A 24‐Day MicroCycle Journey to Interleukin‐17 Inhibitors: From Library Design to Central Core Prioritization and Capping Group Identification

We herein report an application of the MicroCycle platform, which leverages advanced machine learning models, automation, and miniaturization of processes to accelerate the exploration of chemical space through libraries. This approach was applied to a novel thiazole-based series targeting interleukin-17, enabling rapid prioritization of central cores and identification of compelling new capping groups, thereby guiding further optimization efforts.