High-sensitivity SPR biosensor for dual detection of glucose and tuberculosis biomarkers with xgboost-assisted predictive modeling

Tuberculosis (TB) and diabetes mellitus are widespread, with chronic hyperglycemia increasing TB susceptibility. Conventional diagnostics — sputum microscopy, culture assays, nucleic acid amplification and blood glucose tests — require laboratory infrastructure, invasive sampling, or long processing times. Surface plasmon resonance (SPR) biosensors offer label-free detection by measuring refractive index changes at a metal-dielectric interface. This study presents a five-layer Kretschmann SPR sensor (BK7 prism/Ag/graphene/WS 2 /biosample) for glucose and TB biomarker detection. Optical behavior was analyzed via the Transfer Matrix Method and finite element simulations in COMSOL Multiphysics, with silver permittivity modeled by Drude–Lorentz and graphene conductivity by Kubo formalism. Layer thicknesses were optimized (Ag: 20–55[Formula: see text]nm, graphene: 0.2–3.0[Formula: see text]nm, WS 2 : 0.3–1.7[Formula: see text]nm), with the configuration 30[Formula: see text]nm Ag, 1.0[Formula: see text]nm graphene and 0.5[Formula: see text]nm WS 2 yielding the strongest resonance (reflectance minimum 0.154%, angular sensitivity [Formula: see text]/RIU, quality factor 460 RIU[Formula: see text]). The sensor exhibited linear resonance shifts with glucose ([Formula: see text], slope 170.4/RIU) and TB biomarkers ([Formula: see text], slope 163.0/RIU). Data from thickness optimization were used to train an XGBoost regression model, predicting Ag-thickness-dependent responses with [Formula: see text] and RMSE [Formula: see text] 0.0125, replicating simulation trends at far lower computational cost. These results demonstrate that the Ag/graphene/WS 2 multilayer enhances SPR sensitivity, providing an efficient platform for label-free, multi-analyte biochemical detection via angular interrogation.