To be economically viable in the evolving biotherapeutic landscape, process development teams have an increasingly challenging task of developing robust cell culture processes that achieve desired productivity targets and product quality profiles in shorter timelines.  To meet this challenge, new technologies like metabolic modeling can be employed to identify changes to enable process improvements and optimization.  A variety of cell-based models exist and have been used to provide insights into changes in cell metabolism and predict how variations in process inputs (e.g., raw materials, process parameters, etc.) will affect culture performance and/or product quality.  Here, we present how a detailed, genome-based Chinese Hamster Ovary (CHO) cell model capable of predicting cell culture metabolite trends, as well as product glycosylation patterns, can be applied to provide solutions for different cell culture development challenges. To our knowledge, this is the first example of using an <i>in silico</i> model to make amino acid concentration predictions in order to improve cell culture performance and product glycan distribution. In separate proof-of-concept scenarios, the model was employed to make media predictions to address three different cell culture challenges relating to antibody production, reduction of a waste metabolite, and to target a desired glycan profile for a mAb therapeutic.

Applications of a CHO metabolic model for cell culture process development

2019 Spring National Meeting

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