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Published on: September 20, 2011
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Nanoscale coordination polymers: synthesis, characterization, and emerging biomedical applications.
1Department of Chemistry, JIS University, Kolkata, India.
Journal of Biomaterials Science. Polymer Edition
|February 23, 2026
Summary
Nanoscale coordination polymers (NCPs) offer tunable properties for advanced theranostics and imaging. Recent progress in synthesis and engineering highlights their potential in drug delivery and therapy, despite challenges in clinical translation.
Area of Science:
- Materials Science
- Nanotechnology
- Biomedical Engineering
Background:
- Nanoscale coordination polymers (NCPs), including nanoMOFs and amorphous nanoparticles, are versatile hybrid materials.
- Their tunable composition, porosity, and surface properties enable precise control over drug delivery and biological interactions.
- NCPs show significant promise for theranostics, imaging, and therapeutic applications.
Purpose of the Study:
- To review recent advancements in the synthesis and nanoscale engineering of NCPs.
- To highlight structure-property relationships crucial for biomedical performance.
- To examine the growing applications and future directions of NCPs in medicine.
Main Methods:
- Literature review of recent advancements in NCP synthesis and engineering.
- Analysis of structure-property relationships impacting biomedical applications.
- Incorporation of quantitative benchmarks from existing studies.
Main Results:
- NCPs demonstrate superior drug loading (e.g., ZIF-8 up to 70-80 wt%) and enhanced relaxivity (Gd-NCPs 25-30 mM⁻¹s⁻¹) compared to conventional materials.
- Characterization methods link material properties to biological functions effectively.
- NCPs show broad applications in drug delivery, biosensing, imaging, and antimicrobial/antiviral therapies.
Conclusions:
- NCPs are highly adaptable platforms for theranostics and drug delivery.
- Further research is needed to address challenges like biodegradation, toxicity, and clinical translation.
- Computational design and AI offer promising avenues for future NCP development.

