---
_id: '13652'
abstract:
- lang: eng
  text: "Modellbasierte Konzepte und Simulationstechniken in Kombination mit digitalen
    Werkzeugen erweisen sich als Schlüssel, um das volle Potenzial biopharmazeutischer
    Produktionsprozesse zu erschließen, die mehrere herausfordernde Entwicklungs-
    und Prozessschritte enthalten. Einer dieser Schritte ist der zeit- und kostenintensive
    Zellproliferationsprozess (auch als Seed Train bezeichnet), um die Zellzahl vom
    Auftauen der Zellen bis zum Produktionsmaßstab zu erhöhen. Herausforderungen wie
    komplexer Zellstoffwechsel, Chargen-zu-Chargen-Variationen, Variabilitäten im
    Zellverhalten und Einflüsse von Änderungen der Kultivierungsbedingungen erfordern
    adäquate digitale Lösungen, um Informationen über den aktuellen und zukünftigen
    Prozesszustand bereitzustellen und korrekte Prozessentscheidungen abzuleiten.\r\n\r\nZu
    diesem Zweck haben sich digitale Seed Train Zwillinge als effizient erwiesen,
    die das zeitabhängige Verhalten wichtiger Prozessvariablen basierend auf mathematischen
    Modellen, Strategien und Anpassungsverfahren digital darstellen.\r\n\r\nDieses
    Kapitel skizziert die Notwendigkeit der Digitalisierung von Seed Trains, den Aufbau
    eines digitalen Seed Train Zwillings, die Rolle der Parameterschätzung und verschiedene
    statistische Methoden in diesem Zusammenhang, die auf mehrere Probleme im Bereich
    der Bioprozessierung anwendbar sind. Die Ergebnisse einer Fallstudie werden vorgestellt,
    um einen Bayes’schen Ansatz zur Parameterschätzung und Vorhersage eines industriellen
    Zellkultur-Seed Trains für die Seed Train Digitalisierung zu veranschaulichen."
author:
- first_name: Tanja
  full_name: Hernández Rodriguez, Tanja
  id: '52466'
  last_name: Hernández Rodriguez
- first_name: Björn
  full_name: Frahm, Björn
  id: '45666'
  last_name: Frahm
citation:
  ama: 'Hernández Rodriguez T, Frahm B. Digitale Seed Train Zwillinge und statistische
    Methoden. In: Herwig C, Pörtner R, Möller J, eds. <i>Digitale Zwillinge - Werkzeuge
    und Konzepte für intelligente Bioproduktion</i>. Advances in Biochemical Engineering/Biotechnology.
    Springer ; 2025:107-145. doi:<a href="https://doi.org/10.1007/978-3-031-75698-6_5">https://doi.org/10.1007/978-3-031-75698-6_5</a>'
  apa: Hernández Rodriguez, T., &#38; Frahm, B. (2025). Digitale Seed Train Zwillinge
    und statistische Methoden. In C. Herwig, R. Pörtner, &#38; J. Möller (Eds.), <i>Digitale
    Zwillinge - Werkzeuge und Konzepte für intelligente Bioproduktion</i> (pp. 107–145).
    Springer . <a href="https://doi.org/10.1007/978-3-031-75698-6_5">https://doi.org/10.1007/978-3-031-75698-6_5</a>
  bjps: '<b>Hernández Rodriguez T and Frahm B</b> (2025) Digitale Seed Train Zwillinge
    und statistische Methoden. In Herwig C, Pörtner R and Möller J (eds), <i>Digitale
    Zwillinge - Werkzeuge und Konzepte für intelligente Bioproduktion</i>. Berlin,
    Heidelberg: Springer , pp. 107–145.'
  chicago: 'Hernández Rodriguez, Tanja, and Björn Frahm. “Digitale Seed Train Zwillinge
    und statistische Methoden.” In <i>Digitale Zwillinge - Werkzeuge und Konzepte
    für intelligente Bioproduktion</i>, edited by Christoph Herwig, Ralf Pörtner,
    and Johannes Möller, 107–45. Advances in Biochemical Engineering/Biotechnology.
    Berlin, Heidelberg: Springer , 2025. <a href="https://doi.org/10.1007/978-3-031-75698-6_5">https://doi.org/10.1007/978-3-031-75698-6_5</a>.'
  chicago-de: 'Hernández Rodriguez, Tanja und Björn Frahm. 2025. Digitale Seed Train
    Zwillinge und statistische Methoden. In: <i>Digitale Zwillinge - Werkzeuge und
    Konzepte für intelligente Bioproduktion</i>, hg. von Christoph Herwig, Ralf Pörtner,
    und Johannes Möller, 107–145. Advances in Biochemical Engineering/Biotechnology.
