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

Abstract

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.

Recent Developments in Bioprocessing of Recombinant Proteins: Expression Hosts and Process Development

“…A simple techno-economic model for mAbs production was also studied that can be used for any production platform (Mir-Artigues et al, 2019). Various other modeling approaches to optimize bioprocesses have also been studied (Gangadharan et al, 2019;Grilo and Mantalaris, 2019). A three-dimensional computational fluid dynamics (CFD) model was established for the analysis of the influence of baffle structure on the flow field in orbitally shaken bioreactors (OSRs), and it was proposed that the shear stress was gentle for mammalian cell growth (Zhu et al, 2019a).…”

Integration Approaches to Model Bioreactor Hydrodynamics and Cellular Kinetics for Advancing Bioprocess Optimisation

“…There have been valuable contributions made in the literature for the application of CFD to model volumetric mass transfer coefficient (k L a) [ 40 , 41 , 42 ], power density (P/V) [ 43 , 44 , 45 ], mixing time [ 46 , 47 , 48 ], Kolmogorov length ( λ k ) [ 49 , 50 ], shear stress (τ) [ 51 , 52 , 53 ] and sedimentation [ 54 , 55 ] in bioreactors. Cell culture dynamics, metabolism and product glycosylation have been modelled in the past using mechanistic models [ 56 , 57 , 58 ], statistical models [ 59 , 60 , 61 ], and hybrid models [ 61 , 62 ]. The application of CFD for hydrodynamic characterisation and scale-up and CRK for cell metabolism modelling has been extensively reviewed recently [ 63 , 64 , 65 , 66 ].…”