Evidence map›Paper›PMID 40837711›Full record

ReviewFrontiers in drug delivery2025

Advanced drug delivery systems for oral squamous cell carcinoma: a comprehensive review of nanotechnology-based and other innovative approaches.

Alain Herrada Céspedes, Montserrat Reyes, Javier O Morales

Abstract readReview
In one paragraph

Review in Frontiers in drug delivery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Review
  5. Review
  6. Review
  7. Article
  8. Review
  9. 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.

Alain Herrada CéspedesDrug Delivery Laboratory, Department of Pharmaceutical Science and Technology, School of Chemical and Pharmaceutical Sciences, Universidad de Chile, Santiago, Chile.
Montserrat ReyesDepartment of Oral Pathology and Medicine, Faculty of Dentistry, Universidad de Chile, Santiago, Chile.
Javier O MoralesDrug Delivery Laboratory, Department of Pharmaceutical Science and Technology, School of Chemical and Pharmaceutical Sciences, Universidad de Chile, Santiago, Chile.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Oral cancer, particularly oral squamous cell carcinoma (OSCC), poses significant challenges due to its aggressiveness, high metastatic potential, and resistance to conventional therapies. Recent advancements in drug delivery systems (DDS), including nanotechnology, intelligent hydrogels, lipid nanoparticles, and photodynamic therapy (PDT), offer innovative solutions for targeted treatment. These DDS utilize tumor-specific stimuli, such as pH variations, reactive oxygen species (ROS), and enzymatic activity, to achieve precise drug release while minimizing systemic toxicity. Cutting-edge technologies, such as microelectromechanical systems (MEMS) and artificial intelligence (AI), are enhancing the precision and personalization of DDS. Combination therapies integrating chemotherapy, PDT, and immunotherapy show promise in overcoming current limitations. Despite significant progress, challenges remain in scalability, patient-specific customization, and safety assessments. This review synthesizes the state-of-the-art in DDS for OSCC, highlighting future directions and the need for interdisciplinary collaboration to improve therapeutic outcomes and patient quality of life.

Indexed as

drug delivery systemsimmunotherapyintelligent hydrogelslipid nanoparticlesnanotechnologyoral canceroral squamous cell carcinomaphotodynamic therapy

Identifiers

PMID40837711
PMCPMC12360444

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.