Evidence map›Paper›PMID 41094228›Full record

ReviewDrug delivery and translational research2026

Electron paramagnetic resonance (EPR) meets drug delivery and biomaterials: a magnetic love story.

Bernard Gallez

Abstract readReview
In one paragraph

Review in Drug delivery and translational research, 2026. 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

1 author.

Bernard GallezLouvain Drug Research Institute, Biomedical Magnetic Resonance, UCLouvain, Avenue Mounier 73.08, Brussels, B-1200, Belgium. bernard.gallez@uclouvain.be.ORCID http://orcid.org/0000-0002-5708-1302

Funding

Communauté française de Belgique ARC 21/26-118Fonds De La Recherche Scientifique - FNRS J.0084.22Fonds De La Recherche Scientifique - FNRS J.0086.24Fonds De La Recherche Scientifique - FNRS U.G025.25
6 · The paper itself

Abstract

This narrative review underscores the powerful role of Electron Paramagnetic Resonance (EPR), also known as Electron Spin Resonance (ESR), in characterizing drug delivery systems (DDSs). Using drugs or probes tagged with spin labels, EPR provides detailed insights into structural and dynamic properties, as well as the molecular microenvironment (including micro-viscosity, micro-polarity, and micro-pH) and enables real-time monitoring of drug release and degradation processes both in vitro and in vivo. In nanomedicine research, EPR can also serve as a quantitative tool to track the fate of DDSs doped with iron oxide particles that are used in theranostics. Beyond DDS characterization, EPR has contributed substantially to elucidating radical mechanisms within material matrices, notably in bone cements and dental resins used for restorative applications. Moreover, incorporating paramagnetic compounds into DDSs or biomaterials has broadened the scope of EPR applications, enabling precise measurements of oxygen and nitric oxide levels in complex biological environments. The incorporation of oxygen sensors into biocompatible matrices has also enabled the development of implantable resonators for measuring oxygen at substantial tissue depths. Incorporating oxygen sensors into cell therapy implantable devices or grafted tissues can serve as an indicator of both oxygenation and vascularization.

Indexed as

Biocompatible MaterialsDrug Delivery SystemsAnimalsElectron Spin Resonance SpectroscopyHumansOxygenBiocompatible MaterialsOxygenBiocompatibilityDrug deliveryDrug releaseEPRESROxygen

Identifiers

PMID41094228
PMCPMC13294175

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.