Bioprocess digital twins of mammalian cell culture for advanced biomanufacturing

Park, Seo-Young; Park, Cheol-Hwan; Choi, Dong-Hyuk; Hong, Jong Kwang; Lee, Dong-Yup

doi:10.1016/j.coche.2021.100702

Cited by 40 publications

(40 citation statements)

References 49 publications

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“…In this regard, the current study spells out a suitable and easily available statistical technique, which can be combined with a mechanistic model of CHO cells, for directing medium improvement systematically and efficiently. The procedure can also be viewed as an element in a digital twin prototype for guiding real‐time nutrient adjustments during bioprocessing, towards advanced biomanufacturing (Carbonell et al, 2020; Park et al, 2021; L. Zhang et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

Combined multivariate statistical and flux balance analyses uncover media bottlenecks to the growth and productivity of Chinese hamster ovary cell cultures

Yeo

Park

Tan

et al. 2022

Biotech & Bioengineering

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Chinese hamster ovary (CHO) cells are widely used for producing recombinant proteins. To enhance their productivity and product quality, media reformulation has been a key strategy, albeit with several technical challenges, due to the myriad of complex molecular mechanisms underlying media effects on culture performance. Thus, it is imperative to characterize metabolic bottlenecks under various media conditions systematically. To do so, we combined partial least square regression (PLS‐R) with the flux balance analysis of a genome‐scale metabolic model to elucidate the physiological states and metabolic behaviors of human alpha‐1 antitrypsin producing CHO‐DG44 cells grown in one commercial and another two in‐house media under development. At the onset, PLS‐R was used to identify metabolite exchanges that were correlated to specific growth and productivity. Then, by comparing metabolic states described by resultant flux distributions under two of the media conditions, we found suboptimal level of four nutrients and two metabolic wastes, which plausibly hindered cellular growth and productivity; mechanistically, lactate and ammonia recycling were modulated by glutamine and asparagine metabolisms in the media conditions, and also by hitherto unsuspected folate and choline supplements. Our work demonstrated how multivariate statistical analysis can be synergistically combined with metabolic modeling to uncover the mechanistic elements underlying differing media performance. It thus paved the way for the systematic identification of nutrient targets for medium reformulation to enhance recombinant protein production in CHO cells.

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Section: Discussionmentioning

confidence: 99%

Combined multivariate statistical and flux balance analyses uncover media bottlenecks to the growth and productivity of Chinese hamster ovary cell cultures

Yeo

Park

Tan

et al. 2022

Biotech & Bioengineering

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“…Each complex step in bioprocess manufacturing potentially impacts the quality of the final product, yet state-of-the-art practices focus on the static outputs of individual UOs rather than on a holistic process model, particularly with regard to potential real-time applications [ 1 , 4 , 28 , 29 , 30 , 31 ]. Having so far discussed the innovative improvements to the IPM technology, it is now important to better define the framework for real-time DA deployment.…”

Section: Discussionmentioning

confidence: 99%

Architectural and Technological Improvements to Integrated Bioprocess Models towards Real-Time Applications

Taylor

Pretzner

Zahel³

et al. 2022

Bioengineering

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Integrated or holistic process models may serve as the engine of a digital asset in a multistep-process digital twin. Concatenated individual-unit operation models are effective at propagating errors over an entire process, but are nonetheless limited in certain aspects of recent applications that prevent their deployment as a plausible digital asset, particularly regarding bioprocess development requirements. Sequential critical quality attribute tests along the process chain that form output–input (i.e., pool-to-load) relationships, are impacted by nonaligned design spaces at different scales and by simulation distribution challenges. Limited development experiments also inhibit the exploration of the overall design space, particularly regarding the propagation of extreme noncontrolled parameter values. In this contribution, bioprocess requirements are used as the framework to improve integrated process models by introducing a simplified data model for multiunit operation processes, increasing statistical robustness, adding a new simulation flow for scale-dependent variables, and describing a novel algorithm for extrapolation in a data-driven environment. Lastly, architectural and procedural requirements for a deployed digital twin are described, and a real-time workflow is proposed, thus providing a final framework for a digital asset in bioprocessing along the full product life cycle.

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“…This possibility will empower research across fields and the use of this database within digitalization efforts, in which having a cloud-based data storage system, as presented in this work, is fundamental. For example, see Park et al (2021) and Gargalo et al (2020b) for details concerning the flow of information under the digitalization paradigm. Moreover, the data and models included in the database will also have a peerreview cycle allowing other users to edit the information currently available in the database and, at the same time, add new information.…”

Section: Limitations and Future Perspectivesmentioning

confidence: 99%

NyctiDB: A non-relational bioprocesses modeling database supported by an ontology

et al. 2022

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Strategies to exploit and enable the digitalization of industrial processes are on course to become game-changers in optimizing (bio)chemical facilities. To achieve this, these industries face an increasing need for process models and, as importantly, an efficient way to store the models and data/information. Therefore, this work proposes developing an online information storage system that can facilitate the reuse and expansion of process models and make them available to the digitalization cycle. This system is named NyctiDB, and it is a novel non-relational database coupled with a bioprocess ontology. The ontology supports the selection and classification of bioprocess models focused information, while the database is in charge of the online storage of said information. Through a series of online collections, NyctiDB contains essential knowledge for the design, monitoring, control, and optimization of a bioprocess based on its mathematical model. Once NyctiDB has been implemented, its applicability and usefulness are demonstrated through two applications. Application A shows how NyctiDB is integrated inside the software architecture of an online educational bioprocess simulator. This implies that NyctiDB provides the information for the visualization of different bioprocess behaviours and the modifications of the models in the software. Moreover, the information related to the parameters and conditions of each model is used to support the users’ understanding of the process. Additionally, application B illustrates that NyctiDB can be used as AI enabler to further the research in this field through open-source and reliable data. This can, in fact, be used as the information source for the AI frameworks when developing, for example, hybrid models or smart expert systems for bioprocesses. Henceforth, this work aims to provide a blueprint on how to collect bioprocess modeling information and connect it to facilitate and empower the Internet-of-Things paradigm and the digitalization of the biomanufacturing industries.

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Bioprocess digital twins of mammalian cell culture for advanced biomanufacturing

Cited by 40 publications

References 49 publications

Combined multivariate statistical and flux balance analyses uncover media bottlenecks to the growth and productivity of Chinese hamster ovary cell cultures

Combined multivariate statistical and flux balance analyses uncover media bottlenecks to the growth and productivity of Chinese hamster ovary cell cultures

Architectural and Technological Improvements to Integrated Bioprocess Models towards Real-Time Applications

NyctiDB: A non-relational bioprocesses modeling database supported by an ontology

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