Cell cycle and apoptosis: a map for the GS-NS0 cell line at the genetic level and the link to environmental stress

Usaku, Chonlatep; Munzer, David Garcia; Pistikopoulos, Efstratios N.; Mantalaris, Athanasios

doi:10.1186/1753-6561-7-s6-p54

Cited by 1 publication

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“…Four key genes involved in apoptosis have been considered: caspase‐8 and caspase‐3 , as explained above, together with bcl‐2 and bax, respectively, encoding for anti‐ and proapoptotic proteins . Unpublished data from GS–NS0 fed‐batch cultures conducted in the authors’ laboratory suggest that the expression of caspase‐8 is increased in the absence of aspartate and glutamate, and in order to account for the role of arginine the dependency on the concentration of this AA was also considered. The expression of caspase‐8 has been modeled by Equation .…”

Section: Monoclonal Antibodymentioning

confidence: 99%

A Predictive Mathematical Model of Cell Cycle, Metabolism, and Apoptosis of Monoclonal Antibody‐Producing GS–NS0 Cells

Grilo

Mantalaris

2019

Biotechnology Journal

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The monoclonal antibody (mAb) industry is witnessing unprecedented growth, with an increasing range of new molecules and biosimilars as well as disease targets approved than ever before. Competition necessitates pharmaceutical companies to reduce development/production costs and time‐to‐market. To this aim, mathematical modeling can aid traditional experiment‐only‐based process development by reducing the design space, integrating scales, and assisting in identifying optimal operating conditions in less time and with lower expense. Mathematical models have been employed by other industries for control and optimization purposes and are important decisional tools for testing scenarios, process configurations, operating conditions, etc. Herein, a predictive, experimentally validated mathematical model that captures cellular metabolism and growth with cell cycle, cell death (apoptosis), and mAb production in GS–NS0 cells is presented. The model utilizes cellular, metabolic, and gene expression data, highlighting how multiple data sources can be integrated in one tool with the aim of optimizing mammalian cell bioprocessing.

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Section: Monoclonal Antibodymentioning

confidence: 99%