    Berlin, Heidelberg: Springer . doi:<a href="https://doi.org/10.1007/978-3-031-75698-6_5">https://doi.org/10.1007/978-3-031-75698-6_5</a>,
    .'
  din1505-2-1: '<span style="font-variant:small-caps;">Hernández Rodriguez, Tanja</span>
    ; <span style="font-variant:small-caps;">Frahm, Björn</span>: Digitale Seed Train
    Zwillinge und statistische Methoden. In: <span style="font-variant:small-caps;">Herwig,
    C.</span> ; <span style="font-variant:small-caps;">Pörtner, R.</span> ; <span
    style="font-variant:small-caps;">Möller, J.</span> (Hrsg.): <i>Digitale Zwillinge
    - Werkzeuge und Konzepte für intelligente Bioproduktion</i>, <i>Advances in Biochemical
    Engineering/Biotechnology</i>. Berlin, Heidelberg : Springer , 2025, S. 107–145'
  havard: 'T. Hernández Rodriguez, B. Frahm, Digitale Seed Train Zwillinge und statistische
    Methoden, in: C. Herwig, R. Pörtner, J. Möller (Eds.), Digitale Zwillinge - Werkzeuge
    und Konzepte für intelligente Bioproduktion, Springer , Berlin, Heidelberg, 2025:
    pp. 107–145.'
  ieee: 'T. Hernández Rodriguez and B. Frahm, “Digitale Seed Train Zwillinge und statistische
    Methoden,” in <i>Digitale Zwillinge - Werkzeuge und Konzepte für intelligente
    Bioproduktion</i>, C. Herwig, R. Pörtner, and J. Möller, Eds. Berlin, Heidelberg:
    Springer , 2025, pp. 107–145. doi: <a href="https://doi.org/10.1007/978-3-031-75698-6_5">https://doi.org/10.1007/978-3-031-75698-6_5</a>.'
  mla: Hernández Rodriguez, Tanja, and Björn Frahm. “Digitale Seed Train Zwillinge
    und statistische Methoden.” <i>Digitale Zwillinge - Werkzeuge und Konzepte für
    intelligente Bioproduktion</i>, edited by Christoph Herwig et al., Springer ,
    2025, pp. 107–45, <a href="https://doi.org/10.1007/978-3-031-75698-6_5">https://doi.org/10.1007/978-3-031-75698-6_5</a>.
  short: 'T. Hernández Rodriguez, B. Frahm, in: C. Herwig, R. Pörtner, J. Möller (Eds.),
    Digitale Zwillinge - Werkzeuge und Konzepte für intelligente Bioproduktion, Springer
    , Berlin, Heidelberg, 2025, pp. 107–145.'
  ufg: '<b>Hernández Rodriguez, Tanja/Frahm, Björn</b>: Digitale Seed Train Zwillinge
    und statistische Methoden, in: <i>Herwig, Christoph/Pörtner, Ralf/Möller, Johannes
    (Hgg.)</i>: Digitale Zwillinge - Werkzeuge und Konzepte für intelligente Bioproduktion,
    Berlin, Heidelberg 2025 (Advances in Biochemical Engineering/Biotechnology), 
    S. 107–145.'
  van: 'Hernández Rodriguez T, Frahm B. Digitale Seed Train Zwillinge und statistische
    Methoden. In: Herwig C, Pörtner R, Möller J, editors. Digitale Zwillinge - Werkzeuge
    und Konzepte für intelligente Bioproduktion. Berlin, Heidelberg: Springer ; 2025.
    p. 107–45. (Advances in Biochemical Engineering/Biotechnology).'
date_created: 2026-03-27T17:45:02Z
date_updated: 2026-04-08T12:46:45Z
department:
- _id: DEP4000
doi: https://doi.org/10.1007/978-3-031-75698-6_5
editor:
- first_name: Christoph
  full_name: Herwig, Christoph
  last_name: Herwig
- first_name: Ralf
  full_name: Pörtner, Ralf
  last_name: Pörtner
- first_name: Johannes
  full_name: Möller, Johannes
  last_name: Möller
keyword:
- Bayes
- Digitaler Zwilling
- Parameterabschätzung
- Seed-Train
- Unsicherheit
language:
- iso: ger
page: 107-145
place: Berlin, Heidelberg
publication: Digitale Zwillinge - Werkzeuge und Konzepte für intelligente Bioproduktion
publication_identifier:
  eisbn:
  - 978-3-031-75698-6
  isbn:
  - 978-3-031-75697-9
publication_status: published
publisher: 'Springer '
quality_controlled: '1'
series_title: Advances in Biochemical Engineering/Biotechnology
status: public
title: Digitale Seed Train Zwillinge und statistische Methoden
type: book_chapter
user_id: '83781'
year: '2025'
...
---
_id: '11377'
abstract:
- lang: eng
  text: <jats:p>consuming and often performed rather empirically. Efficient optimization
    of multiple objectives such as process time, viable cell density, number of operating
    steps &amp; cultivation scales, required medium, amount of product as well as
    product quality depicts a promising approach. This contribution presents a workflow
    which couples uncertainty-based upstream simulation and Bayes optimization using
    Gaussian processes. Its application is demonstrated in a simulation case study
    for a relevant industrial task in process development, the design of a robust
    cell culture expansion process (seed train), meaning that despite uncertainties
    and variabilities concerning cell growth, low variations of viable cell density
    during the seed train are obtained. Compared to a non-optimized reference seed
    train, the optimized process showed much lower deviation rates regarding viable
    cell densities (&lt;10% instead of 41.7%) using five or four shake flask scales
    and seed train duration could be reduced by 56 h from 576 h to 520 h. Overall,
    it is shown that applying Bayes optimization allows for optimization of a multi-objective
    optimization function with several optimizable input variables and under a considerable
    amount of constraints with a low computational effort. This approach provides
    the potential to be used in the form of a decision tool, e.g., for the choice
    of an optimal and robust seed train design or for further optimization tasks within
    process development.
