Towards Autonomous Process Control—Digital Twin for HIV-Gag VLP Production in HEK293 Cells Using a Dynamic Metabolic Model

Helgers, Heribert; Hengelbrock, Alina; Rosengarten, Jamila Franca; Stitz, Jörn; Schmidt, A.; Strube, Jochen

doi:10.3390/pr10102015

Cited by 6 publications

(10 citation statements)

References 48 publications

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“…The model consists of multiplicative Michaelis−Menten equations or variants derived from them, which represent the inhibition or activation of a reaction as a result of an accumulation of activator or inhibitor. 114,115 The change in oxygen concentration in the bioreactor depends on the transfer of oxygen from the supplied air and the supplied pure oxygen into the medium as well as the consumption of oxygen during cell respiration. The transition of oxygen from the gas phase to the liquid phase is described using the two-film model and depends on the volumetric mass transfer coefficient k L a and the equilibrium concentration c Od 2 *.…”

Section: Sds-pagementioning

confidence: 99%

Digital Twin for Continuous Production of Virus-like Particles toward Autonomous Operation

Hengelbrock,

Probst,

Baukmann

et al. 2024

ACS Omega

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Lentiviral vector and virus-like particle (VLP) manufacturing have been published in fed-batch upstream and batch downstream modes before. Batch downstream and continuous upstream in perfusion mode were reported as well. This study exemplifies development and validation steps for a digital twin combining a physical-chemical-based mechanistic model for all unit operations with a process analytical technology strategy in order to show the efforts and benefits of autonomous operation approaches for manufacturing scale. As the general models are available from various other biologic manufacturing studies, the main step is model calibration for the human embryo kidney cell-based VLPs with experimental quantitative validation within the Quality-by-Design (QbD) approach, including risk assessment to define design and control space. For continuous operation in perfusion mode, the main challenge is the efficient separation of large particle manifolds for VLPs and cells, including cell debris, which is of similar size. Here, innovative tangential flow filtration operations are needed to avoid fast blocking with low mechanical stress pumps. A twofold increase of productivity was achieved using simulation case studies. This increase is similar to improvements previously described for other entities like plasmid DNAs, monoclonal antibodies (mAbs), and single-chain fragments of variability (scFv) fragments. The advantages of applying a digital twin for an advanced process control strategy have proven additional productivity gains of 20% at 99.9% reliability.

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Section: Sds-pagementioning

confidence: 99%

Digital Twin for Continuous Production of Virus-like Particles toward Autonomous Operation

Hengelbrock,

Probst,

Baukmann

et al. 2024

ACS Omega

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“…HIV-based VLPs are usually produced by the transfection of mammalian cells (typically Chinese hamster ovary (CHO) cells or human embryonic kidney (HEK) 293 cells). , Once the production phase is completed, the cells are removed from the growth medium by means of centrifugation or depth filtration. Despite recent progress achieved in downstream processing technology, the high-resolution and cost-efficient purification of HIV-based VLPs from this unique matrix still represents a serious challenge and currently constitutes one of the main bottlenecks in the successful commercialization of vaccines based on enveloped VLPs. , The current technology mainly involves state-of-the-art ion exchangers and the precise adjustment of elution conditions. − …”

Section: Introductionmentioning

confidence: 99%

Investigation of the Electrokinetic Properties of HIV-Based Virus-Like Particles

Wolf,

Grau,

Rosengarten

et al. 2024

Langmuir

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The antigen density on the surface of HIV-based virus-like particles (VLPs) plays a crucial role in the improvement of HIV vaccine potency. HIV VLPs consist of a dense protein core, which is surrounded by a lipid bilayer and whose surface is usually decorated with antigenic glycoproteins. The successful downstream processing of these particles is challenging, and the high-resolution and cost-efficient purification of HIV-based VLPs has not yet been achieved. Chromatography, one of the major unit operations involved in HIV VLP purification strategies, is usually carried out by means of ion exchangers or ion-exchange membranes. Understanding the electrokinetic behavior of HIV-based VLPs may help to improve the adjustment and efficiency of the corresponding chromatographic processes. In this study, we investigated the electrokinetics and aggregation of both undecorated and decorated VLPs and interpreted the data from the perspective of the soft particle model developed by Ohshima (OSPM), which fails to fully predict the behavior of the studied VLPs. Post-Ohshima literature, and particularly the soft multilayer particle model developed by Langlet et al., provides an alternative theoretical framework to overcome the limits of the OSPM. We finally hypothesized that the electrophoretic mobility of HIV-based VLPs is controlled by an electrohydrodynamic interplay between envelope glycoproteins, lipid bilayer, and Gag envelope.

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“…Joiner and co‐authors have reviewed modeling approaches of recombinant adeno‐associated virus production in HEK293 cells (Joiner et al, 2022). Helgers and co‐authors developed a dynamic model to describe cell growth, metabolism (glucose, lactate, ammonium and amino acids) and HIV virus‐like particle production in fed‐batch cultivations (Helgers et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Deep hybrid modeling of a HEK293 process: Combining long short‐term memory networks with first principles equations

Ramos,

Pinto,

Poiares‐Oliveira

et al. 2024

Biotech & Bioengineering

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The combination of physical equations with deep learning is becoming a promising methodology for bioprocess digitalization. In this paper, we investigate for the first time the combination of long short‐term memory (LSTM) networks with first principles equations in a hybrid workflow to describe human embryonic kidney 293 (HEK293) culture dynamics. Experimental data of 27 extracellular state variables in 20 fed‐batch HEK293 cultures were collected in a parallel high throughput 250 mL cultivation system in an industrial process development setting. The adaptive moment estimation method with stochastic regularization and cross‐validation were employed for deep learning. A total of 784 hybrid models with varying deep neural network architectures, depths, layers sizes and node activation functions were compared. In most scenarios, hybrid LSTM models outperformed classical hybrid Feedforward Neural Network (FFNN) models in terms of training and testing error. Hybrid LSTM models revealed to be less sensitive to data resampling than FFNN hybrid models. As disadvantages, Hybrid LSTM models are in general more complex (higher number of parameters) and have a higher computation cost than FFNN hybrid models. The hybrid model with the highest prediction accuracy consisted in a LSTM network with seven internal states connected in series with dynamic material balance equations. This hybrid model correctly predicted the dynamics of the 27 state variables (R2 = 0.93 in the test data set), including biomass, key substrates, amino acids and metabolic by‐products for around 10 cultivation days.

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Towards Autonomous Process Control—Digital Twin for HIV-Gag VLP Production in HEK293 Cells Using a Dynamic Metabolic Model

Cited by 6 publications

References 48 publications

Digital Twin for Continuous Production of Virus-like Particles toward Autonomous Operation

Digital Twin for Continuous Production of Virus-like Particles toward Autonomous Operation

Investigation of the Electrokinetic Properties of HIV-Based Virus-Like Particles

Deep hybrid modeling of a HEK293 process: Combining long short‐term memory networks with first principles equations

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