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Cited by 369

The DOI matches its Crossref record; 445 of the 445 references it cites were found in a registry or an index.

Recent trends in protein and peptide-based biomaterials for advanced drug delivery

Open access
Varanko, Anastasia, Saha, Soumen, Chilkoti, Ashutosh·2020·Advanced Drug Delivery Reviews

Abstract

Engineering protein and peptide-based materials for drug delivery applications has gained momentum due to their biochemical and biophysical properties over synthetic materials, including biocompatibility, ease of synthesis and purification, tunability, scalability, and lack of toxicity. These biomolecules have been used to develop a host of drug delivery platforms, such as peptide- and protein-drug conjugates, injectable particles, and drug depots to deliver small molecule drugs, therapeutic proteins, and nucleic acids. In this review, we discuss progress in engineering the architecture and biological functions of peptide-based biomaterials —naturally derived, chemically synthesized and recombinant— with a focus on the molecular features that modulate their structure-function relationships for drug delivery.

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Crossref · 10.1016/j.addr.2020.08.008

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Metadata

Authors
Varanko, A., Saha, S., & Chilkoti, A.
Venue
Advanced Drug Delivery Reviews
Publisher
Elsevier BV
Published
2020
Volume
156
Pages
133-187
ISSN
0169-409X (ISSN-L)
OpenAlex
W3082953595
Cited by
369
References
445
FWCI
5.86
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Recent trends in protein and peptide-based biomaterials for advanced drug delivery. https://app.cochat.ai/papers/10.1016/j.addr.2020.08.008
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Varanko, A., Saha, S., & Chilkoti, A. (2020). Recent trends in protein and peptide-based biomaterials for advanced drug delivery. Advanced Drug Delivery Reviews. https://doi.org/10.1016/j.addr.2020.08.008

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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.