article_number: '883'
author:
- first_name: Tanja
  full_name: Hernández Rodriguez, Tanja
  id: '52466'
  last_name: Hernández Rodriguez
- first_name: Anton
  full_name: Sekulic, Anton
  last_name: Sekulic
- first_name: Markus
  full_name: Lange-Hegermann, Markus
  id: '71761'
  last_name: Lange-Hegermann
- first_name: Björn
  full_name: Frahm, Björn
  id: '45666'
  last_name: Frahm
citation:
  ama: Hernández Rodriguez T, Sekulic A, Lange-Hegermann M, Frahm B. Designing Robust
    Biotechnological Processes Regarding Variabilities Using Multi-Objective Optimization
    Applied to a Biopharmaceutical Seed Train Design. <i>Processes</i>. 2022;10(5).
    doi:<a href="https://doi.org/10.3390/pr10050883">10.3390/pr10050883</a>
  apa: Hernández Rodriguez, T., Sekulic, A., Lange-Hegermann, M., &#38; Frahm, B.
    (2022). Designing Robust Biotechnological Processes Regarding Variabilities Using
    Multi-Objective Optimization Applied to a Biopharmaceutical Seed Train Design.
    <i>Processes</i>, <i>10</i>(5), Article 883. <a href="https://doi.org/10.3390/pr10050883">https://doi.org/10.3390/pr10050883</a>
  bjps: <b>Hernández Rodriguez T <i>et al.</i></b> (2022) Designing Robust Biotechnological
    Processes Regarding Variabilities Using Multi-Objective Optimization Applied to
    a Biopharmaceutical Seed Train Design. <i>Processes</i> <b>10</b>.
  chicago: Hernández Rodriguez, Tanja, Anton Sekulic, Markus Lange-Hegermann, and
    Björn Frahm. “Designing Robust Biotechnological Processes Regarding Variabilities
    Using Multi-Objective Optimization Applied to a Biopharmaceutical Seed Train Design.”
    <i>Processes</i> 10, no. 5 (2022). <a href="https://doi.org/10.3390/pr10050883">https://doi.org/10.3390/pr10050883</a>.
  chicago-de: Hernández Rodriguez, Tanja, Anton Sekulic, Markus Lange-Hegermann und
    Björn Frahm. 2022. Designing Robust Biotechnological Processes Regarding Variabilities
    Using Multi-Objective Optimization Applied to a Biopharmaceutical Seed Train Design.
    <i>Processes</i> 10, Nr. 5. doi:<a href="https://doi.org/10.3390/pr10050883">10.3390/pr10050883</a>,
    .
  din1505-2-1: '<span style="font-variant:small-caps;">Hernández Rodriguez, Tanja</span>
    ; <span style="font-variant:small-caps;">Sekulic, Anton</span> ; <span style="font-variant:small-caps;">Lange-Hegermann,
    Markus</span> ; <span style="font-variant:small-caps;">Frahm, Björn</span>: Designing
    Robust Biotechnological Processes Regarding Variabilities Using Multi-Objective
    Optimization Applied to a Biopharmaceutical Seed Train Design. In: <i>Processes</i>
    Bd. 10. Basel, MDPI AG (2022), Nr. 5'
  havard: T. Hernández Rodriguez, A. Sekulic, M. Lange-Hegermann, B. Frahm, Designing
    Robust Biotechnological Processes Regarding Variabilities Using Multi-Objective
    Optimization Applied to a Biopharmaceutical Seed Train Design, Processes. 10 (2022).
  ieee: 'T. Hernández Rodriguez, A. Sekulic, M. Lange-Hegermann, and B. Frahm, “Designing
    Robust Biotechnological Processes Regarding Variabilities Using Multi-Objective
    Optimization Applied to a Biopharmaceutical Seed Train Design,” <i>Processes</i>,
    vol. 10, no. 5, Art. no. 883, 2022, doi: <a href="https://doi.org/10.3390/pr10050883">10.3390/pr10050883</a>.'
  mla: Hernández Rodriguez, Tanja, et al. “Designing Robust Biotechnological Processes
    Regarding Variabilities Using Multi-Objective Optimization Applied to a Biopharmaceutical
    Seed Train Design.” <i>Processes</i>, vol. 10, no. 5, 883, 2022, <a href="https://doi.org/10.3390/pr10050883">https://doi.org/10.3390/pr10050883</a>.
  short: T. Hernández Rodriguez, A. Sekulic, M. Lange-Hegermann, B. Frahm, Processes
    10 (2022).
  ufg: '<b>Hernández Rodriguez, Tanja u. a.</b>: Designing Robust Biotechnological
    Processes Regarding Variabilities Using Multi-Objective Optimization Applied to
    a Biopharmaceutical Seed Train Design, in: <i>Processes</i> 10 (2022), H. 5.'
