Abstract
Intensified and accelerated development processes are being demanded by the market, as innovative biopharmaceuticals such as virus-like particles, exosomes, cell and gene therapy, as well as recombinant proteins and peptides will possess no available platform approach. Therefore, methods that are able to accelerate this development are preferred. Especially, physicochemical rigorous process models, based on all relevant effects of fluid dynamics, phase equilibrium, and mass transfer, can be predictive, if the model is verified and distinctly quantitatively validated. In this approach, a macroscopic kinetic model based on Monod kinetics for mammalian cell cultivation is developed and verified according to a general valid model validation workflow. The macroscopic model is verified and validated on the basis of four decision criteria (plausibility, sensitivity, accuracy and precision as well as equality). The process model workflow is subjected to a case study, comprising a Chinese hamster ovary fed-batch cultivation for the production of a monoclonal antibody. By performing the workflow, it was found that, based on design of experiments and Monte Carlo simulation, the maximum growth rate µmax exhibited the greatest influence on model variables such as viable cell concentration XV and product concentration. In addition, partial least squares regressions statistically evaluate the correlations between a higher µmax and a higher cell and product concentration, as well as a higher substrate consumption.
Highlights
The process analytical technology (PAT), which was initiated by the Food and Drug Administration (FDA) in 2004, is a key-enabling technology for quality-by-design (QbD) process development approaches [1,2,3]
An online estimation of difficult to measure variables can be achieved by implementing macroscopic kinetic models into
A Monod-type process model was used for the simulation of dynamic cellular states, as well as the uptake of substrates (i.e., glucose (GLC), glutamine (GLN)), production of metabolites (i.e., lactate (LAC), ammonium (AMM)), and product (i.e., monoclonal antibody)
Summary
The process analytical technology (PAT), which was initiated by the Food and Drug Administration (FDA) in 2004, is a key-enabling technology for quality-by-design (QbD) process development approaches [1,2,3]. Bioprocess (i.e., cultivation in batch, fed-batch, and continuous operational mode) monitoring includes process variables such as (viable) cell, substrate, metabolite, and product concentration, as well as product quality and impurities. These target variables depend on state variables such as pH, dissolved oxygen (pO2 ), and temperature, providing suitable cultivation conditions [8]. The ability for measurement, analysis, monitoring, and controlling of variables, preferably online, is strongly dependent on the state (i.e., physical, chemical, biological), the variable itself, and available sensor techniques [2,10]. An online estimation of difficult to measure variables can be achieved by implementing macroscopic kinetic models into
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