Evidence map›Paper›PMID 25780923›Full record

ArticlePloS one2015

Quantitative structure-property relationship (QSPR) modeling of drug-loaded polymeric micelles via genetic function approximation.

Wensheng Wu, Canyang Zhang, Wenjing Lin, Quan Chen, Xindong Guo, Yu Qian, Lijuan Zhang

Abstract readValidation Study
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 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

7 authors.

Wensheng WuSchool of Chemistry and Chemical Engineering, South China University of Technology, Guangzhou, P. R. China; School of Chemistry and Chemical Engineering, Zhaoqing University, Zhaoqing, P. R. China.
Canyang ZhangSchool of Chemistry and Chemical Engineering, South China University of Technology, Guangzhou, P. R. China.
Wenjing LinSchool of Chemistry and Chemical Engineering, South China University of Technology, Guangzhou, P. R. China.
Quan ChenSchool of Chemistry and Chemical Engineering, South China University of Technology, Guangzhou, P. R. China.
Xindong GuoSchool of Chemistry and Chemical Engineering, South China University of Technology, Guangzhou, P. R. China.
Yu QianSchool of Chemistry and Chemical Engineering, South China University of Technology, Guangzhou, P. R. China.
Lijuan ZhangSchool of Chemistry and Chemical Engineering, South China University of Technology, Guangzhou, P. R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Self-assembled nano-micelles of amphiphilic polymers represent a novel anticancer drug delivery system. However, their full clinical utilization remains challenging because the quantitative structure-property relationship (QSPR) between the polymer structure and the efficacy of micelles as a drug carrier is poorly understood. Here, we developed a series of QSPR models to account for the drug loading capacity of polymeric micelles using the genetic function approximation (GFA) algorithm. These models were further evaluated by internal and external validation and a Y-randomization test in terms of stability and generalization, yielding an optimization model that is applicable to an expanded materials regime. As confirmed by experimental data, the relationship between microstructure and drug loading capacity can be well-simulated, suggesting that our models are readily applicable to the quantitative evaluation of the drug-loading capacity of polymeric micelles. Our work may offer a pathway to the design of formulation experiments.

Indexed as

Quantitative Structure-Activity RelationshipAlgorithmsAntineoplastic AgentsDrug CarriersMicellesAntineoplastic AgentsDrug CarriersMicelles

Identifiers

PMID25780923
PMCPMC4364361

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Registered trials

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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.