  van: Hernández Rodriguez T, Sekulic A, Lange-Hegermann M, Frahm B. Designing Robust
    Biotechnological Processes Regarding Variabilities Using Multi-Objective Optimization
    Applied to a Biopharmaceutical Seed Train Design. Processes. 2022;10(5).
date_created: 2024-04-25T13:35:04Z
date_updated: 2024-05-21T09:30:15Z
department:
- _id: DEP4000
doi: 10.3390/pr10050883
intvolume: '        10'
issue: '5'
keyword:
- Gaussian processes
- Bayes optimization
- Pareto optimization
- multi-objective
- cell culture
- seed train
language:
- iso: eng
place: Basel
publication: Processes
publication_identifier:
  eissn:
  - 2227-9717
publication_status: published
publisher: MDPI AG
status: public
title: Designing Robust Biotechnological Processes Regarding Variabilities Using Multi-Objective
  Optimization Applied to a Biopharmaceutical Seed Train Design
type: scientific_journal_article
user_id: '83781'
volume: 10
year: '2022'
...
---
_id: '10193'
abstract:
- lang: eng
  text: Development and optimization of biopharmaceutical production processes with
    cell cultures is cost- and time-consuming and often performed rather empirically.
    Efficient optimization of multiple objectives such as process time, viable cell
    density, number of operating steps & cultivation scales, required medium, amount
    of product as well as product quality depicts a promising approach. This contribution
    presents a workflow which couples uncertainty-based upstream simulation and Bayes
    optimization using Gaussian processes. Its application is demonstrated in a simulation
    case study for a relevant industrial task in process development, the design of
    a robust cell culture expansion process (seed train), meaning that despite uncertainties
    and variabilities concerning cell growth, low variations of viable cell density
    during the seed train are obtained. Compared to a non-optimized reference seed
    train, the optimized process showed much lower deviation rates regarding viable
    cell densities (<10% instead of 41.7%) using five or four shake flask scales and
    seed train duration could be reduced by 56 h from 576 h to 520 h. Overall, it
    is shown that applying Bayes optimization allows for optimization of a multi-objective
    optimization function with several optimizable input variables and under a considerable
    amount of constraints with a low computational effort. This approach provides
    the potential to be used in the form of a decision tool, e.g., for the choice
    of an optimal and robust seed train design or for further optimization tasks within
    process development.
author:
- first_name: Tanja
  full_name: Hernández Rodriguez, Tanja
  id: '52466'
  last_name: Hernández Rodriguez
- first_name: Anton
  full_name: Sekulic, Anton
  last_name: Sekulic
- first_name: Markus
  full_name: Lange-Hegermann, Markus
  id: '71761'
  last_name: Lange-Hegermann
- first_name: Björn
  full_name: Frahm, Björn
  id: '45666'
  last_name: Frahm
citation:
  ama: 'Hernández Rodriguez T, Sekulic A, Lange-Hegermann M, Frahm B. Designing robust
    biotechnological processes regarding variabilities using multi-objective optimization
    applied to a biopharmaceutical seed train design. In: Pörtner R, Möller J, eds.
    <i>Bioprocess Systems Engineering Applications in Pharmaceutical Manufacturing</i>.
    Vol special issue. Processes : open access journal. MDPI; 2022:21-48. doi:<a href="https://doi.org/10.3390/pr10050883">https://doi.org/10.3390/pr10050883</a>'
  apa: 'Hernández Rodriguez, T., Sekulic, A., Lange-Hegermann, M., &#38; Frahm, B.
    (2022). Designing robust biotechnological processes regarding variabilities using
    multi-objective optimization applied to a biopharmaceutical seed train design.
    In R. Pörtner &#38; J. Möller (Eds.), <i>Bioprocess Systems Engineering Applications
    in Pharmaceutical Manufacturing: Vol. special issue</i> (pp. 21–48). MDPI. <a
    href="https://doi.org/10.3390/pr10050883">https://doi.org/10.3390/pr10050883</a>'
  bjps: '<b>Hernández Rodriguez T <i>et al.</i></b> (2022) Designing Robust Biotechnological
    Processes Regarding Variabilities Using Multi-Objective Optimization Applied to
    a Biopharmaceutical Seed Train Design. In Pörtner R and Möller J (eds), <i>Bioprocess
    Systems Engineering Applications in Pharmaceutical Manufacturing</i>, vol. special
    issue. Basel: MDPI, pp. 21–48.'
  chicago: 'Hernández Rodriguez, Tanja, Anton Sekulic, Markus Lange-Hegermann, and
    Björn Frahm. “Designing Robust Biotechnological Processes Regarding Variabilities
    Using Multi-Objective Optimization Applied to a Biopharmaceutical Seed Train Design.”
    In <i>Bioprocess Systems Engineering Applications in Pharmaceutical Manufacturing</i>,
    edited by Ralf Pörtner and Johannes Möller, special issue:21–48. Processes : Open
    Access Journal. Basel: MDPI, 2022. <a href="https://doi.org/10.3390/pr10050883">https://doi.org/10.3390/pr10050883</a>.'
  chicago-de: 'Hernández Rodriguez, Tanja, Anton Sekulic, Markus Lange-Hegermann und
    Björn Frahm. 2022. Designing robust biotechnological processes regarding variabilities
    using multi-objective optimization applied to a biopharmaceutical seed train design.
