Diabetes management requires accurate, continuous monitoring of glucose levels to reduce complications and improve clinical outcomes. Conventional finger‐prick methods are invasive and fail to capture dynamic glycemic fluctuations. Continuous glucose monitoring (CGM) biosensors have emerged as a transformative solution, enabling real‐time, minimally or noninvasive glucose tracking with improved patient compliance. The literature was systematically searched across PubMed, Scopus, and Google Scholar, emphasizing recent innovations, fabrication strategies, and clinical applicability. Findings highlight future prospects of CGM biosensors in advancing diabetes care. This review provides a critical synthesis of recent advances in CGM technologies, with a particular focus on sensor transduction mechanisms, algorithm‐driven data interpretation, and the transition toward hybrid closed‐loop (artificial pancreas) systems . We compare invasive, minimally invasive, and noninvasive platforms, highlighting their relative performance, clinical maturity, and translational potential. Clinical evidence indicates that CGM use is associated with reductions in HbA1c of ∼0.5%–1.0%, decreased hypoglycemic events, and improved time‐in‐range, while emerging predictive algorithms enable glucose forecasting within 15–30 min, supporting proactive therapeutic decisions. Advances in electrochemical and optical biosensors, smart coatings, and wearable integration have significantly enhanced accuracy, stability, and biocompatibility. A key insight of this review is that no single sensing modality currently achieves the ideal balance of accuracy, stability, and noninvasiveness; instead, progress lies in the convergence of multimodal sensing, improved calibration algorithms, and seamless integration with insulin delivery systems. Emerging technologies including optical spectroscopy, bioimpedance, and electromagnetic sensing show promise but remain limited by signal variability and the need for robust real‐time data correction. The major challenges remain in calibration, signal drift, and reliability of noninvasive systems. Overall, this review identifies algorithm sensor integration and noninvasive sensing technologies as key drivers in the evolution toward fully autonomous closed‐loop diabetes management, offering a roadmap for next‐generation CGM development and precision diabetes car.
B. Rajgopal (Fri,) studied this question.