To circumvent the challenges of rational design, researchers drew inspiration from bioengineering approaches and developed methods that optimize the screening process. In contrast to synthesis-limited methods, the sensor optimization of such selection-limited approaches proceeds over multiple iterations in which suitable surface modifications are either enriched from a random library or actively modified in an attempt to further improve the sensors (Figure ). We use this terminology and classification to show that they are different in terms of what one could call the rate-determining step. For synthesis-limited high throughput approaches the current bottleneck is the assembly of many different sensors. In screening-based approaches, multiple different sensors are synthesized in one pot and create a pool of sensor candidates. This allows for a much higher number of nanosensors but it also means that one does not know the exact design of the sensors with the highest performance, affinity, etc. Therefore, the rate-limiting step is typically identification/selection and we call it a selection-limited approach. To allow for the identification of the sensors, the surface chemistry of this approach must fulfill synthetic conditions e.g. primers need to be incorporated (see Section 3.2.).