One example is the automated coaxial jet mixer setup developed by Bovone et al., which can operate continuously without human intervention for up to 24 hours . In this case, the microfluidic process was programmed through a LabView user interface to modulate operating conditions and control syringe pumps. By increasing the concentration of block copolymer and the ratio of organic to aqueous solutions, polymeric NPs were produced with consistent size and a narrow size distribution (PDI < 0.2). Further, the production rate with automation was significantly greater than standard batch preparation . Similarly, Loy et al. demonstrated that an automated microfluidic platform can be economical while producing polymeric NPs with less variability in their physicochemical properties compared to manual preparation methods . Their inexpensive prototype consisted of commercially available syringe pumps and a fraction collector connected to a computer module controlled by open-source code. The modular design of the system allows for future improvements, such as swapping components for more efficient ones to boost scalability . These examples illustrate how automation can be introduced into a formulation strategy to endow more experimental flexibility, increase throughput, and reduce batch variability. As such, automation can contribute significantly to the systematic investigation of formulations with more refined screening and selection. Ultimately, the concept that "automation isn't automatic" is an important reminder for the future adoption of automated systems, as they progress iteratively through incremental improvements and continuous evaluation. In this process, the data generated through automated methods can be orders of magnitude larger, more accurate and reproducible than that produced by human researchers. This lays the foundation for more sophisticated computational analyses that can improve formulation development.