A comprehensive review of metal-organic framework based biosensors for detection of reactive oxygen species and hydrogen peroxide in biomedical applications
Year: 2025
Type: article
Abstract: Metal-organic frameworks (MOFs) have emerged as revolutionary materials for developing advanced biosensors, especially for detecting reactive oxygen species (ROS) and hydrogen peroxide (H₂O₂) in biomedical applications. This comprehensive review explores the current state-of-the-art in MOF-based biosensors, covering fundamental principles, design strategies, performance features, and clinical uses. MOFs offer unique benefits, including exceptional porosity (up to 10,400 m²/g), tunable structures, biocompatibility, and natural enzyme-mimicking properties, making them ideal platforms for sensitive and selective detection of ROS and H₂O₂. Recent advances have shown significant improvements in detection capabilities, with limits as low as 0.357 nM for H₂O₂ detection using ZIF-8-based SERS sensors and picomolar sensitivity for various ROS species. The review systematically examines different MOF structures, including pure MOFs, bimetallic systems, and composite materials, emphasizing their mechanisms through electrochemical, optical, and colorimetric methods. Key biomedical applications include cancer diagnosis, cardiovascular disease monitoring, inflammatory condition assessment, and point-of-care testing. Despite notable progress, challenges such as stability under physiological conditions, biocompatibility, manufacturing reproducibility, and regulatory approval remain for clinical translation. Future directions include developing AI-integrated systems, wearable devices, and theranostic platforms that combine sensing with therapeutic functions.
Authors: Ibadi, Ihsan, Faraj, Russol Abdul Salam, Jamur, Jasim M. S., Vahdatkhah, Arash
Institutions: Al-Kunooze University, University of Baghdad, University of Tabriz
Language: English
Subfield: Inorganic Chemistry
Field: Chemistry
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7101404471
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