---
_id: '7977'
abstract:
- lang: eng
  text: Kinetic growth models are a useful tool for a better understanding of microalgal
    cultivation and for optimizing cultivation conditions. The evaluation of such
    models requires experimental data that is laborious to generate in bioreactor
    settings. The experimental shake flask setting used in this study allows to run
    12 experiments at the same time, with 6 individual light intensities and light
    durations. This way, 54 biomass data sets were generated for the cultivation of
    the microalgae Chlorella vulgaris. To identify the model parameters, a stepwise
    parameter estimation procedure was applied. First, light-associated model parameters
    were estimated using additional measurements of local light intensities at differ
    heights within medium at different biomass concentrations. Next, substrate related
    model parameters were estimated, using experiments for which biomass and nitrate
    data were provided. Afterwards, growth-related model parameters were estimated
    by application of an extensive cross validation procedure.
author:
- first_name: Fabian
  full_name: Kuhfuß, Fabian
  last_name: Kuhfuß
- first_name: Veronika
  full_name: Gassenmeier, Veronika
  id: '74048'
  last_name: Gassenmeier
- first_name: Sahar
  full_name: Deppe, Sahar
  id: '52121'
  last_name: Deppe
- first_name: George Adrian
  full_name: Ifrim, George Adrian
  id: '73814'
  last_name: Ifrim
- 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: Kuhfuß F, Gassenmeier V, Deppe S, Ifrim GA, Hernández Rodriguez T, Frahm B.
    View on a mechanistic model of Chlorella vulgaris in incubated shake flasks. <i>Bioprocess
    and Biosystems Engineering</i>. 2022;45:15-30. doi:<a href="https://doi.org/10.1007/s00449-021-02627-2">10.1007/s00449-021-02627-2</a>
  apa: Kuhfuß, F., Gassenmeier, V., Deppe, S., Ifrim, G. A., Hernández Rodriguez,
    T., &#38; Frahm, B. (2022). View on a mechanistic model of Chlorella vulgaris
    in incubated shake flasks. <i>Bioprocess and Biosystems Engineering</i>, <i>45</i>,
    15–30. <a href="https://doi.org/10.1007/s00449-021-02627-2">https://doi.org/10.1007/s00449-021-02627-2</a>
  bjps: <b>Kuhfuß F <i>et al.</i></b> (2022) View on a Mechanistic Model of Chlorella
    Vulgaris in Incubated Shake Flasks. <i>Bioprocess and Biosystems Engineering</i>
    <b>45</b>, 15–30.
  chicago: 'Kuhfuß, Fabian, Veronika Gassenmeier, Sahar Deppe, George Adrian Ifrim,
    Tanja Hernández Rodriguez, and Björn Frahm. “View on a Mechanistic Model of Chlorella
    Vulgaris in Incubated Shake Flasks.” <i>Bioprocess and Biosystems Engineering</i>
    45 (2022): 15–30. <a href="https://doi.org/10.1007/s00449-021-02627-2">https://doi.org/10.1007/s00449-021-02627-2</a>.'
  chicago-de: 'Kuhfuß, Fabian, Veronika Gassenmeier, Sahar Deppe, George Adrian Ifrim,
    Tanja Hernández Rodriguez und Björn Frahm. 2022. View on a mechanistic model of
    Chlorella vulgaris in incubated shake flasks. <i>Bioprocess and Biosystems Engineering</i>
    45: 15–30. doi:<a href="https://doi.org/10.1007/s00449-021-02627-2">10.1007/s00449-021-02627-2</a>,
    .'
  din1505-2-1: '<span style="font-variant:small-caps;">Kuhfuß, Fabian</span> ; <span
    style="font-variant:small-caps;">Gassenmeier, Veronika</span> ; <span style="font-variant:small-caps;">Deppe,
    Sahar</span> ; <span style="font-variant:small-caps;">Ifrim, George Adrian</span>
    ; <span style="font-variant:small-caps;">Hernández Rodriguez, Tanja</span> ; <span
    style="font-variant:small-caps;">Frahm, Björn</span>: View on a mechanistic model
    of Chlorella vulgaris in incubated shake flasks. In: <i>Bioprocess and Biosystems
    Engineering</i> Bd. 45. Berlin, Springer (2022), S. 15–30'
  havard: F. Kuhfuß, V. Gassenmeier, S. Deppe, G.A. Ifrim, T. Hernández Rodriguez,
    B. Frahm, View on a mechanistic model of Chlorella vulgaris in incubated shake
    flasks, Bioprocess and Biosystems Engineering. 45 (2022) 15–30.
