MAR-APR 2019

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INTECH MARCH/APRIL 2019 21 PROCESS AUTOMATION Case study B: Column maintenance in production-scale chromatography A PAT methodology can be applied in production-scale chromatography to track column efficiency degradation using, for example, transition analysis and the calculated height equivalent to the theoretical plate (HETP), so en - gineers can optimize column mainte - nance. This example shows conduc- tivity and volume signals spanning a variety of production, downtime, re- generation, and transition analysis pe- riods (figure 6). First, the organization uses Seeq's Profile Search tool to identify all of the transition analysis periods, enabling calculation of the HETP during each transition. The HETP increases, indicat- ing fewer resolved separations per unit column length (i.e., lower efficiency), with total volume through the column, as might be expected. This calculation is refreshed as the connected data sources are updated, allowing engineers to con- tinuously monitor column efficiency and schedule maintenance before the HETP exceeds the desired threshold, which would decrease product purity. Similar analyses could be used to optimize flow rates and eluent com- position, increasing productivity and reducing maintenance costs. Further, this information can be captured as part of a continuous improvement pro- cess through workflow documentation in Journals and Organizer Topics. Recipe for success In a world currently trapped in unfocused data collection and time-consuming, complicated, nontransferable spread- sheets, there is a path forward. Data in and of itself is not useful unless one has an approach to derive insights from it. Fortu- nately, there is a recipe for success. The keys are implementing an ad- vanced analytics solution where the da tasets are gathered strategically with an end use in mind upfront, and then providing a way for these datasets to be easily accessed and analyzed within a user-friendly interface. With this ap- proach in hand, organizations can more fully realize the knowledge management practices essential to achieving business value within a PAT framework. n ABOUT THE AUTHOR Lisa Graham, PhD, PE (lisa.graham@seeq. com), leads the analytics engineering team at Seeq Corporation. Her PhD is in chemi- RESOURCES "It's the right time for PAT" "What's next for big data in process manufacturing" "Big data analytics need new solutions" Guidance for Industry PAT — A Framework for Innovative Pharma - ceutical Development, Manufactur- ing, and Quality Assurance ucm070305.pdf cal engineering, and she has 20 years of experience across many industries—includ- ing pharmaceuticals and life sciences and specialty chemicals. Graham was previ- ously COO and SVP at Bend Research (now Lonza) and Alkemy Innovation, which she founded. Graham was director of the Or - egon governor's STEM Investment Council and chair of the Oregon Board of Trustees for Oregon Tech University. View the online version at Figure 6. Pharmaceutical process example illustrating how a PAT methodology can be applied in production-scale chromatography to track column efficiency degradation using Workbench and Journal.

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