    In: <i>Bioprocess Systems Engineering Applications in Pharmaceutical Manufacturing</i>,
    hg. von Ralf Pörtner und Johannes Möller, special issue:21–48. Processes : open
    access journal. Basel: MDPI. doi:<a href="https://doi.org/10.3390/pr10050883">https://doi.org/10.3390/pr10050883</a>,
    .'
  din1505-2-1: '<span style="font-variant:small-caps;">Hernández Rodriguez, Tanja</span>
    ; <span style="font-variant:small-caps;">Sekulic, Anton</span> ; <span style="font-variant:small-caps;">Lange-Hegermann,
    Markus</span> ; <span style="font-variant:small-caps;">Frahm, Björn</span>: Designing
    robust biotechnological processes regarding variabilities using multi-objective
    optimization applied to a biopharmaceutical seed train design. In: <span style="font-variant:small-caps;">Pörtner,
    R.</span> ; <span style="font-variant:small-caps;">Möller, J.</span> (Hrsg.):
    <i>Bioprocess Systems Engineering Applications in Pharmaceutical Manufacturing</i>,
    <i>Processes : open access journal</i>. Bd. special issue. Basel : MDPI, 2022,
    S. 21–48'
  havard: 'T. Hernández Rodriguez, A. Sekulic, M. Lange-Hegermann, B. Frahm, Designing
    robust biotechnological processes regarding variabilities using multi-objective
    optimization applied to a biopharmaceutical seed train design, in: R. Pörtner,
    J. Möller (Eds.), Bioprocess Systems Engineering Applications in Pharmaceutical
    Manufacturing, MDPI, Basel, 2022: pp. 21–48.'
  ieee: 'T. Hernández Rodriguez, A. Sekulic, M. Lange-Hegermann, and B. Frahm, “Designing
    robust biotechnological processes regarding variabilities using multi-objective
    optimization applied to a biopharmaceutical seed train design,” in <i>Bioprocess
    Systems Engineering Applications in Pharmaceutical Manufacturing</i>, vol. special
    issue, R. Pörtner and J. Möller, Eds. Basel: MDPI, 2022, pp. 21–48. doi: <a href="https://doi.org/10.3390/pr10050883">https://doi.org/10.3390/pr10050883</a>.'
  mla: Hernández Rodriguez, Tanja, et al. “Designing Robust Biotechnological Processes
    Regarding Variabilities Using Multi-Objective Optimization Applied to a Biopharmaceutical
    Seed Train Design.” <i>Bioprocess Systems Engineering Applications in Pharmaceutical
    Manufacturing</i>, edited by Ralf Pörtner and Johannes Möller, vol. special issue,
    MDPI, 2022, pp. 21–48, <a href="https://doi.org/10.3390/pr10050883">https://doi.org/10.3390/pr10050883</a>.
  short: 'T. Hernández Rodriguez, A. Sekulic, M. Lange-Hegermann, B. Frahm, in: R.
    Pörtner, J. Möller (Eds.), Bioprocess Systems Engineering Applications in Pharmaceutical
    Manufacturing, MDPI, Basel, 2022, pp. 21–48.'
  ufg: '<b>Hernández Rodriguez, Tanja u. a.</b>: Designing robust biotechnological
    processes regarding variabilities using multi-objective optimization applied to
    a biopharmaceutical seed train design, in: <i>Pörtner, Ralf/Möller, Johannes (Hgg.)</i>:
    Bioprocess Systems Engineering Applications in Pharmaceutical Manufacturing, Band
    <i>special issue</i>, Basel 2022 (Processes : open access journal),  S. 21–48.'
  van: 'Hernández Rodriguez T, Sekulic A, Lange-Hegermann M, Frahm B. Designing robust
    biotechnological processes regarding variabilities using multi-objective optimization
    applied to a biopharmaceutical seed train design. In: Pörtner R, Möller J, editors.
    Bioprocess Systems Engineering Applications in Pharmaceutical Manufacturing. Basel:
    MDPI; 2022. p. 21–48. (Processes : open access journal; vol. special issue).'
date_created: 2023-08-08T12:58:36Z
date_updated: 2023-08-16T09:24:16Z
department:
- _id: DEP4000
doi: https://doi.org/10.3390/pr10050883
editor:
- first_name: Ralf
  full_name: Pörtner, Ralf
  last_name: Pörtner
- first_name: Johannes
  full_name: Möller, Johannes
  last_name: Möller
keyword:
- Gaussian processes
- Bayes optimization
- Pareto optimization
- multi-objective
- cell culture
- seed train
language:
- iso: eng
page: 21-48
place: Basel
publication: Bioprocess Systems Engineering Applications in Pharmaceutical Manufacturing
publication_identifier:
  eisbn:
  - 978-3-0365-5209-5
  eissn:
  - 2227-9717
  isbn:
  - 978-3-0365-5210-1
publication_status: published
publisher: MDPI
quality_controlled: '1'
series_title: 'Processes : open access journal'
status: public
title: Designing robust biotechnological processes regarding variabilities using multi-objective
  optimization applied to a biopharmaceutical seed train design
type: book_chapter
user_id: '83781'
volume: special issue
year: '2022'
...
