**5. Conclusions**

Droplet microfluidics as a technique for biosensing applications represents an innovative and versatile approach as it offers high throughput, and the possibility to work with a multitude of reagents and samples using very low volumes. This technique also enhances the diffusion and mixing of species and reduces cross-contamination between different confined reactors and experiments. Likewise, droplet microfluidics has been shown for a variety of applications, ranging from the production of micro- and nanomaterials, to the performance of chemical reactions, microbiology and cellular analysis, including steps like sample preconcentration, incubation, mixing, and separation. However, most of these processes have been monitored via optical microscopy. Therefore, in this chapter we have highlighted the possibility to integrate other transducers that on one side enable the further miniaturization of droplet-microfluidic based systems, and on the other side provide new means of characterizing the processes taking place inside such tiny reactors. The range of characteristics and parameters that one can analyze in a sample are broader than just analyzing their morphology, size and color, for instance by determining their capacitance, inductance, magnetoresistance, which provide insights about for example interfacial charges, cell membrane proteins, expressed biomarkers, among others. Here, we also discuss the challenges in doing such an integration as we are talking about a multiphase system, where typically oil and aqueous solutions are employed to produce the droplets. Thus, if such phase change interferes with the active surface of the sensing device, new ways of integration and/or surface treatments or encapsulations should be taken into consideration. Finally, we also mention the requirements and solutions when moving across scales from mili-, to micro and nanofluidics, which would significantly affect the production and treatment of such devices and the further integration and miniaturization of sensors for a determined application. In summary, the combination of droplet microfluidics with different readout techniques would increase the applicability and monitoring efficiency of different chemical and biological processes at different scales. It would also allow multiparametric detection, combining the advantages for instance of electrical sensors with miniaturized optical readouts and new computational tools like machine learning and artificial intelligence which facilitate the interpretation and analysis of the high-dense data set obtained with such kind of platforms.
