How can measurement, monitoring, modeling and control advance cell culture in industrial biotechnology?

Carrondo, Manuel J.T.; Alves, Paula M.; Carinhas, Nuno; Glassey, Jarka; Hesse, Friedemann; Merten, Otto‐Wilhelm; Micheletti, Martina; Noll, Thomas; Oliveira, Rui; Reichl, Udo; Staby, Arne; Teixeira, Augusto; Weichert, Henry; Mandenius, Carl‐Fredrik

doi:10.1002/biot.201200226

Cited by 53 publications

(45 citation statements)

References 30 publications

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“…The US Food and Drug Administration advises (bio)pharmaceutical companies to use process analytical technology (PAT) for better control of bioprocesses in order to consistently deliver high quality products . In applications of PAT to cell cultivation processes, parameters are often controlled using data from well‐established classical sensors such as glass electrodes for pH, thermocouples for temperature or Clark electrodes for dissolved oxygen . Solutions for real‐time monitoring of other relevant analytes such as concentrations of cells, main nutrients, and metabolic by‐products (glucose, glutamine, lactate, etc.)…”

Section: Introductionmentioning

confidence: 99%

Process analytical technology tools for perfusion cell culture

Mercier

Rouel

Lebrun³

et al. 2015

Engineering in Life Sciences

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During cell cultivation processes for the production of biopharmaceuticals, good process performance and good product quality can be ensured by online monitoring of critical process parameters (e.g. temperature, pH, or dissolved oxygen). These data can be used in real‐time for process control, as suggested by the process analytical technology (PAT) initiative. Today, solutions for real‐time monitoring of parameters such as concentrations of cells, main nutrients, and metabolism by‐products are developing, but applications of these more complex tools in industrial settings are still limited. Here, we evaluated the use of dielectric spectroscopy (DS) and near‐infrared spectroscopy (NIRS) as PAT tools for a perfusion PER.C6® cultivation process. We showed that DS enabled predictions of viable cell density from the cultivation vessel, with a root mean square error of prediction (RMSEP) of 4.4% of the calibration range. Additionally, predictions of glucose and lactate concentrations from the cultivation vessel (RMSEP of 10 and 14%, respectively) and from the perfusion stream (RMSEP of 12 and 10%, respectively) were achieved with NIRS. We also showed that the perfusion stream offers great opportunities for noninvasive, yet frequent process monitoring. Accurate online monitoring of critical process parameters with PAT tools is the essential first step toward increased control of process output.

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Section: Introductionmentioning

confidence: 99%

Process analytical technology tools for perfusion cell culture

Mercier

Rouel

Lebrun³

et al. 2015

Engineering in Life Sciences

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“…It has been stressed by [48][49][50] that mathematical modeling is a substantial part of QbD since the model contributes to a scientific understanding on the product formation and the process control and monitoring. However, the performance of a model structure is highly dependent on the identification of key parameters.…”

Section: Modelingmentioning

confidence: 99%

Model-Based Design of Process Strategies for Cell Culture Bioprocesses: State of the Art and New Perspectives

Pörtner¹

2017

New Insights Into Cell Culture Technology

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Production processes for biopharmaceuticals with mammalian cells have to provide a nearly optimal environment to promote cell growth and product formation. Design and operation of a bioreactor are complex tasks, not only with respect to reactor configuration and size but also with respect to the mode of operation. New concepts for the design and layout of process strategies are required to meet regulatory demands and to guarantee efficient, safe, and reproducible biopharmaceutical production. Key elements are critical process parameters (CPPs), which affect critical quality attributes (CQAs), quality by design (QbD), process analytical tools (PAT), and design of experiment (DoE). In this chapter, some fundamentals including process and control strategies as well as concepts for process development are discussed. Examples for novel model-based concepts for the design of experiments to identify suitable fed-batch-feeding strategies are shown.

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“…The impact of Systems Biology in biotechnological processes is so great that the term "industrial systems biology" is today very common within this kind of industries [1,2]. Measurement, monitoring, modelling and control (the so-called M3C methodology) are critical for obtaining high value-added biochemicals [3].…”

Section: Introductionmentioning

confidence: 99%

MCR-ALS on metabolic networks: Obtaining more meaningful pathways

Folch-Fortuny

Tortajada

Prats-Montalbán

et al. 2015

Chemometrics and Intelligent Laboratory Systems

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With the aim of understanding the flux distributions across a metabolic network, i.e. within living cells, Principal Component Analysis (PCA) has been proposed to obtain a set of orthogonal components (pathways) capturing most of the variance in the flux data. The problems with this method are (i) that no additional information can be included in the model, and (ii) that orthogonality imposes a hard constraint, not always reasonably. To overcome these drawbacks, here we propose to use a more flexible approach such as Multivariate Curve Resolution -Alternating Least Squares (MCR-ALS) to obtain this set of biological pathways through the network. By using this method, different constraints can be included in the model, and the same source of variability can be present in different pathways, which is reasonable from a biological standpoint. This work follows a methodology developed for Pichia pastoris cultures grown on different carbon sources, lately presented in [González Martínez et al. 2014].In this paper a different grey modelling approach, which aims to incorporate a priori knowledge through constraints on the modelling algorithms, is applied to the same case of study. The results of both models are compared to show their strengths and weaknesses.

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How can measurement, monitoring, modeling and control advance cell culture in industrial biotechnology?

Cited by 53 publications

References 30 publications

Process analytical technology tools for perfusion cell culture

Process analytical technology tools for perfusion cell culture

Model-Based Design of Process Strategies for Cell Culture Bioprocesses: State of the Art and New Perspectives

MCR-ALS on metabolic networks: Obtaining more meaningful pathways

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