---
_id: '3349'
abstract:
- lang: eng
  text: "Model-based concepts and simulation techniques in combination with digital
    tools emerge as a key to explore the full potential of biopharmaceutical production
    processes, which contain several challenging development and process steps. One
    of these steps is the time- and cost-intensive cell proliferation process (also
    called seed train) to increase cell number from cell thawing up to production
    scale. Challenges like complex cell metabolism, batch-to-batch variation, variabilities
    in cell behavior, and influences of changes in cultivation conditions necessitate
    adequate digital solutions to provide information about the current and near future
    process state to derive correct process decisions.\r\nFor this purpose digital
    seed train twins have proved to be efficient, which digitally display the time-dependent
    behavior of important process variables based on mathematical models, strategies,
    and adaption procedures.\r\nThis chapter will outline the needs for digitalization
    of seed trains, the construction of a digital seed train twin, the role of parameter
    estimation, and different statistical methods within this context, which are applicable
    to several problems in the field of bioprocessing. The results of a case study
    are presented to illustrate a Bayesian approach for parameter estimation and prediction
    of an industrial cell culture seed train for seed train digitalization."
author:
- first_name: Tanja
  full_name: Hernández Rodriguez, Tanja
  id: '52466'
  last_name: Hernández Rodriguez
- first_name: Björn
  full_name: Frahm, Björn
  id: '45666'
  last_name: Frahm
citation:
  ama: 'Hernández Rodriguez T, Frahm B. Digital Seed Train Twins and Statistical Methods.
    In: Herwig C, Pörtner R, Möller J, eds. <i>Digital Twins Tools and Concepts for
    Smart Biomanufacturing</i>. Vol 176. Advances in Biochemical Engineering/Biotechnology.
    Springer; 2021:97-131. doi:<a href="https://doi.org/10.1007/10_2020_137">https://doi.org/10.1007/10_2020_137</a>'
  apa: Hernández Rodriguez, T., &#38; Frahm, B. (2021). Digital Seed Train Twins and
    Statistical Methods. In C. Herwig, R. Pörtner, &#38; J. Möller (Eds.), <i>Digital
    Twins Tools and Concepts for Smart Biomanufacturing</i> (Vol. 176, pp. 97–131).
    Springer. <a href="https://doi.org/10.1007/10_2020_137">https://doi.org/10.1007/10_2020_137</a>
  bjps: '<b>Hernández Rodriguez T and Frahm B</b> (2021) Digital Seed Train Twins
    and Statistical Methods. In Herwig C, Pörtner R and Möller J (eds), <i>Digital
    Twins Tools and Concepts for Smart Biomanufacturing</i>, vol. 176. Berlin, Heidelberg:
    Springer, pp. 97–131.'
  chicago: 'Hernández Rodriguez, Tanja, and Björn Frahm. “Digital Seed Train Twins
    and Statistical Methods.” In <i>Digital Twins Tools and Concepts for Smart Biomanufacturing</i>,
    edited by Christoph  Herwig, Ralf  Pörtner, and Johannes  Möller, 176:97–131.
    Advances in Biochemical Engineering/Biotechnology. Berlin, Heidelberg: Springer,
    2021. <a href="https://doi.org/10.1007/10_2020_137">https://doi.org/10.1007/10_2020_137</a>.'
  chicago-de: 'Hernández Rodriguez, Tanja und Björn Frahm. 2021. Digital Seed Train
    Twins and Statistical Methods. In: <i>Digital Twins Tools and Concepts for Smart
    Biomanufacturing</i>, hg. von Christoph  Herwig, Ralf  Pörtner, und Johannes  Möller,
    176:97–131. Advances in Biochemical Engineering/Biotechnology. Berlin, Heidelberg:
    Springer. doi:<a href="https://doi.org/10.1007/10_2020_137">https://doi.org/10.1007/10_2020_137</a>,
    .'
  din1505-2-1: '<span style="font-variant:small-caps;">Hernández Rodriguez, Tanja</span>
    ; <span style="font-variant:small-caps;">Frahm, Björn</span>: Digital Seed Train
    Twins and Statistical Methods. In: <span style="font-variant:small-caps;">Herwig,
    C.</span> ; <span style="font-variant:small-caps;">Pörtner, R.</span> ; <span
    style="font-variant:small-caps;">Möller, J.</span> (Hrsg.): <i>Digital Twins Tools
    and Concepts for Smart Biomanufacturing</i>, <i>Advances in Biochemical Engineering/Biotechnology</i>.
