Molecularly imprinted polymer technology for electrochemical detection of diabetes-related biomarkers - Launa Silky Karenindra Rokhmat; Irkham; Serly Zuliska; Adisyahputra; Yohanes Susanto Ridwan; Retna Putri Fauzia; Putra Rafli Ramdani; Yeni Wahyuni Hartati (Sensors and Actuators Reports)
Delayed treatment of diabetes mellitus (DM) can result in severe complications, including cardiovascular disease, neuropathy, and kidney failure, emphasizing the critical importance of early and accurate detection. Key biomarkers for DM diagnosis and monitoring include glucose, insulin, glycated hemoglobin (HbA1c), and glycated albumin (GHSA), which are typically measured using techniques like chromatography, electrophoresis, and immunoassays. While these methods offer high accuracy and reliability, their application is often limited by the need for sophisticated instrumentation, high operational costs, and lengthy analysis times, making them less suitable for point-of-care diagnostics. As an alternative, Molecularly Imprinted Polymers (MIPs) have emerged as a promising solution due to their exceptional specificity in biomarker recognition, mimicking the selective binding properties of natural antibodies. MIPs-based electrochemical sensors offer significant advantages, including high stability, selectivity, reproducibility, and cost-effectiveness, making them highly suitable for rapid and portable biomarker detection. This review provides a comprehensive overview of recent advances in MIPs-based electrochemical sensors for DM biomarker detection, emphasizing various synthesis strategies, including bulk polymerization, surface polymerization, electropolymerization, and cooling polymerization. Furthermore, key factors influencing sensor performance, such as functional monomers, crosslinkers, and initiators, are discussed. The continued development of MIPs-based electrochemical sensors holds great potential for enhancing the accessibility and efficiency of DM biomarker detection, with ongoing research paving the way for their integration into point-of-care diagnostic platforms.