In traditional process development, reaction models are built mainly using data from offline analysis (Figure , top). This workflow includes the initial reaction screening and feasibility study, reaction optimization and the reaction model development. In parallel to (or even after) the reaction development, a PAT and control strategy is often developed to control critical quality attributes (CQAs) in the final process. This encompasses the feasibility and implementation of PAT within the process, calibration of the process analytics, and the real-time processing of raw data into meaningful information (e.g., species concentrations and performance metrics). Multiple scientists with individual expertise will work on both workflows to combine them into a final process model. The digitalization of chemical development work provides opportunities to automate parts of the aforementioned workflows. This ultimately will save resources and accelerate the development of processes.