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.