Multivariate Data Analysis Finds Use In Biopharmaceutical Process Development And Scale-Up

Multivariate data analysis (MVDA) is being used to effectively handle complex datasets generated by process analytical technology (PAT) in biopharmaceutical process development and manufacturing. From these large datasets, MVDA can be used to identify the parameters that are causing most of the variability in a process. These parameters can then be controlled to improve consistency in the process and product quality, noted Rathore and Singh in an article reviewing use of MVDA in bioprocessing (1). The authors gave an example of MVDA used in scale-up of a cell-culture process from 2 L to  2000 L. Data analysis showed that osmolality and ammonia levels were changed upon scale-up, indicating a change in cell-culture performance. The change in osmolality resulted from the buildup of carbon dioxide due to less-efficient gas transfer at the larger scale.

MVDA can also be used to establish comparability of processes and products, which is crucial for biosimilar development, noted Rathore and Singh (1). Chemometric algorithms can be used to compare different phases of manufacturing. Partial-least squares analysis of data in a laboratory-scale and a production-scale fermenter, for example, identified which variables were responsible for differences between the two scales.

Sartorius Stedim Biotech (SSB) recently integrated chemometric software into its microbioreactors used for bioprocess development. "Providing a consistent, scalable platform for design-of-experiment (DOE) studies and data analysis will help scientists develop robust and flexible manufacturing processes based on single-use bioreactor technology," said Mario Becker, director of marketing, PAT and Automation at SSB, in a press release (2). He said that the MVDA toolkit would help reduce risk in bioprocess development and achieve more rapid, cost-effective production. The combination of microbioreactors and chemometric software can be used for media optimization, process parameter screening applications, and Monte Carlo simulations as part of a quality-by-design program to identify the desired operating region for manufacturing-scale processes, commented Barney Zoro, ambr15 product manager at SSB, in the press release.

References      
1. A.S. Rathore and S.K. Singh, "Use of Multivariate Data Analysis in Bioprocessing," www.biopharminternational.com/use-multivariate-data-analysis-bioprocessing, Apr. 1, 2015.
2. Sartorius Stedim Biotech, "New ambr Bioreactor Systems Enhanced with Software for Design of Experiments," Press Release, (Goettingen, Germany and Cambridge, UK, Feb. 25, 2015).