High-Throughput Automated Design of Experiment (DoE) and Kinetic Modeling to Aid in Process Development of an API

A Design of Experiment (DoE) and kinetic screening study was carried out using an automated reaction screening platform, and as a case study, an early stage in the synthesis of a late phase developmental candidate was investigated. Key impurities were tracked and kinetically modeled, and significant factors impacting impurity formation were identified. In particular, factors that influence the formation of the diastereomer 4, a precursor to an API impurity identified as a Critical Quality Attribute (CQA), were identified and optimized to minimize its formation. Acetic acid, methanesulfonic acid, volumes of solvent, amino alcohol, and reaction B temperature were observed to be the most significant factors along with a factor interaction between methanesulfonic acid and the reaction B temperature. From the experimental data, diastereomer levels of 2.5–5.4 mol % were observed and a kinetic model was developed around the diastereomer formation. Good agreement between the model and experimental data gave confidence in understanding the contributing factors of diastereomer generation, and enabled confirmation of process parameter recommendations to support risk assessments and Quality by Design (QbD) activities. In total, automation provided a 4–5 times savings in FTE hours over a manual process when conducting these experiments and greatly accelerated the generation of supporting information for a drug file.