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The approach was applied to the production process of a difficult\u2010to\u2010express enzyme by CHO cells, to identify key feed medium component candidates responsible for improved productivity through feed modification. The exploitation of untargeted metabolomics implies no prior decision of the metabolites or pathways and thus allows screening of metabolic phenomena and bringing an objective perspective. However, such exploitation is challenging due to the high\u2010dimensionality, complexity, relative quantitative information, and high analysis cost of the data, leading to data scarcity. A combination of untargeted metabolomics data exploration and mechanistic modeling was developed to leverage metabolomics data. The study analyzed LC\/MS\/MS metabolomics data (563 cellular and 386 supernatant metabolites) to determine the key metabolites involved in the productivity increase associated with a feeding modification. The metabolome data was utilized to expand the original stoichiometric reaction network of 127 reactions to 370 reactions. Mechanistic modeling using elementary flux modes\u2010based column generation identified and simulated the underlying metabolic pathways. Twenty\u2010one key metabolites significant for productivity improvement were revealed. This included several unexpected metabolites, such as citraconate and 5\u2010aminovaleric acid, in addition to well\u2010known components, as well as their underlying metabolic pathways. This study offers a novel approach for investigating nutrient supplementation in terms of metabolic fluxes and process performance, paving the way for rational process optimization supported by mechanistic understanding.<\/jats:p>","DOI":"10.1002\/biot.70008","type":"journal-article","created":{"date-parts":[[2025,7,4]],"date-time":"2025-07-04T03:31:02Z","timestamp":1751599862000},"source":"Crossref","is-referenced-by-count":2,"title":["Novel Data\u2010Driven Mechanistic Modeling of Untargeted Metabolome Data Reveals Feed Component Effects in CHO Cell Bioprocess Using Column Generation\u2010Based EFMs"],"prefix":"10.1002","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2753-4152","authenticated-orcid":false,"given":"Meeri E.\u2010L.","family":"M\u00e4kinen","sequence":"first","affiliation":[{"name":"Competence Centre for Advanced Bioproduction by Continuous Processing, AdBIOPRO Stockholm Sweden"},{"name":"Department of Industrial Biotechnology School of Engineering 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