(558f) Leveraging PAT for Efficient Process Development Workflows

James C. Marek^*, Eric G. Moschetta, Travis B. Dunn,

AbbVie, Inc. Process R&D, 1401 Sheridan Road North Chicago, IL 60064

^*speaker: james.marek@abbvie.com

Timelines to develop process understanding and controls for pharmaceutical processes are universally short, necessitating efficient workflows to design and execute data-rich experiments leading to sound conclusions. Leveraging on-line Process Analytical Technology (PAT) is an integral component of efficient workflows. We present a case study that illustrates the power of in situ ATR/FTIR to elucidate fundamental kinetics for a complex reaction system, focusing in this talk on the development of the approach. Measuring the relevant chemical species concentrations was essential to modeling the kinetics, and on-line measurements with rapid sampling frequencies collected many data points over the course of the reaction.

The PAT approach was taken after careful consideration of the potential benefits and risks compared to the HPLC method intended for the manufacturing process. Simple calibration models constructed using FTIR measurements of solutions with a single reaction component yielded accuracy sufficient for the purposes of the study. The models were further used to derive species concentrations from FTIR profiles of the reaction run in batch mode. The concentration profiles were readily exported to standard software for kinetic modeling. Because the reaction was relatively fast, and the HPLC method involved a lengthy derivatization step, PAT via on-line ATR/FTIR was clearly the better approach for this investigation. ATR/FTIR was further used to monitor the reaction chemistry in the pilot plant process using the same calibration models developed for the lab study, with results demonstrating excellent scalability of the reaction.

This abstract presentation was sponsored by AbbVie. AbbVie contributed to the design, study conduct, and financial support for the research. AbbVie participated in the interpretation of data, writing, reviewing, and approving the publication. All authors are AbbVie employees.