Enabling Rapid Elemental Analysis of Highly-Automated, Parallel Screening Studies for Pharmaceutical Process Development

In the pharmaceutical industry, utilization of lab automation for parallel, statistically designed experiments to optimize reagent and processing parameters allows for accelerated development of chemical processes. The resulting generation of comprehensive, high-fidelity data sets provides in-depth knowledge which ultimately informs a robust chemical manufacturing process. For a given chemical step that may require downstream removal of a metal catalyst, the use of X-ray fluorescence (XRF) enables rapid elemental analysis of samples for pharmaceutical process development. Together, automated parallel experimentation and XRF technology have proven to be a valuable partnership for the high-throughput analysis of large sample arrays for obtaining process knowledge and advancing pharmaceutical process development. Herein, we exhibit a case study where the combination of highly-automated design of experiments (DoE) studies and XRF allowed for rapid metals analysis and, subsequently, significant improvements in processing a late stage asset to remove trace metals.