Sensors for monitoring biomolecular dynamics in biological systems and biotechnological processes in real time, need to accurately and precisely reconstruct concentration-time profiles. This requirement becomes challenging when transport processes and biochemical kinetics are important, as is typically the case for biomarkers at low concentrations. Here, we present a comprehensive methodology to study the concentration-time profiles generated by affinity-based sensors that continuously interact with a biological system of interest. Simulations are performed for sensors with diffusion-based sampling (e.g., a sensor patch on the skin) and advection-based sampling (e.g., a sensor connected to a catheter). The simulations clarify how transport processes and molecular binding kinetics result in concentration gradients and time delays in the sensor system. Using these simulations, measured and true concentration-time profiles of insulin were compared as a function of sensor design parameters. The results lead to guidelines on how biomolecular monitoring sensors can be designed for optimal bioanalytical performance in terms of concentration and time properties.
Keywords: affinity kinetics; biomolecules; concentration change; lag time; monitoring; sensing; sensor performance.