCID 0000-0003-4385-0569
Adi Idris *Institute for Biomedicine and Glycomics, Griffith University, Brisbane, QLD, Australia.
Hadi Yassine *Biomedical Research Centre, QU Health, Qatar University, Doha, Qatar.ORCID 0000-0001-7592-2788

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Delivery of nano-therapeutics through the nasal route offers a promising approach for several applications, including intranasal conditions, pulmonary delivery, brain targeting, and vaccination. Despite its potential, this method faces significant challenges, including overcoming the mucosal barrier, ensuring consistent absorption, controlling the deposition area, and managing immunogenic responses. This review provides a comprehensive overview of the current state of nasally delivered lipid nanoparticles (LNPs) for gene medicine, focusing on the specific barriers encountered in this delivery route and strategies to overcome them. We examine how formulation composition affects stability during aerosolization, analyze the impact of particle characteristics on mucociliary clearance, and evaluate interactions with the lung surfactant layer. The review also compares delivery devices including metered-dose inhalers, dry powder inhalers, and nebulizers, highlighting how device selection influences LNP integrity and deposition patterns. Furthermore, we explore potential safety considerations with intranasal LNPs and propose approaches to mitigate adverse effects. By addressing these challenges with evidence-based strategies, this review aims to advance the development and clinical application of intranasal and pulmonary LNP delivery systems for gene-based therapeutics and vaccines.

Indexed as

Gene Transfer TechniquesLipidsNanoparticlesAdministration, IntranasalAnimalsGenetic TherapyHumansLiposomesLungMucociliary ClearanceLipid NanoparticlesLipidsLiposomesgene medicineintranasal deliverylipid nanoparticlesLNPs

Identifiers

PMID40584779
PMCPMC12204099

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.