Despite huge efforts and investments in biosensor research and development over several decades, and apparently promising developments [1], implantable devices capable of providing long-term (months, years) continuous monitoring of key molecular disease markers remain far from practical implementation. The reasons for this are many-fold, but the most important relate to fundamental materials challenges associated with biocompatibility, and practical barriers related to checking of system integrity [2]. While the management of many chronic health conditions clearly would improve significantly from advances in continuous long-term monitoring, the management of diabetes is most apparent, due to the scale of the problem, and its huge impact on people, society and our health systems [3],[4]. Examples include the Abbott Freestyle Libre (https://www.freestylelibre.ie) and the Dexcom G6 Technologies (http://dexcom.eu/). Pressure to improve the offering from the increasingly IT literate user community is pushing these platforms towards much closer integration with mainstream IOT technologies. For example, tech-savvy parents of children with Type 1 Diabetes have set up their own technology group, and produced their own information management system called Nightscout (http://www.nightscout.info/). This is now driving technology advances in Continuous Glucose Monitoring (CGM), at least on the informatics side (Tagline “#WeAreNotWaiting”!). These disruptive developments are also going to create a major demand for improved sensor performance, which places an increasing focus on how to dramatically extend the functional lifetime of such biosensors, which in turn will drive new thinking around the fundamental materials challenges of long-term on-body/in-body biosensing and controlled therapeutics (in this case insulin delivery) . In this lecture, I will discuss these and related issues, and speculate on strategies for delivering longer-term sensing and control functions based on the inherent behaviour of materials, rather than conventional approaches. References [1] J.Y. Lucisano, T.L. Routh, J.T. Lin, D.A. Gough, Glucose Monitoring in Individuals With Diabetes Using a Long-Term Implanted Sensor/Telemetry System and Model, IEEE Transactions on Biomedical Engineering. 64 (2017) 1982–1993. doi:10.1109/TBME.2016.2619333. [2] S. Coleman, L. Florea, D. Diamond, Chemical Sensing with Autonomous Devices in Remote Locations - Why is it so difficult and how do we deliver revolutionary improvements in performance, Irish Chemical News. (2016) 13–23. [3] C. Chen, X.-L. Zhao, Z.-H. Li, Z.-G. Zhu, S.-H. Qian, A. Flewitt, Current and Emerging Technology for Continuous Glucose Monitoring, Sensors. 17 (2017) 182. doi:10.3390/s17010182. [4] D. Bruen, C. Delaney, L. Florea, D. Diamond, Glucose Sensing for Diabetes Monitoring: Recent Developments, Sensors. 17 (2017) 1866. doi:10.3390/s17081866.