A-399 Analytical performance of enzymatic amperometric glucose and creatinine sensors for the Fluxergy multimodal point-of-care platform

Abstract

Background Point-of-care (POC) metabolic testing requires robust amperometric sensors capable of accurately quantifying clinically relevant analytes across wide concentration ranges while maintaining manufacturability and scalability. Enzymatic amperometric sensing of glucose and creatinine presents challenges related to non-ideal electrode behavior, enzyme kinetics, and matrix effects. This study evaluates the analytical performance of enzymatic glucose and creatinine sensors integrated into a multimodal POC platform with respect to FDA-cleared benchtop reference systems, with an emphasis on calibration, accuracy, and robustness across clinically relevant concentration ranges. Methods Amperometric glucose and creatinine sensors were evaluated using aqueous and biological samples spanning concentrations relevant to intended clinical use (glucose: 20–450 mg/dL; creatinine: 0.3–12 mg/dL). Sensors employed enzyme-based reaction cascades and were tested under controlled assay conditions. Sensor responses were compared against measurements obtained from a Nova Stat Prime Plus reference analyzer. Calibration approaches incorporated data-driven correction methods to account for nonlinear sensor response and electrode-specific variability. Analytical performance was assessed using correlation analysis, bias evaluation, and agreement with established clinical accuracy criteria. Manufacturing reproducibility was evaluated by testing sensors from multiple production batches. Results Both glucose and creatinine sensors demonstrated strong correlation with the reference analyzer across the evaluated concentration ranges in aqueous and biological matrices. Data-driven calibration and correction approaches improved linearity and reduced bias without introducing instability or increased variability. Most tested samples met applicable clinical accuracy expectations (as defined by the 2025 CLIA limits) across the reportable range for both analytes. Sensor performance remained consistent across production batches, indicating acceptable manufacturing reproducibility. Conclusion These results demonstrate that enzymatic amperometric glucose and creatinine sensors can achieve clinically relevant analytical performance on a scalable POC platform when paired with appropriate calibration and correction strategies. The findings support the feasibility of integrating multiple enzymatic assays into a single multimodal POC system and highlight the importance of data-driven approaches for characterizing and mitigating non-ideal electrochemical behavior in practical sensor implementation for diagnostics.