Automation Technologies to Enable Data-Rich Experimentation: Beyond Design of Experiments for Process Modeling in Late-Stage Process Development

Automated reactor and sampling technologies were used in process characterization studies of a cyclization reaction using gaseous ammonia. These data-rich experiments were structured according to a 24 full factorial design of experiment, with each experiment having 12 reaction samples at equal time intervals. Data-driven models were established for key reaction responses to create a process fingerprint, to identify the optimal operating conditions under various constraints, and to evaluate the stability of the process. Leveraging these technologies in late-stage reaction characterization enabled significant improvements in efficiency and experimental reproducibility compared to conventional methods.