Simultaneous reaction- and analytical model building using dynamic flow experiments to accelerate process development

Abstract

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 encompass prolonged timelines for the development of both a reaction model and analytical models. The development of both methods are often separated into different departments and can require an iterative optimization process. Addressing this issue, we introduce an innovative dual modeling approach, combining 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 involvement, 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 an open-source software program facilitates rapid kinetic parameter fitting and additional in silico 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.