ArticleBioprocess and biosystems engineering2016
Hybrid modeling as a QbD/PAT tool in process development: an industrial E. coli case study.
Article in Bioprocess and biosystems engineering, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- On the Prediction of pDNA Productivity Across Diverse Bioprocesses Using Ensemble Hybrid Models.Biotechnology and bioengineering · 2026Article
- Programmable cell differentiation in budding yeast uncouples reproductive and metabolic tasks.bioRxiv : the preprint server for biology · 2025Article
- The use of predictive models to develop chromatography-based purification processes.Frontiers in bioengineering and biotechnology · 2022Review
- Generic and specific recurrent neural network models: Applications for large and small scale biopharmaceutical upstream processes.Biotechnology reports (Amsterdam, Netherlands) · 2021Article
- Model-assisted DoE software: optimization of growth and biocatalysis in Saccharomyces cerevisiae bioprocesses.Bioprocess and biosystems engineering · 2021Article
- Working within the Design Space: Do Our Static Process Characterization Methods Suffice?Pharmaceutics · 2020Article
- Real-time monitoring and model-based prediction of purity and quantity during a chromatographic capture of fibroblast growth factor 2.Biotechnology and bioengineering · 2019Article
- Accelerated Bioprocess Development of Endopolygalacturonase-Production withBioengineering (Basel, Switzerland) · 2018Article
- From Physics to Bioengineering: Microbial Cultivation Process Design and Feeding Rate Control Based on Relative Entropy Using Nuisance Time.Entropy (Basel, Switzerland) · 2018Article
- Intensified design of experiments for upstream bioreactors.Engineering in life sciences · 2017Article
- Editorial: Bioprocess Development in the era of digitalization.Engineering in life sciences · 2017Article
- Raman spectroscopy as a process analytical technology for pharmaceutical manufacturing and bioprocessing.Analytical and bioanalytical chemistry · 2017Review
Corrections and comments
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Authors and funding
3 authors.
Funding
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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.
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Registered trials
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