Evidence map›Paper›PMID 42360296›Full record

ReviewSmall (Weinheim an der Bergstrasse, Germany)2026

Advances in Nanoarchitectural Designs for Anticancer Drug Delivery to Deep Tumors.

Ranjith Kumar Kankala, Ai-Zheng Chen, Philipp Kapranov

Abstract readReview
In one paragraph

Review in Small (Weinheim an der Bergstrasse, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Ranjith Kumar KankalaInstitute of Biomaterials and Tissue Engineering, Huaqiao University, Xiamen, P. R. China.ORCID 0000-0003-4081-9179
Ai-Zheng ChenInstitute of Biomaterials and Tissue Engineering, Huaqiao University, Xiamen, P. R. China.ORCID 0000-0002-5840-3406
Philipp KapranovState Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China.ORCID 0000-0003-2647-4856

Funding

National Natural Science Foundation of China 32071323National Natural Science Foundation of China 32170619National Natural Science Foundation of China 32271410National Natural Science Foundation of China 32471417Natural Science Foundation of Fujian Province 2026J01111542
6 · The paper itself

Abstract

Extensive progress in the design of drug delivery systems based on advanced materials offers new and exciting opportunities in the fight against cancer. However, multiple challenges remain to be addressed before this approach can find a widespread application in clinics. Here, we provide a comprehensive overview of various innovative nanoparticle design strategies, including ultrasmall-size, size-shrinkable and multi-stage degradable nanoparticles, anisotropic particles with irregular dimensions, electrostatically-driven charge-reversal nanoparticles, and bioinspired carriers. We also discuss in detail the process of infiltration and various challenges faced by the nanoparticle-based delivery systems and highlight the roles of various factors (size, shape, chemistry, and surface charge) affecting tumor penetration by nanoparticles. In addition, the crucial roles of tumor size and metastatic stage in influencing the therapeutic efficacy of nanoparticles are highlighted. Finally, we discuss emerging highly advanced intelligent drug delivery platforms based on nanorobotics/nanomotors and immunotherapeutic activation.

Indexed as

Antineoplastic AgentsDrug Delivery SystemsNanoparticlesNeoplasmsAnimalsDrug CarriersHumansAntineoplastic AgentsDrug Carriersadvanced materialsanticancer therapydrug deliverynanoarchitecturesnanoparticles

Identifiers

PMID42360296
PMCPMC13450329

What OpenQuestion holds

Textmetadata
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.