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Cited by 648

The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.

Nanoparticles of Metal‐Organic Frameworks: On the Road to In Vivo Efficacy in Biomedicine

Simon‐Yarza, Teresa, Mielcarek, Angelika, Couvreur, Patrick, Serre, Christian·2018·Advanced Materials

Abstract

In the past few years, numerous studies have demonstrated the great potential of nano particles of metal‐organic frameworks (nanoMOFs) at the preclinical level for biomedical applications. Many of them were reported very recently based on their bioactive composition, anticancer application, or from a general drug delivery/theranostic perspective. In this review, the authors aim at providing a global view of the studies that evaluated MOFs' biomedical applications at the preclinical stage, when in vivo tests are described either for pharmacological applications or for toxicity evaluation. The authors first describe the current surface engineering approaches that are crucial to understand the in vivo behavior of the nanoMOFs. Finally, after a detailed and comprehensive analysis of the in vivo studies reported with MOFs so far, and considering the general evolution of the drug delivery science, the authors suggest new directions for future research in the use of nanoMOFs for biomedical applications.

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Metadata

Authors
Simon‐Yarza, T., Mielcarek, A., Couvreur, P., & Serre, C.
Venue
Advanced Materials
Publisher
Wiley
Published
2018-06-06
Volume
30
Issue
37
Pages
e1707365-e1707365
ISSN
  • 0935-9648 (ISSN-L)
  • 1521-4095
OpenAlex
W2805982534
Cited by
648
References
12
FWCI
29.57
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Nanoparticles of Metal‐Organic Frameworks: On the Road to In Vivo Efficacy in Biomedicine. https://app.cochat.ai/papers/10.1002/adma.201707365
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Simon‐Yarza, T., Mielcarek, A., Couvreur, P., & Serre, C. (2018). Nanoparticles of Metal‐Organic Frameworks: On the Road to In Vivo Efficacy in Biomedicine. Advanced Materials. https://doi.org/10.1002/adma.201707365

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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.