Matrix materials as functional enablers in metabolite sensing: from mechanistic demands to translational potential

The performance of metabolite sensors is strongly shaped by the physicochemical properties of the matrix that governs analyte transport, interfacial stability, and signal coupling, yet the role of the matrix has largely been overlooked, often being viewed as a passive support rather than an active design parameter. This review analyses how matrix architecture controls sensing behaviour across polymeric, inorganic, carbon-based, and supramolecular material classes, examining mechanistic trade-offs between diffusion and binding, conductivity and biocompatibility, and structural stability and responsiveness in the context of electrochemical, optical, and electrical transduction modes. Particular emphasis is placed on operation in complex biological media, where protein adsorption, ionic fluctuations, mechanical mismatch, and dynamic metabolite flux impose constraints rarely captured in buffered laboratory systems. The comparative analysis reveals that no single matrix class universally optimizes sensitivity, selectivity, and stability; instead, sensor behaviour and performance-relevant characteristics emerge from alignment between the matrix architecture and the signal-generating mechanism. By framing matrix selection through these mechanistic principles, this review provides a foundation for rational matrix design toward continuous, multi-analyte, and clinically deployable metabolite sensors.