    Bd. 176. Berlin, Heidelberg : Springer, 2021, S. 97–131'
  havard: 'T. Hernández Rodriguez, B. Frahm, Digital Seed Train Twins and Statistical
    Methods, in: C. Herwig, R. Pörtner, J. Möller (Eds.), Digital Twins Tools and
    Concepts for Smart Biomanufacturing, Springer, Berlin, Heidelberg, 2021: pp. 97–131.'
  ieee: 'T. Hernández Rodriguez and B. Frahm, “Digital Seed Train Twins and Statistical
    Methods,” in <i>Digital Twins Tools and Concepts for Smart Biomanufacturing</i>,
    vol. 176, C. Herwig, R. Pörtner, and J. Möller, Eds. Berlin, Heidelberg: Springer,
    2021, pp. 97–131. doi: <a href="https://doi.org/10.1007/10_2020_137">https://doi.org/10.1007/10_2020_137</a>.'
  mla: Hernández Rodriguez, Tanja, and Björn Frahm. “Digital Seed Train Twins and
    Statistical Methods.” <i>Digital Twins Tools and Concepts for Smart Biomanufacturing</i>,
    edited by Christoph  Herwig et al., vol. 176, Springer, 2021, pp. 97–131, <a href="https://doi.org/10.1007/10_2020_137">https://doi.org/10.1007/10_2020_137</a>.
  short: 'T. Hernández Rodriguez, B. Frahm, in: C. Herwig, R. Pörtner, J. Möller (Eds.),
    Digital Twins Tools and Concepts for Smart Biomanufacturing, Springer, Berlin,
    Heidelberg, 2021, pp. 97–131.'
  ufg: '<b>Hernández Rodriguez, Tanja/Frahm, Björn</b>: Digital Seed Train Twins and
    Statistical Methods, in: <i>Herwig, Christoph/Pörtner, Ralf/Möller, Johannes (Hgg.)</i>:
    Digital Twins Tools and Concepts for Smart Biomanufacturing, Bd. 176, Berlin,
    Heidelberg 2021 (Advances in Biochemical Engineering/Biotechnology),  S. 97–131.'
  van: 'Hernández Rodriguez T, Frahm B. Digital Seed Train Twins and Statistical Methods.
    In: Herwig C, Pörtner R, Möller J, editors. Digital Twins Tools and Concepts for
    Smart Biomanufacturing. Berlin, Heidelberg: Springer; 2021. p. 97–131. (Advances
    in Biochemical Engineering/Biotechnology; vol. 176).'
date_created: 2020-08-19T07:14:11Z
date_updated: 2023-08-16T06:48:35Z
department:
- _id: DEP4021
doi: https://doi.org/10.1007/10_2020_137
editor:
- first_name: 'Christoph '
  full_name: 'Herwig, Christoph '
  last_name: Herwig
- first_name: 'Ralf '
  full_name: 'Pörtner, Ralf '
  last_name: Pörtner
- first_name: 'Johannes '
  full_name: 'Möller, Johannes '
  last_name: Möller
intvolume: '       176'
keyword:
- Bayes
- Digital twin
- Parameter estimation
- Seed train
- Uncertainty
language:
- iso: eng
page: 97–131
place: Berlin, Heidelberg
publication: Digital Twins Tools and Concepts for Smart Biomanufacturing
publication_identifier:
  eisbn:
  - 978-3-030-71660-8
  eissn:
  - 1616-8542
  isbn:
  - 978-3-030-71659-2
  issn:
  - 0724-6145
publication_status: published
publisher: Springer
quality_controlled: '1'
series_title: Advances in Biochemical Engineering/Biotechnology
status: public
title: Digital Seed Train Twins and Statistical Methods
type: book_chapter
user_id: '83781'
volume: 176
year: '2021'
...
---
_id: '4327'
abstract:
- lang: eng
  text: In ever changing world, the industrial systems become more and more complex.
    Machine feedback in the form of alarms and notifications, due to its growing volume,
    becomes overwhelming for the operator. In addition, expectations in relation to
    system availability are growing as well. Therefore, there exists strong need for
    new solutions guaranteeing fast troubleshooting of problems that arise during
    system operation. The approach proposed in this study uses advantages of the Asset
    Administration Shell, machine learning, and human-machine interaction in order
    to create the assistance system which holistically addresses the issue of troubleshooting
    complex industrial systems.
author:
- first_name: Dorota
  full_name: Lang, Dorota
  id: '68941'
  last_name: Lang
- first_name: Paul
  full_name: Wunderlich, Paul
  id: '52317'
  last_name: Wunderlich
- first_name: Mario
  full_name: Heinz, Mario
  id: '68913'
  last_name: Heinz
- first_name: Lukasz
  full_name: Wisniewski, Lukasz
  id: '1710'
  last_name: Wisniewski
- first_name: Jürgen
  full_name: Jasperneite, Jürgen
  id: '1899'
  last_name: Jasperneite
- first_name: Oliver
  full_name: Niggemann, Oliver
  id: '10876'
  last_name: Niggemann
- first_name: Carsten
  full_name: Röcker, Carsten
  id: '61525'
  last_name: Röcker
citation:
  ama: 'Lang D, Wunderlich P, Heinz M, et al. Assistance System to Support Troubleshooting
    of Complex Industrial Systems. In: <i>14th IEEE International Workshop on Factory
    Communication Systems (WFCS)</i>. Piscataway, NJ: IEEE; 2018. doi:<a href="https://doi.org/10.1109/WFCS.2018.8402380">10.1109/WFCS.2018.8402380</a>'
  apa: 'Lang, D., Wunderlich, P., Heinz, M., Wisniewski, L., Jasperneite, J., Niggemann,
    O., &#38; Röcker, C. (2018). Assistance System to Support Troubleshooting of Complex
    Industrial Systems. In <i>14th IEEE International Workshop on Factory Communication
    Systems (WFCS)</i>. Piscataway, NJ: IEEE. <a href="https://doi.org/10.1109/WFCS.2018.8402380">https://doi.org/10.1109/WFCS.2018.8402380</a>'
  bjps: '<b>Lang D <i>et al.</i></b> (2018) Assistance System to Support Troubleshooting
    of Complex Industrial Systems. <i>14th IEEE International Workshop on Factory
    Communication Systems (WFCS)</i>. Piscataway, NJ: IEEE.'
