CASE STUDY INVOLVING REAL-TIME PROCESS MONITORING
As an example of real-time multivariate statistical process monitoring, a PCA-based model has been developed for monitoring
a mammalian cell culture bioreactor at commercial-scale. In this setting, historical batches are mined from the manufacturing
databases to develop a nominal process model for a seed bioreactor train. Eleven process variables that are measured online
for 30 batches are used in model building. The model is able to explain overall process variability with only three PCs. New
production batches are monitored against this model in real time.
During the real-time monitoring, one typically looks at high-level multivariate charts for deviation detection purposes as
mentioned earlier. In Figure 3, the three main steps involved in monitoring are shown. In step 1, a T
chart is used to detect a deviation. Step 2 involves diagnosis at the variable level, which indicates that the pH probe is
reading less than historical averages, i.e., outside of +/–3 standard deviation. Finally, in step 3, inspection of the pH
trace is performed. This allows scientists and engineers to start troubleshooting the probe and other operational factors
to better understand and monitor the process by this simple three-step process.20
Statistical techniques, such as those discussed in the article, have been demonstrated to be capable of performing rigorous
analysis of complex datasets that abound in biotech applications. This, combined with the advancements in analytical tools
to allow online analysis, can form the basis of real-time process monitoring. Implementation of such systems is likely to
result in gains in consistency of product quality as well as efficiency in manufacturing of biotech products and bring us
closer to full implementation of QbD and realizing its benefits.
Paul Konold is senior engineer, Rob Woolfenden II is principal engineer at Seattle, WA, Cenk Undey is principal engineer at West Greenwich, RI, and Anurag S. Rathore is director at Thousand Oaks, CA, 805.447.4491, email@example.com
All authors are in the process development department at Amgen, Inc. Rathore is also a member of BioPharm International's editorial advisory board.
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Other articles from The Elements of Biopharmaceutical Production series:
1. Modeling of Microbial and Mammalian Unit Operations
2. Scaling Down Fermentation
3. Optimization, Scale-up, and Validation Issues in Filtration
4. Filter Clogging Issues in Sterile Filtration
5. Lifetime Studies for Membrane Reuse
6. Modeling of Process Chromatography Unit Operation
7. Resin Screening to Optimize Chromatographic Separations
8. Optimization and Scale-Up in Preparative Chromatography
9. Scaling Down Chromatography and Filtration
10. Qualification of a Chromatographic Column
11. Efficiency Measurements for Chromatography Columns
12. Process Validation: How Much to Do and When to Do It
13. Quality by Design for Biopharmaceuticals: Defining Design Space
14. Quality by Design for Biopharmaceuticals: Case Studies
15. Design Space for Biotech Products
16. Applying PAT to Biotech Unit Operations
17. Applications of MVDA in Biotech Processing
18. Future Technologies for Efficient Manufacturing
19. Costing Issues in the Production of Biopharmaceuticals
20. Economic Analysis as a Tool for Process Development
For the entire series of The Elements of Biopharmaceutical Production, please visit