To fulfill all of these requirements, we endeavored to establish a platform that calibrates process analytics, collects optimization data in a dynamic flow regime, and parameterizes a process model for scale-up in less than a working day (<8 h, Figure , bottom). This optimization platform has a high degree of automation, but still includes the operator in the loop. The calibration of PAT is performed using a standard addition approach 47 in continuous flow. The standard addition data trains a partial least squares (PLS) regression model. This model is then applied to the collected dynamic data in a broad process space. The processed analytical data is fed with all process inputs into a software program which is coded in Julia. The program is capable of fitting kinetic parameters and creating a process model which can be used for in-silico optimization and scale-up. The developed workflow is showcased with a broad scope of amidation reactions between esters and amines and the two-step synthesis of the API benznidazole (alkylation followed by amidation).