There is a need for sensing technologies that can continuously monitor concentration levels of critical biomolecules in applications such as patient care, fundamental biological research, biotechnology and food industry, as well as the environment. However, it is fundamentally difficult to develop measurement technologies that are not only sensitive and specific, but also allow monitoring over a broad concentration range and over long timespans. Here we describe a continuous biomolecular sensing methodology based on the free diffusion of biofunctionalized particles hovering over a sensor surface. The method records digital events due to single-molecule interactions and enables biomarker monitoring at picomolar to micromolar concentrations without consuming any reagents. We demonstrate the affinity-based sensing methodology for DNA-based sandwich and competition assays, and for an antibody-based cortisol assay. Additionally, the sensor can be dried, facilitating storage over weeks while maintaining its sensitivity. We foresee that this will enable the development of continuous monitoring sensors for applications in fundamental research, for studies on organs on a chip, for the monitoring of patients in critical care, and for the monitoring of industrial processes and bioreactors as well as ecological systems.

The ability to continuously measure concentrations of small molecules is important for biomedical, environmental and industrial monitoring. However, due to their low molecular mass it is difficult to quantify concentrations of such molecules, particularly at low concentrations. Here we describe a small-molecule sensor that is generalizable, sensitive, specific, reversible, and suited for continuous monitoring over long durations. The sensor consists of particles attached to a sensing surface via a double stranded DNA tether. The particles transiently bind to the sensing surface via single molecular affinity interactions and the transient binding is optically detected as digital binding events via the Brownian motion of the particles. The rate of binding events decreases with increasing analyte concentration, because analyte molecules inhibit binding of the tethered particle to the surface. The sensor enables continuous measurements of analyte concentrations due to the reversibility of the inter-molecular bonds and digital read-out of particle motion. We show results for the monitoring of short single-stranded DNA sequences and creatinine, a small-molecule biomarker (113 Da) for kidney function, demonstrating a temporal resolution of a few minutes. The precision of the sensor is determined by the statistics of the digital switching events, which means that the precision is tunable by the number of particles and the measurement time.

Cortisol is a steroid hormone involved in a wide range of medical conditions. The level of the hormone fluctuates over time, but with traditional laboratory-based assays, such dynamics cannot be monitored in real time. Here, a reversible cortisol sensor is reported that allows continuous monitoring of cortisol in blood plasma using sampling by microdialysis. The sensor is based on measuring single-molecule binding and unbinding events of tethered particles. The particles are functionalized with antibodies and the substrate with cortisol-analogues, causing binding and unbinding events to occur between particles and substrate. The frequency of binding events is reduced when cortisol is present in the solution as it blocks the binding sites of the antibodies. The sensor responds to cortisol in the high nanomolar to low micromolar range and can monitor cortisol concentrations over multiple hours. Results are shown for cortisol monitoring in filtered and in microdialysis-sampled human blood plasma.

A time-dependent electrochemical impedance spectroscopy (EIS) model is presented using the finite element method (FEM) to simulate a 2D interdigitated electrode in an aqueous NaCl electrolyte. Developed in COMSOL Multiphysics, the model incorporates ion transport, electric field distribution, Stern layer effects, and electrode sheet resistance, governed by the Poisson and Nernst–Planck equations. This model can predict the transient current response to an applied excitation voltage, which gives information about the dynamics of the electrochemical system. The simulation results are compared with the experimental data, reproducing key features of the measurements. The transient current response indicates the need for multiple excitation cycles to stabilize the impedance measurement. At low frequencies (100 kHz), the voltage drop due to sheet resistance dominates. Moreover, the amplitude of the excitation voltage influences the EIS measurement, higher amplitudes (above 0.1 V) lead to non-linear impedance behavior, particularly at low ion concentrations. Discrepancies at low frequencies suggest that Faradaic processes may need to be incorporated for improved accuracy. Overall, this model provides quantitative insights for optimizing EIS sensor design and highlights critical factors for high-frequency and low-concentration conditions, laying the foundation for future biosensing applications with functionalized electrodes.

The integration of microdialysis with a continuous biosensor was studied to realize a continuous sampling-and-sensing methodology with minimal time delay.