[{"year":"2021","editor":[{"first_name":"Christoph ","full_name":"Herwig, Christoph ","last_name":"Herwig"},{"last_name":"Pörtner","first_name":"Ralf ","full_name":"Pörtner, Ralf "},{"first_name":"Johannes ","full_name":"Möller, Johannes ","last_name":"Möller"}],"type":"book_chapter","citation":{"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>.","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>.","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>","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).","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>.","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.","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.","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","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-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>, .","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.","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>"},"user_id":"83781","date_updated":"2023-08-16T06:48:35Z","department":[{"_id":"DEP4021"}],"date_created":"2020-08-19T07:14:11Z","doi":"https://doi.org/10.1007/10_2020_137","series_title":"Advances in Biochemical Engineering/Biotechnology","keyword":["Bayes","Digital twin","Parameter estimation","Seed train","Uncertainty"],"page":"97–131","place":"Berlin, Heidelberg","quality_controlled":"1","language":[{"iso":"eng"}],"_id":"3349","publication_identifier":{"eisbn":["978-3-030-71660-8"],"isbn":["978-3-030-71659-2"],"issn":["0724-6145"],"eissn":["1616-8542"]},"volume":176,"intvolume":"       176","title":"Digital Seed Train Twins and Statistical Methods","status":"public","publication":"Digital Twins Tools and Concepts for Smart Biomanufacturing","author":[{"first_name":"Tanja","full_name":"Hernández Rodriguez, Tanja","last_name":"Hernández Rodriguez","id":"52466"},{"id":"45666","full_name":"Frahm, Björn","first_name":"Björn","last_name":"Frahm"}],"publisher":"Springer","publication_status":"published","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."}]}]