Population balance modeling of influenza virus replication in MDCK cells during vaccine production

Mueller, Thomas; Schulze‐Horsel, J.; Sidorenko, Y.; Reichl, Udo; Kienle, Achim

doi:10.1016/s1570-7946(08)80027-2

Cited by 8 publications

(7 citation statements)

References 67 publications

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“…To account for characteristic dynamic phenomena concerning the intracellular progress of infection a degree of fluorescence was introduced as an internal coordinate which is linearly linked to the intracellular amount of NP. The lag period between infection and virus release was implemented directly as opposed to previous approaches with distributed cell populations (see Müller et al, 2008, 2011). In this way, distinct waves of virus release could be produced which are characteristic for the early phase of vaccine production processes with low multiplicities of infection.…”

Section: Resultsmentioning

confidence: 99%

“…First steps in this direction using either stochastic or deterministic modeling approaches were done by Sidorenko et al (2008a, b) and Müller et al (2008), respectively, for equine influenza A virus infection of adherent Madin–Darby canine kidney (MDCK) cells. In contrast to this, focus in the present article is on human influenza A virus.…”

Section: Introductionmentioning

confidence: 99%

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Distributed modeling of human influenza a virus–host cell interactions during vaccine production

Müller

Dürr

Isken

et al. 2013

Biotech & Bioengineering

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This contribution is concerned with population balance modeling of virus-host cell interactions during vaccine production. Replication of human influenza A virus in cultures of adherent Madin-Darby canine kidney (MDCK) cells is considered as a model system. The progress of infection can be characterized by the intracellular amount of viral nucleoprotein (NP) which is measured via flow cytometry. This allows the differentiation of the host cell population and gives rise to a distributed modeling approach. For this purpose a degree of fluorescence is introduced as an internal coordinate which is linearly linked to the intracellular amount of NP. Experimental results for different human influenza A subtypes reveal characteristic dynamic phenomena of the cell distribution like transient multimodality and reversal of propagation direction. The presented population balance model provides a reasonable explanation for these dynamic phenomena by the explicit consideration of different states of infection of individual cells. Kinetic parameters are determined from experimental data. To translate the emerging infinite dimensional parameter estimation problem to a finite dimension the parameters are assumed to depend linearly on the internal coordinate. As a result, the model is able to reproduce all characteristic dynamic phenomena of the considered process for the two examined virus strains and allows deeper insight into the underlying kinetic processes. Thus, the model is an important contribution to the understanding of the intracellular virus replication and virus spreading in cell cultures and can serve as a stepping stone for optimization in vaccine production.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Distributed modeling of human influenza a virus–host cell interactions during vaccine production

Müller

Dürr

Isken

et al. 2013

Biotech & Bioengineering

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“…Provides information on the extent/progress of infection in the cell population. Data can be obtained from flow cytometry [116][117][118] List of Figures Dynamical cellular-scale model outputs for a recombinant AAV production process. In this study, Nguyen et al [11] created a model mapping the generation of recominant AAVs via transient transfection.…”

Section: Fluorescencementioning

confidence: 99%

“…Figure 3: Flowchart for a simplified TIV system adapted from [69]; see [120] for additional examples of flow charts for more complex systems.…”

Section: Fluorescencementioning

confidence: 99%

Mechanistic Modeling of Viral Particle Production

Canova

Inguva

Braatz

2022

Preprint

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Viral systems such as wild-type viruses, viral vectors, and virus-like particles are essential components of modern biotechnology and medicine. Despite their importance, the commercial-scale production of viral systems remains highly inefficient for multiple reasons. Computational strategies are a promising avenue for improving process development, optimization, and control, but require a mathematical description of the system. This article reviews mechanistic modeling strategies for the production of viral particles, both at the cellular and bioreactor scales. In many cases, techniques and models from adjacent fields such as epidemiology and wild-type viral infection kinetics can be adapted to construct a suitable process model. These process models can then be employed for various purposes such as in-silico testing of novel process operating strategies and/or advanced process control.

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“…However, as with cellular-and reactorscale models, analogous multiscale wild-type viral models can be leveraged for recombinant multiscale modeling(Garira, 2017). These wild-type models are typically motivated by mapping the spread and treatment of a virus within a population, tissue, or cellular system, but many of the high-level mathematical approaches and considerations F I G U R E 3 Flowchart for a simplified TIV system adapted fromMöhler et al (2005); seeMüller (2015) for additional examples of flow charts for more complex systems.F I G U R E 4 Exemplar reactor-scale simulations performed using the TIV (left) and extended model (right) in a continuously stirred tank reactor (CSTR) fromFrensing et al (2013) Frensing et al (2013). observed oscillatory behavior during experimental runs which was explained by the presence of defective interfering particles (DIPs).…”

mentioning

confidence: 99%

Mechanistic modeling of viral particle production

Canova

Inguva

Braatz

2022

Biotech & Bioengineering

View full text Add to dashboard Cite

Viral systems such as wild‐type viruses, viral vectors, and virus‐like particles are essential components of modern biotechnology and medicine. Despite their importance, the commercial‐scale production of viral systems remains highly inefficient for multiple reasons. Computational strategies are a promising avenue for improving process development, optimization, and control, but require a mathematical description of the system. This article reviews mechanistic modeling strategies for the production of viral particles, both at the cellular and bioreactor scales. In many cases, techniques and models from adjacent fields such as epidemiology and wild‐type viral infection kinetics can be adapted to construct a suitable process model. These process models can then be employed for various purposes such as in‐silico testing of novel process operating strategies and/or advanced process control.

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Population balance modeling of influenza virus replication in MDCK cells during vaccine production

Cited by 8 publications

References 67 publications

Distributed modeling of human influenza a virus–host cell interactions during vaccine production

Distributed modeling of human influenza a virus–host cell interactions during vaccine production

Mechanistic Modeling of Viral Particle Production

Mechanistic modeling of viral particle production

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