Micro- and nano- droplets and particles find diverse applications in fields such as biology, biotechnology, and pharmaceuticals. They can be fabricated using a variety of materials, both organic and inorganic, and employing various techniques (see, e.g., the review paper by Liu et al., 2020). In particular, these particles are utilized for drug delivery, enabling the transport of Active Pharmaceutical Ingredients (APIs) within the human body. Achieving precise control over the shape, composition, and size of nanoparticles is crucial for such applications. Recent advances in microfluidics have played a key role in ensuring an accurate control of particle quality and many device geometries have been proposed in the literature to achieve well-controlled droplet generation, including the T- and X-shaped junctions used, e.g., for hydrodynamic flow focusing or co-axial injection. In this study, we explore the capabilities of numerical simulations for the computation of droplet and particle formation in microfluidic devices, drawing comparisons with experimental results. Specifically, we employ an X-junction to generate (i) alginate droplets using the segmented dispersed phase method and (ii) chitosan nanoparticles via the solvent displacement method. Numerical simulations of these phenomena pose significant challenges. Concerning sodium alginate droplets, a sensitivity analysis to the contact angle between the two phases and surface tension is conducted in numerical simulations, and the results are compared with experimental data. Subsequently, a systematic examination of flow behavior, droplet diameter, and pinching efficiency is conducted by varying the flow rates both in experiments and simulations. In producing chitosan nanoparticles, we experimentally and numerically investigate how the concentration of chitosan influences the fluid dynamics within the device and, consequently, how different flow regimes impact particle size and size distribution. For instance, the potential presence of vortical structures increases both the particles' size and polydispersity index.