Peptide-based hydrogels as delivery systems for doxorubicin

Area of Science:

• Biomaterials Science
• Nanotechnology
• Drug Delivery Systems

Background:

• Hydrogels (HGs) and nanogels (NGs) are advanced supramolecular materials with diverse biomedical applications, including tissue engineering and drug delivery.
• Peptides are favored building blocks for HGs and NGs due to their biocompatibility, ease of synthesis, cost-effectiveness, and tunable properties.
• Peptide HGs demonstrate significant potential for delivering various therapeutic agents, preserving their efficacy, preventing degradation, and responding to stimuli.

Purpose of the Study:

• To review the application of peptide-based hydrogels and nanogels as delivery vehicles for the anticancer drug doxorubicin (Dox).
• To explore how these peptide-based supramolecular systems can mitigate the cardiotoxicity associated with doxorubicin therapy.
• To classify doxorubicin-loaded peptide systems based on their constituent peptide sequences.

Main Methods:

• Literature review focusing on peptide-based hydrogels and nanogels for drug delivery.
• Analysis of doxorubicin loading into various supramolecular systems, including liposomes, micelles, hydrogels, and nanogels.
• Classification of peptide-based drug delivery systems according to peptide sequence (short, ultra-short, RGD, RADA).

Main Results:

• Peptide-based hydrogels and nanogels show potential as effective carriers for doxorubicin delivery.
• Loading doxorubicin into supramolecular systems, particularly peptide-based ones, can reduce its associated cardiotoxicity.
• Doxorubicin-loaded peptide systems can be categorized into short/ultra-short peptide HGs, RGD-peptide HGs, RADA-peptide HGs, and peptide-based NGs.

Conclusions:

• Peptide-based hydrogels and nanogels represent a viable strategy for improving doxorubicin delivery in cancer therapy.
• These materials offer a tunable and biocompatible approach to enhance drug efficacy and minimize adverse effects.
• Further research into peptide sequence-based classification can guide the development of optimized doxorubicin delivery vehicles.