Evidence map›Paper›PMID 40682256›Full record

ReviewThoracic cancer2025

Nanotechnology-Driven Drug Delivery Systems for Lung Cancer: Computational Advances and Clinical Perspectives.

Min Yi, Yiming Li, Hui Jie, Senyi Deng

Abstract readReview
In one paragraph

Review in Thoracic cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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

4 authors.

Min YiDepartment of Thoracic Surgery and Institute of Thoracic Oncology, West China Hospital, Sichuan University, Chengdu, China.
Yiming LiDepartment of Thoracic Surgery and Institute of Thoracic Oncology, West China Hospital, Sichuan University, Chengdu, China.ORCID https://orcid.org/0000-0002-2022-6811
Hui JieDepartment of Thoracic Surgery and Institute of Thoracic Oncology, West China Hospital, Sichuan University, Chengdu, China.
Senyi DengDepartment of Thoracic Surgery and Institute of Thoracic Oncology, West China Hospital, Sichuan University, Chengdu, China.ORCID https://orcid.org/0000-0002-3278-3375

Funding

National Natural Science Foundation of China 82473155
6 · The paper itself

Abstract

Lung cancer remains one of the leading causes of cancer-related deaths worldwide, underscoring the urgent need for transformative therapeutic strategies. Conventional treatments face critical limitations, including poor targeting efficiency, systemic toxicity, and resistance to targeted therapies. Nanotechnology offers promising solutions by enabling enhanced drug stability, bioavailability, and targeting precision. This review integrates recent advancements in nanotechnology-driven drug delivery systems with a particular focus on computational tools that optimize nanocarrier design. Molecular simulations, quantum mechanics, and AI-driven models have emerged as powerful approaches to streamline development, accelerate innovation, and enable personalized therapies. Clinically, several nanocarrier-based formulations have been associated with favorable therapeutic outcomes in lung cancer patients, including extended progression-free survival and reduced treatment-related toxicity. Despite these advancements, challenges remain in scaling production, ensuring regulatory compliance, and achieving broad clinical adoption. By addressing these barriers through interdisciplinary collaboration, nanotechnology holds the potential to revolutionize lung cancer therapy and set new standards for precision oncology.

Indexed as

Antineoplastic AgentsDrug Delivery SystemsLung NeoplasmsNanotechnologyHumansAntineoplastic Agentscomputational designdrug deliverylung cancermolecular simulationsnanotechnology

Identifiers

PMID40682256
PMCPMC12274165

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.