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Design and fabrication of magnetic nanoparticles for targeted drug delivery and imaging

Open access
Veiseh, Omid, Gunn, Jonathan W., Zhang, Miqin·2010·Advanced Drug Delivery Reviews

Abstract

Magnetic nanoparticles (MNPs) represent a class of non-invasive imaging agents that have been developed for magnetic resonance (MR) imaging. These MNPs have traditionally been used for disease imaging via passive targeting, but recent advances have opened the door to cellular-specific targeting, drug delivery, and multi-modal imaging by these nanoparticles. As more elaborate MNPs are envisioned, adherence to proper design criteria (e.g. size, coating, molecular functionalization) becomes even more essential. This review summarizes the design parameters that affect MNP performance in vivo, including the physicochemical properties and nanoparticle surface modifications, such as MNP coating and targeting ligand functionalizations that can enhance MNP management of biological barriers. A careful review of the chemistries used to modify the surfaces of MNPs is also given, with attention paid to optimizing the activity of bound ligands while maintaining favorable physicochemical properties.

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Crossref · 10.1016/j.addr.2009.11.002

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Metadata

Authors
Veiseh, O., Gunn, J. W., & Zhang, M.
Venue
Advanced Drug Delivery Reviews
Publisher
Elsevier BV
Published
2010-03
Volume
62
Issue
3
Pages
284-304
ISSN
0169-409X (ISSN-L)
OpenAlex
W1980122435
Cited by
1,832
References
20
FWCI
3.14
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Design and fabrication of magnetic nanoparticles for targeted drug delivery and imaging. https://app.cochat.ai/papers/10.1016/j.addr.2009.11.002
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Veiseh, O., Gunn, J. W., & Zhang, M. (2010). Design and fabrication of magnetic nanoparticles for targeted drug delivery and imaging. Advanced Drug Delivery Reviews. https://doi.org/10.1016/j.addr.2009.11.002

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

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