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Issue 4, 2017
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Visualization of drug delivery processes using AIEgens

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Drug delivery systems (DDSs) have been extensively studied as carriers to deliver small molecule chemo-drugs to tumors for cancer therapy. The therapeutic efficiency of chemo-drugs is crucially dependent on the effective drug concentrations in tumors and cancer cells. Novel DDSs that can simultaneously unveil drug distribution, drug release/activation behaviors and offer early evaluation of their therapeutic responses are highly desirable. Traditional fluorescent dye-labeled DDSs may suffer from notorious aggregation-caused quenching (ACQ) with limited sensitivity for bioimaging; in addition, the intrinsic fluorescence of these dyes requires careful selection of energy acceptor or quencher moieties for a light-up probe design, which complicates the development of self-reporting DDSs, especially the ones for reporting multiple processes. The recently emerged fluorogens with aggregation-induced emission characteristics (AIEgens) offer a straightforward solution to tackle this challenge. Thanks to the unique properties of AIEgens, new theranostic DDSs have been developed for simultaneous drug delivery and bioimaging with high signal to background ratio and multiple signal reporting capabilities. In this mini-review, we summarize the recent development of theranostic DDSs based on AIEgens for monitoring the drug distribution, drug activation and prediction of the therapeutic responses. Through illustration of their design principles and application examples, we hope to stimulate the interest in the design of more advanced theranostic DDSs for biomedical research.

Graphical abstract: Visualization of drug delivery processes using AIEgens

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Publication details

The article was received on 12 Dec 2016, accepted on 11 Jan 2017, published on 18 Jan 2017 and first published online on 18 Jan 2017

Article type: Perspective
DOI: 10.1039/C6SC05421H
Citation: Chem. Sci., 2017,8, 2537-2546
  • Open access: Creative Commons BY license
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    Visualization of drug delivery processes using AIEgens

    Y. Yuan and B. Liu, Chem. Sci., 2017, 8, 2537
    DOI: 10.1039/C6SC05421H

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