  ieee: 'F. Kuhfuß, V. Gassenmeier, S. Deppe, G. A. Ifrim, T. Hernández Rodriguez,
    and B. Frahm, “View on a mechanistic model of Chlorella vulgaris in incubated
    shake flasks,” <i>Bioprocess and Biosystems Engineering</i>, vol. 45, pp. 15–30,
    2022, doi: <a href="https://doi.org/10.1007/s00449-021-02627-2">10.1007/s00449-021-02627-2</a>.'
  mla: Kuhfuß, Fabian, et al. “View on a Mechanistic Model of Chlorella Vulgaris in
    Incubated Shake Flasks.” <i>Bioprocess and Biosystems Engineering</i>, vol. 45,
    2022, pp. 15–30, <a href="https://doi.org/10.1007/s00449-021-02627-2">https://doi.org/10.1007/s00449-021-02627-2</a>.
  short: F. Kuhfuß, V. Gassenmeier, S. Deppe, G.A. Ifrim, T. Hernández Rodriguez,
    B. Frahm, Bioprocess and Biosystems Engineering 45 (2022) 15–30.
  ufg: '<b>Kuhfuß, Fabian u. a.</b>: View on a mechanistic model of Chlorella vulgaris
    in incubated shake flasks, in: <i>Bioprocess and Biosystems Engineering</i> 45
    (2022),  S. 15–30.'
  van: Kuhfuß F, Gassenmeier V, Deppe S, Ifrim GA, Hernández Rodriguez T, Frahm B.
    View on a mechanistic model of Chlorella vulgaris in incubated shake flasks. Bioprocess
    and Biosystems Engineering. 2022;45:15–30.
date_created: 2022-05-05T11:28:56Z
date_updated: 2024-08-05T07:07:37Z
department:
- _id: DEP4021
doi: 10.1007/s00449-021-02627-2
intvolume: '        45'
language:
- iso: eng
page: 15-30
place: Berlin
publication: Bioprocess and Biosystems Engineering
publication_identifier:
  eissn:
  - 1615-7605
  issn:
  - '1615-7591 '
publication_status: published
publisher: Springer
quality_controlled: '1'
status: public
title: View on a mechanistic model of Chlorella vulgaris in incubated shake flasks
type: scientific_journal_article
user_id: '83781'
volume: 45
year: '2022'
...
---
_id: '7985'
abstract:
- lang: eng
  text: Bioprocess modeling has become a useful tool for prediction of the process
    future with the aim to deduce operating decisions (e.g. transfer or feeds). Due
    to variabilities, which often occur between and within batches, updating (re-estimation)
    of model parameters is required at certain time intervals (dynamic parameter estimation)
    to obtain reliable predictions. This can be challenging in the presence of low
    sampling frequencies (e.g. every 24 h), different consecutive scales and large
    measurement errors, as in the case of cell culture seed trains. This contribution
    presents an iterative learning workflow which generates and incorporates knowledge
    concerning cell growth during the process by using a moving horizon estimation
    (MHE) approach for updating of model parameters. This estimation technique is
    compared to a classical weighted least squares estimation (WLSE) approach in the
    context of model updating over three consecutive cultivation scales (40–2160 L)
    of an industrial cell culture seed train. Both techniques were investigated regarding
    robustness concerning the aforementioned challenges and the required amount of
    experimental data (estimation horizon). It is shown how the proposed MHE can deal
    with the aforementioned difficulties by the integration of prior knowledge, even
    if only data at two sampling points are available, outperforming the classical
    WLSE approach. This workflow allows to adequately integrate current process behavior
    into the model and can therefore be a suitable component of a digital twin.
author:
- first_name: Tanja
  full_name: Hernández Rodriguez, Tanja
  id: '52466'
  last_name: Hernández Rodriguez
- first_name: Christoph
  full_name: Posch, Christoph
  last_name: Posch
- first_name: Ralf
  full_name: Pörtner, Ralf
  last_name: Pörtner
- first_name: Björn
  full_name: Frahm, Björn
  id: '45666'
  last_name: Frahm
citation:
  ama: Hernández Rodriguez T, Posch C, Pörtner R, Frahm B. Dynamic parameter estimation
    and prediction over consecutive scales, based on moving horizon estimation - applied
    to an industrial cell culture seed train. <i>Bioprocess and Biosystems Engineering</i>.
