Evidence map›Paper›PMID 40284502›Full record

ReviewPharmaceutics2025

Nanomedicine-Enhanced Radiotherapy for Glioblastoma: Advances in Targeted Therapy and Adaptive Treatment Strategies.

Kamila Rawojć, Mansoor M Ahmed, Ayesha Mukhtiar, Magdalena Łukowiak, Kamil Kisielewicz

Abstract readReview
In one paragraph

Review in Pharmaceutics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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

5 authors.

Kamila RawojćNational Institute of Oncology, Maria Sklodowska-Curie Memorial Institute, 31-115 Cracow, Poland.ORCID 0000-0002-5212-5484
Mansoor M AhmedAlbert Einstein College of Medicine, Montefiore Einstein, New York, NY 10461, USA.ORCID 0000-0002-4634-9430
Ayesha MukhtiarSeneca Valley High School, Germantown, MD 20874, USA.
Magdalena ŁukowiakDepartment of Medical Physics, Pomeranian Medical University, 70-204 Szczecin, Poland.
Kamil KisielewiczNational Institute of Oncology, Maria Sklodowska-Curie Memorial Institute, 31-115 Cracow, Poland.ORCID 0000-0003-3217-2918

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Glioblastoma multiforme remains one of the most aggressive and treatment-resistant brain tumors that necessitate innovative therapeutic approaches. Nanomedicine has emerged as a promising strategy to enhance radiation therapy by improving drug delivery, radiosensitization, and real-time treatment monitoring. Stimuli-responsive nanoparticles can overcome limitations of the blood-brain barrier, modulate tumor microenvironment, and facilitate targeted therapeutic interventions. The integration of nanotechnology with proton and X-ray radiotherapy offers improved dose precision, enhanced radiosensitization, and adaptive treatment strategies. Furthermore, Artificial Intelligence-driven nanoparticle designs are optimizing therapeutic outcomes by tailoring formulations to tumor-specific characteristics. While promising, clinical translation remains a challenge that requires rigorous validation to ensure safety and efficacy. This review highlights advancements in nanomedicine-enhanced radiotherapy and future directions for glioblastoma multiforme treatment.

Indexed as

adaptive radiotherapyblood–brain barrier (BBB)glioblastoma multiforme (GBM)golden nanopeanutshypoxia-targeting nanomedicineimmunogenic cell death (ICD)immunotherapynanomedicinepersonalized oncologyproton therapyradiosensitizationredox-responsive nanocarriersstimuli-responsive nanoparticlestumor microenvironment (TME)

Identifiers

PMID40284502
PMCPMC12030262

What OpenQuestion holds

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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.