  chicago: 'Lang, Dorota, Paul Wunderlich, Mario Heinz, Lukasz Wisniewski, Jürgen
    Jasperneite, Oliver Niggemann, and Carsten Röcker. “Assistance System to Support
    Troubleshooting of Complex Industrial Systems.” In <i>14th IEEE International
    Workshop on Factory Communication Systems (WFCS)</i>. Piscataway, NJ: IEEE, 2018.
    <a href="https://doi.org/10.1109/WFCS.2018.8402380">https://doi.org/10.1109/WFCS.2018.8402380</a>.'
  chicago-de: 'Lang, Dorota, Paul Wunderlich, Mario Heinz, Lukasz Wisniewski, Jürgen
    Jasperneite, Oliver Niggemann und Carsten Röcker. 2018. Assistance System to Support
    Troubleshooting of Complex Industrial Systems. In: <i>14th IEEE International
    Workshop on Factory Communication Systems (WFCS)</i>. Piscataway, NJ: IEEE. doi:<a
    href="https://doi.org/10.1109/WFCS.2018.8402380,">10.1109/WFCS.2018.8402380,</a>
    .'
  din1505-2-1: '<span style="font-variant:small-caps;">Lang, Dorota</span> ; <span
    style="font-variant:small-caps;">Wunderlich, Paul</span> ; <span style="font-variant:small-caps;">Heinz,
    Mario</span> ; <span style="font-variant:small-caps;">Wisniewski, Lukasz</span>
    ; <span style="font-variant:small-caps;">Jasperneite, Jürgen</span> ; <span style="font-variant:small-caps;">Niggemann,
    Oliver</span> ; <span style="font-variant:small-caps;">Röcker, Carsten</span>:
    Assistance System to Support Troubleshooting of Complex Industrial Systems. In:
    <i>14th IEEE International Workshop on Factory Communication Systems (WFCS)</i>.
    Piscataway, NJ : IEEE, 2018'
  havard: 'D. Lang, P. Wunderlich, M. Heinz, L. Wisniewski, J. Jasperneite, O. Niggemann,
    C. Röcker, Assistance System to Support Troubleshooting of Complex Industrial
    Systems, in: 14th IEEE International Workshop on Factory Communication Systems
    (WFCS), IEEE, Piscataway, NJ, 2018.'
  ieee: D. Lang <i>et al.</i>, “Assistance System to Support Troubleshooting of Complex
    Industrial Systems,” in <i>14th IEEE International Workshop on Factory Communication
    Systems (WFCS)</i>, Imperia, Italy , 2018.
  mla: Lang, Dorota, et al. “Assistance System to Support Troubleshooting of Complex
    Industrial Systems.” <i>14th IEEE International Workshop on Factory Communication
    Systems (WFCS)</i>, IEEE, 2018, doi:<a href="https://doi.org/10.1109/WFCS.2018.8402380">10.1109/WFCS.2018.8402380</a>.
  short: 'D. Lang, P. Wunderlich, M. Heinz, L. Wisniewski, J. Jasperneite, O. Niggemann,
    C. Röcker, in: 14th IEEE International Workshop on Factory Communication Systems
    (WFCS), IEEE, Piscataway, NJ, 2018.'
  ufg: '<b>Lang, Dorota et. al. (2018)</b>: Assistance System to Support Troubleshooting
    of Complex Industrial Systems, in: <i>14th IEEE International Workshop on Factory
    Communication Systems (WFCS)</i>, Piscataway, NJ.'
  van: 'Lang D, Wunderlich P, Heinz M, Wisniewski L, Jasperneite J, Niggemann O, et
    al. Assistance System to Support Troubleshooting of Complex Industrial Systems.
    In: 14th IEEE International Workshop on Factory Communication Systems (WFCS).
    Piscataway, NJ: IEEE; 2018.'
conference:
  end_date: 2018-06-15
  location: 'Imperia, Italy '
  name: 14th IEEE International Workshop on Factory Communication Systems (WFCS)
  start_date: 2018-06-13
date_created: 2021-01-08T08:26:30Z
date_updated: 2023-03-15T13:49:52Z
department:
- _id: DEP5023
- _id: DEP5019
doi: 10.1109/WFCS.2018.8402380
keyword:
- Maintenance engineering
- Adaptation models
- Machine learning
- Data models
- Standards
- Software
- Bayes methods
language:
- iso: eng
main_file_link:
- open_access: '1'
oa: '1'
place: Piscataway, NJ
publication: 14th IEEE International Workshop on Factory Communication Systems (WFCS)
publication_identifier:
  eisbn:
  - 978-1-5386-1066-4
publication_status: published
publisher: IEEE
status: public
title: Assistance System to Support Troubleshooting of Complex Industrial Systems
type: conference
user_id: '45673'
year: 2018
...