Evidence map›Paper›PMID 39968009›Full record

ReviewFrontiers in bioengineering and biotechnology2025

Responsive nanomaterials in biomedicine, patent path and prospect analysis.

Xinrui Liu, Hongmei Yuan

Abstract readReview
In one paragraph

Review in Frontiers in bioengineering and biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Article
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

2 authors.

Xinrui LiuSchool of Business Administration, Shenyang Pharmaceutical University, Shenyang, China.
Hongmei YuanSchool of Business Administration, Shenyang Pharmaceutical University, Shenyang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, responsive nanomaterials have demonstrated tremendous potential in biomedical applications due to their unique advantages in precise drug delivery and controlled release. For complex diseases such as cancer, chronic inflammation, and genetic disorders, traditional treatment methods are often limited by insufficient targeting and significant side effects. Responsive nanotechnology, by sensing specific internal or external stimuli, has significantly enhanced the precision and efficiency of treatments. This study systematically summarizes the technological trajectory and emerging research directions of responsive nanomaterials through global patent and literature data, employing main path analysis, derivative path analysis, and keyword co-occurrence analysis. The results reveal the evolution of this field, from the optimization of early single-stimulus-responsive nano delivery systems to the rise of theranostics integration, followed by advancements in multi-stimuli-responsive synergistic therapies, and finally, the innovation in biomimetic material design. Each developmental phase has increasingly focused on adapting to complex biological environments, achieving superior targeting performance, and enhancing therapeutic efficacy. Keyword co-occurrence analysis highlights key research hotspots, including biomimetic design, multimodal synergistic therapies, and emerging response mechanisms. In the future, responsive nanomaterials are expected to play a pivotal role in personalized medicine, multifunctional carrier design, and complex disease management, providing novel insights and technological support for precision medicine.

Indexed as

biomedicinebiomimetic designmultimodal synergistic therapyprecision medicineresponsive nanomaterials

Identifiers

PMID39968009
PMCPMC11832473

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.