High throughput automation is increasingly essential in structural biology methods, particularly in MicroED, where multiple data sets are often required. Autonomous data collection reduces manual labor, increases instrument usage, and allows larger data sets to be collected in the same timeframe. This is especially important when many data sets must be merged to achieve higher completeness or when crystals are oriented preferentially on the grid. Additionally, studies have shown that automated approaches are effective in analyzing multiple phase systems and distinguishing different crystal forms. For instance, Wang et al. demonstrated the automated analysis of two zeolites using SerialRED for rotation electron diffraction. Smeets et al. used Instamatic to determine two structures from four phases in a multiple phase system. Jones et al. distinguished four natural products from a heterogeneous powder mixture, while Ge et al. identified two different zeoliticimidazolate frameworks from phase mixtures. Broadhurst et al. identified four forms of carbamazepine based on their unit-cell dimensions and processed them to structures of the respective forms. Luo et al. automatically examined hundreds of crystals using SerialRED and identified five similar zeolite phases, and Sasaki et al. found two synthesized phases using SerialEM in diffraction mode, one of which led to a MicroED structure. These studies demonstrate the potential of high throughput automation in collecting and analyzing data in MicroED and other structural biology methods and highlight the ability of automated methods to accelerate the discovery of new crystal forms and improve our understanding of complex material structures.