Analysis of Transformed Upstream Bioprocess Data Provides Insights into Biological System Variation

Area of Science:

• Biotechnology
• Bioprocess Engineering
• Data Science

Background:

• Multivariate data analysis (MVDA) is increasingly used in upstream bioprocess studies.
• Current methods often analyze metabolite and cell concentrations, which are affected by inherent system variations and operational changes.
• A need exists for analysis methods that are independent of scale, operational strategy, and biomass content.

Purpose of the Study:

• To propose and demonstrate a novel MVDA approach for upstream bioprocess analysis using specific rates.
• To show that analyzing specific rates provides superior insights into biological system behavior compared to concentration-based analysis.

Main Methods:

• Developed and applied MVDA and modeling techniques on specific biological rates derived from bioprocess data.
• Utilized two industrial case studies: HEK medium performance comparison and CHO scale-up/down study.
• Compared results from specific rate analysis with traditional concentration-based analysis.

Main Results:

• Analysis of specific rates revealed underlying biological system behaviors not evident from concentration data.
• The proposed method proved effective in both HEK and CHO case studies, demonstrating its versatility.
• Insights gained were independent of scale, operational strategy (batch, fed-batch), and biomass variations.

Conclusions:

• MVDA applied to specific rates offers a more robust and insightful approach to upstream bioprocess analysis.
• This method overcomes limitations of concentration-based analysis, providing a clearer understanding of biological system dynamics.
• The findings have significant implications for bioprocess development, optimization, and scale-up.