Graphene-Plasmonic Nanoparticle Hybrid Sensor Platforms for Vitamin D Detection

Accurate quantification of serum 25-hydroxyvitamin D [25(OH)D], the principal biomarker of vitamin D status, is essential to prevent deficiency and supplementation-induced toxicity. Despite widespread clinical use, immunoassays and LC-MS/MS remain centralised and instrumentation-intensive, limiting scalable point-of-care deployment. Clinically meaningful assessment requires reliable measurement across the 10-150 ng/mL range in protein-rich serum, where 25(OH)D is predominantly vitamin D-binding protein (VDBP)-bound and intrinsically electrochemically and optically inert. These constraints sustain a translational gap between analytical sensitivity and deployable testing. Although biosensor platforms have emerged as alternatives, many prioritise ultra-low limits of detection without equivalent consideration of matrix tolerance, calibration robustness, or fabrication reproducibility. Graphene enhances surface accessibility and charge transport, while plasmonic nanostructures amplify local electromagnetic fields. In hybrid architectures, this mechanistic synergy enables coupled electron-transfer modulation and plasmon-enhanced signal amplification, addressing core limitations of small-molecule detection. This review synthesises graphene, plasmonic, and graphene-plasmonic platforms for 25(OH)D sensing, emphasising interfacial mechanisms, functionalisation strategies, analytical performance relative to clinical thresholds, and translational feasibility. Key challenges in matrix resilience, reproducibility, and reference-method benchmarking are delineated to establish design criteria for clinically deployable vitamin D diagnostics. • Graphene-plasmonic hybrids enable ultrasensitive vitamin D₃ biosensing • Charge and field coupling amplify electrochemical and optical responses • Aptamer-nanohybrid interfaces achieve selective 25(OH)D₃ recognition • Simulation-guided co-design improves reproducibility and scalability • Review outlines translational path for hybrid nanobiosensor deployment