Evidence map›Paper›PMID 33809633›Full record

ReviewNanomaterials (Basel, Switzerland)2021

Nanoplatforms for Targeted Stimuli-Responsive Drug Delivery: A Review of Platform Materials and Stimuli-Responsive Release and Targeting Mechanisms.

Yuzhe Sun, Edward Davis

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Nanomaterials (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing 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

42 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

2 authors.

Yuzhe SunMaterials Engineering Program, Mechanical Engineering Department, Auburn University, 101 Wilmore Drive, Auburn, AL 36830, USA.ORCID 0000-0002-2572-2339
Edward DavisMaterials Engineering Program, Mechanical Engineering Department, Auburn University, 101 Wilmore Drive, Auburn, AL 36830, USA.ORCID 0000-0001-5413-5398

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To achieve the promise of stimuli-responsive drug delivery systems for the treatment of cancer, they should (1) avoid premature clearance; (2) accumulate in tumors and undergo endocytosis by cancer cells; and (3) exhibit appropriate stimuli-responsive release of the payload. It is challenging to address all of these requirements simultaneously. However, the numerous proof-of-concept studies addressing one or more of these requirements reported every year have dramatically expanded the toolbox available for the design of drug delivery systems. This review highlights recent advances in the targeting and stimuli-responsiveness of drug delivery systems. It begins with a discussion of nanocarrier types and an overview of the factors influencing nanocarrier biodistribution. On-demand release strategies and their application to each type of nanocarrier are reviewed, including both endogenous and exogenous stimuli. Recent developments in stimuli-responsive targeting strategies are also discussed. The remaining challenges and prospective solutions in the field are discussed throughout the review, which is intended to assist researchers in overcoming interdisciplinary knowledge barriers and increase the speed of development. This review presents a nanocarrier-based drug delivery systems toolbox that enables the application of techniques across platforms and inspires researchers with interdisciplinary information to boost the development of multifunctional therapeutic nanoplatforms for cancer therapy.

Indexed as

drug deliverydrug targetingendogenous stimuliexogenous stimulinanoparticlesrelease stimuli

Identifiers

PMID33809633
PMCPMC8000772

What OpenQuestion holds

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LicenceCC BY
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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.