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Cited by 250

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Multiple Polymersomes for Programmed Release of Multiple Components

Kim, Shin-Hyun, Shum, Ho Cheung, Kim, Jin Woong, Cho, Jun-Cheol, Weitz, David A.·2011·Journal of the American Chemical Society

Abstract

Long-term storage and controlled release of multiple components while avoiding cross-contamination have potentially important applications for pharmaceuticals and cosmetics. Polymersomes are very promising delivery vehicles but cannot be used to encapsulate multiple independent components and release them in a controlled manner. Here, we report a microfluidic approach to produce multiple polymersomes, or polymersomes-in-polymersome by design, enabling encapsulation and programmed release of multiple components. Monodisperse polymersomes are prepared from templates of double-emulsion drops, which in turn are injected as the innermost phase to form the second level of double-emulsion drops, producing double polymersomes. Using the same strategy, higher-order polymersomes are also prepared. In addition, incorporation of hydrophobic homopolymer into the different bilayers of the multiple polymersomes enables controlled and sequential dissociation of the different bilayer membranes in a programmed fashion. The high encapsulation efficiency of this microfluidic approach, as well as its programmability and the biocompatibility of the materials used to form the polymersomes, will provide new opportunities for practical delivery systems of multiple components.

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Crossref · 10.1021/ja205687k

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Metadata

Authors
Kim, S.-H., Shum, H. C., Kim, J. W., Cho, J.-C., & Weitz, D. A.
Venue
Journal of the American Chemical Society
Published
2011-08-30
Volume
133
Issue
38
Pages
15165-15171
ISSN
  • 0002-7863 (ISSN-L)
  • 1520-5126
OpenAlex
W2074881900
Cited by
250
References
1
FWCI
11.49
Type
journal article
Language
en
Open access
closed

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.