    2021;44(4):793-808. doi:<a href="https://doi.org/10.1007/s00449-020-02488-1 ">10.1007/s00449-020-02488-1
    </a>
  apa: Hernández Rodriguez, T., Posch, C., Pörtner, R., &#38; Frahm, B. (2021). Dynamic
    parameter estimation and prediction over consecutive scales, based on moving horizon
    estimation - applied to an industrial cell culture seed train. <i>Bioprocess and
    Biosystems Engineering</i>, <i>44</i>(4), 793–808. <a href="https://doi.org/10.1007/s00449-020-02488-1
    ">https://doi.org/10.1007/s00449-020-02488-1 </a>
  bjps: <b>Hernández Rodriguez T <i>et al.</i></b> (2021) Dynamic Parameter Estimation
    and Prediction over Consecutive Scales, Based on Moving Horizon Estimation - Applied
    to an Industrial Cell Culture Seed Train. <i>Bioprocess and Biosystems Engineering</i>
    <b>44</b>, 793–808.
  chicago: 'Hernández Rodriguez, Tanja, Christoph Posch, Ralf Pörtner, and Björn Frahm.
    “Dynamic Parameter Estimation and Prediction over Consecutive Scales, Based on
    Moving Horizon Estimation - Applied to an Industrial Cell Culture Seed Train.”
    <i>Bioprocess and Biosystems Engineering</i> 44, no. 4 (2021): 793–808. <a href="https://doi.org/10.1007/s00449-020-02488-1
    ">https://doi.org/10.1007/s00449-020-02488-1 </a>.'
  chicago-de: 'Hernández Rodriguez, Tanja, Christoph Posch, Ralf Pörtner und Björn
    Frahm. 2021. Dynamic parameter estimation and prediction over consecutive scales,
    based on moving horizon estimation - applied to an industrial cell culture seed
    train. <i>Bioprocess and Biosystems Engineering</i> 44, Nr. 4: 793–808. doi:<a
    href="https://doi.org/10.1007/s00449-020-02488-1 ">10.1007/s00449-020-02488-1
    </a>, .'
  din1505-2-1: '<span style="font-variant:small-caps;">Hernández Rodriguez, Tanja</span>
    ; <span style="font-variant:small-caps;">Posch, Christoph</span> ; <span style="font-variant:small-caps;">Pörtner,
    Ralf</span> ; <span style="font-variant:small-caps;">Frahm, Björn</span>: Dynamic
    parameter estimation and prediction over consecutive scales, based on moving horizon
    estimation - applied to an industrial cell culture seed train. In: <i>Bioprocess
    and Biosystems Engineering</i> Bd. 44. Berlin ; Heidelberg [u.a.], Springer (2021),
    Nr. 4, S. 793–808'
  havard: T. Hernández Rodriguez, C. Posch, R. Pörtner, B. Frahm, Dynamic parameter
    estimation and prediction over consecutive scales, based on moving horizon estimation
    - applied to an industrial cell culture seed train, Bioprocess and Biosystems
    Engineering. 44 (2021) 793–808.
  ieee: 'T. Hernández Rodriguez, C. Posch, R. Pörtner, and B. Frahm, “Dynamic parameter
    estimation and prediction over consecutive scales, based on moving horizon estimation
    - applied to an industrial cell culture seed train,” <i>Bioprocess and Biosystems
    Engineering</i>, vol. 44, no. 4, pp. 793–808, 2021, doi: <a href="https://doi.org/10.1007/s00449-020-02488-1
    ">10.1007/s00449-020-02488-1 </a>.'
  mla: Hernández Rodriguez, Tanja, et al. “Dynamic Parameter Estimation and Prediction
    over Consecutive Scales, Based on Moving Horizon Estimation - Applied to an Industrial
    Cell Culture Seed Train.” <i>Bioprocess and Biosystems Engineering</i>, vol. 44,
    no. 4, 2021, pp. 793–808, <a href="https://doi.org/10.1007/s00449-020-02488-1
    ">https://doi.org/10.1007/s00449-020-02488-1 </a>.
  short: T. Hernández Rodriguez, C. Posch, R. Pörtner, B. Frahm, Bioprocess and Biosystems
    Engineering 44 (2021) 793–808.
  ufg: '<b>Hernández Rodriguez, Tanja u. a.</b>: Dynamic parameter estimation and
    prediction over consecutive scales, based on moving horizon estimation - applied
    to an industrial cell culture seed train, in: <i>Bioprocess and Biosystems Engineering</i>
    44 (2021), H. 4,  S. 793–808.'
  van: Hernández Rodriguez T, Posch C, Pörtner R, Frahm B. Dynamic parameter estimation
    and prediction over consecutive scales, based on moving horizon estimation - applied
    to an industrial cell culture seed train. Bioprocess and Biosystems Engineering.
