The development of fast and mobile drug detection is an important aspect of personalized medicine. It enables the quick assessment of inter-individual differences in drug metabolism and corresponding adjustments of the dose. Recent developments of amperometric biosensors using cytochrome P450 (CYP) show great promise, by lowering the detection limit to physiological range for several drugs via the usage of Multi Walled Carbon Nanotubes (MWCNT). The next challenge is to develop algorithms for processing the resulting sensor data compatible with low-power hardware, which would allow the development of portable battery-powered devices. In this work we pursue a novel approach to this problem. Here we provide a proof of principle by demonstrating how sensor data could be analyzed using a conventional multi-layer perceptron network with error-backpropagation.

A full remotely powered system for metabolism monitoring of free-moving mice is presented here. The fully implantable sensing platform hosts two ASICs, one off-the-shelf micro-controller, four biosensors, two other sensors, a coil to receive power, and an antenna to transmit data. Proper enzymes ensure specificity for animal metabolites while Multi-Walled Carbon Nanotubes ensure the due sensitivity. The remote powering is indeed provided by inductive coils located under the floor of the mouse' cage. Two different approaches where investigated to ensure freedom of movement to the animal. The application to studies for personalized medicine is demonstrated by showing continuous monitoring of both glucose and paracetamol.

Biosensors are heterogenous devices, incorporating biological structures combined with electronics, optical or other readout systems. They have been developed for detecting different biomolecules and/or pathogens and represent a key technology for advanced and point-of-care diagnostics as well as patient monitoring. In this paper we present a systematic classification of biosensors described in literature, particularly focusing on nanotechnology-based sensing. Then, we present our approach to develop electrochemical biosensors for measuring metabolites and anticancer drugs, based on a platform for multiple target detection. This platform is modular and achieves a clear separation between the chemical and the electrical components, thus easing design and manufacturing. It shows superior performance thanks to the excellent properties of electron transfer and selectivity showed by enzymes immobilized on carbon nanotubes.