Enabling technologies for neural and biofluid interfaces: biocompatible materials with potential for neurodegenerative disease applications

As global populations age, neurodegenerative diseases impose escalating clinical and economic burdens on healthcare systems worldwide. While gold-standard diagnostics—positron emission tomography, magnetic resonance imaging, and cerebrospinal fluid assays—provide exceptional accuracy, they remain costly, invasive, and temporally limited in their monitoring capabilities. Wearable and minimally invasive biosensors emerge as complementary diagnostic modalities, offering unprecedented opportunities for earlier detection and continuous longitudinal monitoring. However, deployment in older adults presents significant challenges due to compromised skin integrity and diminished tissue resilience, necessitating optimized sensor-tissue interfaces that account for age-related physiological changes. This comprehensive review synthesizes recent advances across multiple biomaterial domains: soft elastomers and hydrogels that conform to aging tissue mechanics; sophisticated bioadhesive and antifouling coatings that maintain long-term stability; and innovative brain-based neural interfaces, skin-based biofluid sensors, and ocular implantable platforms enabling stable, low-irritation continuous monitoring. We systematically evaluate sensing modalities organized by anatomical location—brain, skin, and eye—analyzing their fundamental capabilities, usability in geriatric populations, and biomarker coverage potential. While these technologies demonstrate promising electrophysiology recording, neurochemical detection, and biofluid sampling capabilities essential for neurodegenerative disease monitoring, translation to clinical applications requires integration of disease-specific biomarker detection, rigorous validation in appropriate disease models, and demonstration of long-term stability under pathological conditions. This review provides a critical assessment of current capabilities and limitations, offering a roadmap toward clinically actionable diagnostic systems.