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Injectable Supramolecular Polymer-Nanoparticle Hydrogels for Cell and Drug Delivery Applications
Published on: February 7, 2021
Tailored injectable nanocomposite hydrogels for high-performance biomedical applications
Garima Rathee1,2, Nitesh Kumar Singh3, Sahil Kohli4
1Department of Chemical Engineering, Universitat Politècnica de Catalunya, 08222 Terrassa, Spain. garima.rathee@upc.edu.
Injectable nanocomposite (NC) hydrogels enhance mechanical properties and therapeutic delivery for precision medicine. This review details their advantages, clinical translation, and future potential with AI.
Area of Science:
- Biomaterials Science
- Nanotechnology
- Polymer Chemistry
Background:
- Conventional hydrogels lack mechanical strength and precise therapeutic control, limiting precision medicine applications.
- Engineered nanomaterials integrated into hydrogels offer enhanced functionality and stimuli-responsiveness.
- Nanocomposite (NC) hydrogels represent a significant advancement over traditional polymer networks.
Purpose of the Study:
- To provide a mechanistic and translational analysis of injectable NC hydrogels.
- To evaluate the advantages of NC hydrogels over conventional dynamic hydrogels.
- To assess clinical translation pathways, challenges, and future directions for NC hydrogels.
Main Methods:
- Systematic review of nanoparticle-polymer interfacial interactions governing NC hydrogel properties.
- Analysis of nanomaterial incorporation (metal, carbon, lipid, black phosphorus) in biomedical applications.
- Evaluation of clinical trial data, regulatory hurdles, and manufacturing scalability.
Main Results:
- NC hydrogels exhibit hierarchical drug release, improved tumor penetration, and multiscale responsiveness.
- Key applications include advanced drug delivery, tissue engineering, wound healing, and biosensing.
- AI and machine learning tools show promise for accelerated design and therapeutic monitoring.
Conclusions:
- Injectable NC hydrogels offer superior performance for precision medicine applications.
- Addressing clinical translation barriers is crucial for realizing their full potential.
- Future research should focus on AI-driven design and real-time monitoring for next-generation therapies.
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