    2021;44(4):793–808.
date_created: 2022-05-05T13:06:12Z
date_updated: 2023-08-21T07:51:38Z
department:
- _id: DEP4021
doi: '10.1007/s00449-020-02488-1 '
intvolume: '        44'
issue: '4'
keyword:
- Dynamic parameter estimation
- Bioprocess
- Cell cultures
- Moving horizon estimation
- Prior knowledge
language:
- iso: eng
page: 793-808
place: Berlin ; Heidelberg [u.a.]
publication: Bioprocess and Biosystems Engineering
publication_identifier:
  eissn:
  - 1615-7605
  issn:
  - 1615-7591
publication_status: published
publisher: Springer
quality_controlled: '1'
status: public
title: Dynamic parameter estimation and prediction over consecutive scales, based
  on moving horizon estimation - applied to an industrial cell culture seed train
type: scientific_journal_article
user_id: '83781'
volume: 44
year: '2021'
...
---
_id: '7986'
abstract:
- lang: eng
  text: Bioprocess development and optimization are still cost- and time-intensive
    due to the enormous number of experiments involved. In this study, the recently
    introduced model-assisted Design of Experiments (mDoE) concept (Möller et al.
    in Bioproc Biosyst Eng 42(5):867, https://doi.org/10.1007/s00449-019-02089-7,
    2019) was extended and implemented into a software (“mDoE-toolbox”) to significantly
    reduce the number of required cultivations. The application of the toolbox is
    exemplary shown in two case studies with Saccharomyces cerevisiae. In the first
    case study, a fed-batch process was optimized with respect to the pH value and
    linearly rising feeding rates of glucose and nitrogen source. Using the mDoE-toolbox,
    the biomass concentration was increased by 30% compared to previously performed
    experiments. The second case study was the whole-cell biocatalysis of ethyl acetoacetate
    (EAA) to (S)-ethyl-3-hydroxybutyrate (E3HB), for which the feeding rates of glucose,
    nitrogen source, and EAA were optimized. An increase of 80% compared to a previously
    performed experiment with similar initial conditions was achieved for the E3HB
    concentration.
author:
- first_name: André
  full_name: Moser, André
  last_name: Moser
- first_name: Kim B.
  full_name: Kuchemüller, Kim B.
  last_name: Kuchemüller
- first_name: Sahar
  full_name: Deppe, Sahar
  last_name: Deppe
- 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
- first_name: Ralf
  full_name: Pörtner, Ralf
  last_name: Pörtner
- first_name: Volker C.
  full_name: Hass, Volker C.
  last_name: Hass
- first_name: Johannes
  full_name: Möller, Johannes
  last_name: Möller
citation:
  ama: 'Moser A, Kuchemüller KB, Deppe S, et al. Model-assisted DoE software: Optimization
    of growth and biocatalysis in Saccharomyces cerevisiae bioprocesses. <i>Bioprocess
    and Biosystems Engineering</i>. 2021;44(4):683-700. doi:<a href="https://doi.org/10.1007/s00449-020-02478-3">10.1007/s00449-020-02478-3</a>'
  apa: 'Moser, A., Kuchemüller, K. B., Deppe, S., Hernández Rodriguez, T., Frahm,
    B., Pörtner, R., Hass, V. C., &#38; Möller, J. (2021). Model-assisted DoE software:
    Optimization of growth and biocatalysis in Saccharomyces cerevisiae bioprocesses.
    <i>Bioprocess and Biosystems Engineering</i>, <i>44</i>(4), 683–700. <a href="https://doi.org/10.1007/s00449-020-02478-3">https://doi.org/10.1007/s00449-020-02478-3</a>'
  bjps: '<b>Moser A <i>et al.</i></b> (2021) Model-Assisted DoE Software: Optimization
    of Growth and Biocatalysis in Saccharomyces Cerevisiae Bioprocesses. <i>Bioprocess
    and Biosystems Engineering</i> <b>44</b>, 683–700.'
  chicago: 'Moser, André, Kim B. Kuchemüller, Sahar Deppe, Tanja Hernández Rodriguez,
    Björn Frahm, Ralf Pörtner, Volker C. Hass, and Johannes Möller. “Model-Assisted
    DoE Software: Optimization of Growth and Biocatalysis in Saccharomyces Cerevisiae
    Bioprocesses.” <i>Bioprocess and Biosystems Engineering</i> 44, no. 4 (2021):
    683–700. <a href="https://doi.org/10.1007/s00449-020-02478-3">https://doi.org/10.1007/s00449-020-02478-3</a>.'
