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Cited by 274

The DOI matches its Crossref record; 90 of the 90 references it cites were found in a registry or an index.

Growth Factor Delivery Approaches in Hydrogels

Silva, Amanda K. Andriola, Richard, Cyrille, Bessodes, Michel, Scherman, Daniel, Merten, Otto-Wilhelm·2009·Biomacromolecules

Abstract

The controlled delivery of growth factors is a very challenging task because many different issues have to be addressed to develop the best suited system. A wide range of approaches have been employed for the controlled delivery of growth factors by hydrogels. Direct loading, electrostatic interaction, covalent binding, and the use of carriers are the main strategies presented in the literature. They are all detailed in the first part of this review. Recent work emphasizing biologically inspired strategies is also included. Also, both natural and synthetic materials are discussed. The second part comprises the methods to evaluate such delivery approaches. Both in vivo and in vitro techniques are presented. Improvements based on the discussed approaches may illustrate future paths toward the development of an ideal growth factor delivery system.

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Crossref · 10.1021/bm801103c

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Metadata

Authors
Silva, A. K. A., Richard, C., Bessodes, M., Scherman, D., & Merten, O.-W.
Venue
Biomacromolecules
Published
2008-11-26
Volume
10
Issue
1
Pages
9-18
ISSN
  • 1525-7797 (ISSN-L)
  • 1526-4602
OpenAlex
W2043744566
Cited by
274
References
90
FWCI
6.84
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Growth Factor Delivery Approaches in Hydrogels. https://app.cochat.ai/papers/10.1021/bm801103c
The paper
Silva, A. K. A., Richard, C., Bessodes, M., Scherman, D., & Merten, O.-W. (2009). Growth Factor Delivery Approaches in Hydrogels. Biomacromolecules. https://doi.org/10.1021/bm801103c

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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.