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Published on: March 28, 2017
Identifying inhibitory threshold values of repressing metabolites in CHO cell culture using multivariate analysis
Zizhuo Xing1, Zhengjian Li, Vincent Chow
1Syracuse Manufacturing & Process Development, Bristol-Myers Squibb Company, Syracuse, New York 13221-4755, USA.
Abstract:
Elevation of lactate, ammonia, osmolality, and carbon dioxide to inhibitory levels was reported to have adverse effects on cell growth and protein productivity in mammalian cell culture. Multivariate analysis methods were used to investigate the roles of these repressing metabolites in a fed-batch CHO cell culture for antibody fusion protein B1 (B1) production. Principal Factor Analysis methodology was applied to manufacturing-scale data of 112 cell culture runs, which identified threshold values of four repressing metabolites as follows: (1) ammonium levels above 5.1 mM inhibit cell growth; (2) both lactate and osmolality levels above 58 mM and 382 mOsm/kg affect cell viability; and (3) carbon dioxide levels at or above 111 mmHg reduce protein quality. These threshold values were then verified by simulations using Monod-type equations and Canonical Correlation. These results suggest that adverse effects on cell growth, productivity, and product quality may be minimized under the ideal cell culture condition, in which the peak values of all four repressing metabolites are maintained below the threshold values. This strategy was evaluated in 45 cell culture runs in 50-L bioreactors. Eight out of 45 runs were operated under the ideal condition, while the remaining 37 runs had at least one repressing metabolite with peak value at or above the threshold. In comparison to the remaining runs, the eight cell culture runs under the ideal condition had 17%, 40%, and 11% higher values in peak viable cell density, final B1 titer, and quality attribute, respectively. The unique methodology used in this study may be generally applicable in characterizing cell culture processes.
Insights
Maintaining key metabolite levels below identified thresholds significantly improves Chinese hamster ovary (CHO) cell culture for antibody production. This optimization enhances cell growth, protein titer, and product quality.
Area of Science:
- Biotechnology
- Cell Culture Engineering
- Metabolic Engineering
Background:
- Elevated lactate, ammonia, osmolality, and carbon dioxide negatively impact mammalian cell culture growth and protein productivity.
- Understanding and controlling these inhibitory metabolites is crucial for optimizing biopharmaceutical manufacturing.
Purpose of the Study:
- To identify threshold values for inhibitory metabolites in fed-batch Chinese hamster ovary (CHO) cell culture for antibody fusion protein B1 (B1) production.
- To evaluate the impact of maintaining these metabolites below thresholds on cell growth, productivity, and product quality.
Main Methods:
- Multivariate analysis, specifically Principal Factor Analysis, applied to 112 manufacturing-scale fed-batch CHO cell culture runs.
- Identification of threshold values for ammonium, lactate, osmolality, and carbon dioxide.
- Verification of thresholds using Monod-type equations and Canonical Correlation, followed by evaluation in 50-L bioreactors.
Main Results:
- Identified inhibitory thresholds: ammonium (>5.1 mM), lactate (>58 mM), osmolality (>382 mOsm/kg), and carbon dioxide (>111 mmHg).
- Cell cultures operated under ideal conditions (metabolites below thresholds) showed significant improvements.
- Compared to suboptimal runs, ideal condition runs achieved 17% higher peak viable cell density, 40% higher final B1 titer, and 11% higher quality attribute.
Conclusions:
- Controlling peak metabolite levels below identified thresholds is critical for maximizing cell growth, protein productivity, and product quality in CHO cell cultures.
- The developed methodology offers a generalizable approach for characterizing and optimizing bioprocesses by managing inhibitory metabolites.
- Implementing ideal cell culture conditions based on metabolite thresholds leads to substantial gains in biomanufacturing efficiency and product yield.
