title: Hybrid modeling as a QbD/PAT tool in process development: an industrial E. coli case study.
abstract: Process understanding is emphasized in the process analytical technology initiative and the quality by design paradigm to be essential for manufacturing of biopharmaceutical products with consistent high quality. A typical approach to developing a process understanding is applying a combination of design of experiments with statistical data analysis. Hybrid semi-parametric modeling is investigated as an alternative method to pure statistical data analysis. The hybrid model framework provides flexibility to select model complexity based on available data and knowledge. Here, a parametric dynamic bioreactor model is integrated with a nonparametric artificial neural network that describes biomass and product formation rates as function of varied fed-batch fermentation conditions for high cell density heterologous protein production with E. coli. Our model can accurately describe biomass growth and product formation across variations in induction temperature, pH and feed rates. The model indicates that while product expression rate is a function of early induction phase conditions, it is negatively impacted as productivity increases. This could correspond with physiological changes due to cytoplasmic product accumulation. Due to the dynamic nature of the model, rational process timing decisions can be made and the impact of temporal variations in process parameters on product formation and process performance can be assessed, which is central for process understanding.
authors.affiliation: CEAM, Faculty of Science, Agriculture and Engineering, Newcastle University, Newcastle upon Tyne, NE1 7RU, UK. moritz.von-stosch@ncl.ac.uk.|REQUIMTE/DQ, Faculty of Science and Technology, University Nova de Lisboa, Campus de Caparica, 2829-516, Caparica, Portugal. moritz.von-stosch@ncl.ac.uk.
authors.forename: Moritz
authors.initials: M
authors.lastname: von Stosch
authors.affiliation: GSK Vaccines, Laval, Canada.|Lallemand Inc., Montreal, Canada.
authors.forename: Jan-Martijn
authors.initials: JM
authors.lastname: Hamelink
authors.affiliation: REQUIMTE/DQ, Faculty of Science and Technology, University Nova de Lisboa, Campus de Caparica, 2829-516, Caparica, Portugal.
authors.forename: Rui
authors.initials: R
authors.lastname: Oliveira
mesh_terms: D018533:Biomass; D019149:Bioreactors; D004926:Escherichia coli / Q000378:metabolism*; D005285:Fermentation; D008962:Models, Theoretical; D011994:Recombinant Proteins / Q000096:biosynthesis
chemical_list: D011994:Recombinant Proteins
keywords: Dynamic modeling; E. coli; High cell density fermentation; Hybrid modeling; Upstream bioprocess development/optimization