An Automated Dual Modeling Approach to Accelerate Reaction Analysis and Optimization

In modern pharmaceutical research, the demand for expeditious development of synthetic routes to active pharmaceutical ingredients (APIs) has led to a paradigm shift towards data-rich process development. Conventional methodologies en-compass prolonged timelines for reaction and analytical model developments. Both method developments are separated into different departments and often require an iterative process to optimize the models. Addressing this issue, we intro-duce an innovative dual modeling approach, seamlessly integrating the development of a Process Analytical Technology (PAT) strategy with reaction optimization. This integrated approach is exemplified in diverse amidation reactions and the synthesis of the API benznidazole. The platform, characterized by a high degree of automation and minimal operator in-volvement, achieves PAT calibration through a “standard addition” approach. Dynamic experiments are executed to screen a broad process space and gather data for fitting kinetic parameters. Employing a Julia-coded software program facilitates rapid kinetic parameter fitting and in-situ optimization within minutes. This highly automated workflow not only expedites the understanding and optimization of chemical processes, but also holds significant promise for time and resource savings within the pharmaceutical industry.