  chicago-de: 'Moser, André, Kim B. Kuchemüller, Sahar Deppe, Tanja Hernández Rodriguez,
    Björn Frahm, Ralf Pörtner, Volker C. Hass und Johannes Möller. 2021. Model-assisted
    DoE software: Optimization of growth and biocatalysis in Saccharomyces cerevisiae
    bioprocesses. <i>Bioprocess and Biosystems Engineering</i> 44, Nr. 4: 683–700.
    doi:<a href="https://doi.org/10.1007/s00449-020-02478-3">10.1007/s00449-020-02478-3</a>,
    .'
  din1505-2-1: '<span style="font-variant:small-caps;">Moser, André</span> ; <span
    style="font-variant:small-caps;">Kuchemüller, Kim B.</span> ; <span style="font-variant:small-caps;">Deppe,
    Sahar</span> ; <span style="font-variant:small-caps;">Hernández Rodriguez, Tanja</span>
    ; <span style="font-variant:small-caps;">Frahm, Björn</span> ; <span style="font-variant:small-caps;">Pörtner,
    Ralf</span> ; <span style="font-variant:small-caps;">Hass, Volker C.</span> ;
    <span style="font-variant:small-caps;">Möller, Johannes</span>: Model-assisted
    DoE software: Optimization of growth and biocatalysis in Saccharomyces cerevisiae
    bioprocesses. In: <i>Bioprocess and Biosystems Engineering</i> Bd. 44. Berlin ;
    Heidelberg [u.a.], Springer (2021), Nr. 4, S. 683–700'
  havard: 'A. Moser, K.B. Kuchemüller, S. Deppe, T. Hernández Rodriguez, B. Frahm,
    R. Pörtner, V.C. Hass, J. Möller, Model-assisted DoE software: Optimization of
    growth and biocatalysis in Saccharomyces cerevisiae bioprocesses, Bioprocess and
    Biosystems Engineering. 44 (2021) 683–700.'
  ieee: 'A. Moser <i>et al.</i>, “Model-assisted DoE software: Optimization of growth
    and biocatalysis in Saccharomyces cerevisiae bioprocesses,” <i>Bioprocess and
    Biosystems Engineering</i>, vol. 44, no. 4, pp. 683–700, 2021, doi: <a href="https://doi.org/10.1007/s00449-020-02478-3">10.1007/s00449-020-02478-3</a>.'
  mla: 'Moser, André, et al. “Model-Assisted DoE Software: Optimization of Growth
    and Biocatalysis in Saccharomyces Cerevisiae Bioprocesses.” <i>Bioprocess and
    Biosystems Engineering</i>, vol. 44, no. 4, 2021, pp. 683–700, <a href="https://doi.org/10.1007/s00449-020-02478-3">https://doi.org/10.1007/s00449-020-02478-3</a>.'
  short: A. Moser, K.B. Kuchemüller, S. Deppe, T. Hernández Rodriguez, B. Frahm, R.
    Pörtner, V.C. Hass, J. Möller, Bioprocess and Biosystems Engineering 44 (2021)
    683–700.
  ufg: '<b>Moser, André u. a.</b>: Model-assisted DoE software: Optimization of growth
    and biocatalysis in Saccharomyces cerevisiae bioprocesses, in: <i>Bioprocess and
    Biosystems Engineering</i> 44 (2021), H. 4,  S. 683–700.'
  van: 'Moser A, Kuchemüller KB, Deppe S, Hernández Rodriguez T, Frahm B, Pörtner
    R, et al. Model-assisted DoE software: Optimization of growth and biocatalysis
    in Saccharomyces cerevisiae bioprocesses. Bioprocess and Biosystems Engineering.
    2021;44(4):683–700.'
date_created: 2022-05-05T13:10:11Z
date_updated: 2023-08-21T07:55:05Z
department:
- _id: DEP4021
doi: 10.1007/s00449-020-02478-3
intvolume: '        44'
issue: '4'
keyword:
- Biocatalysis
- Monte Carlo methods
- Fed-batch strategy
- Model-assisted design of experiments
- Quality by design
language:
- iso: eng
page: 683-700
place: Berlin ; Heidelberg [u.a.]
publication: Bioprocess and Biosystems Engineering
publication_identifier:
  eissn:
  - 1615-7605
  isbn:
  - 1615-7591
publication_status: published
publisher: Springer
quality_controlled: '1'
status: public
title: 'Model-assisted DoE software: Optimization of growth and biocatalysis in Saccharomyces
  cerevisiae bioprocesses'
type: scientific_journal_article
user_id: '83781'
volume: 44
year: '2021'
...