This is the second of two volumes that together provide an overview of the latest advances in the generation and application of digital twins in bioprocess design and optimization. Both processes have undergone significant changes over the past few decades, moving from data-driven approaches into the 21st-century digitalization of the bioprocess industry. Moreover, the high demand for biotechnological products calls for efficient methods during research and development, as well as during tech transfer and routine manufacturing. In this regard, one promising tool is the use of digital twins, which offer a virtual representation of the bioprocess. They reflect the mechanistics of the biological system and the interactions between process parameters, key performance indicators and product quality attributes in the form of a mathematical process model. Furthermore, digital twins allow us to use computer-aided methods to gain an improved process understanding, to test and plan novel bioprocesses, and to efficiently monitor them. This book focuses on the application of digital twins in various contexts, e.g. computer-aided experimental design, seed train prediction, and lifeline analysis. Covering fundamentals as well as applications, the two volumes offers the ideal introduction to the topic for researchers in academy and industry alike.

This is the second of two volumes that together provide an overview of the latest advances in the generation and application of digital twins in bioprocess design and optimization. Both processes have undergone significant changes over the past few decades, moving from data-driven approaches into the 21st-century digitalization of the bioprocess industry. Moreover, the high demand for biotechnological products calls for efficient methods during research and development, as well as during tech transfer and routine manufacturing. In this regard, one promising tool is the use of digital twins, which offer a virtual representation of the bioprocess. They reflect the mechanistics of the biological system and the interactions between process parameters, key performance indicators and product quality attributes in the form of a mathematical process model. Furthermore, digital twins allow us to use computer-aided methods to gain an improved process understanding, to test and plan novel bioprocesses, and to efficiently monitor them. This book focuses on the application of digital twins in various contexts, e.g. computer-aided experimental design, seed train prediction, and lifeline analysis. Covering fundamentals as well as applications, the two volumes offers the ideal introduction to the topic for researchers in academy and industry alike.

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Mitte der 90er Jahre des 20. Jahrhunderts vergab das damalige Bundesministerium f r Gesundheit den Auftrag zur Analyse von Prinzipien der Akkreditierung und Zertifizierung von Gesundheitseinrichtungen im Ausland." Ergebnisse dieser Studie wurden von Swertz et al. (1998) ver ffentlicht. Im Rahmen dieser Studie kristallisierten sich mehrere Gesundheitseinrichtungen heraus, welche bereits seit geraumer Zeit mit Konzepten des Qualit tsmanagements experimentierten - darunter das Kantonale Spital in Grabs. Das Kantonale Spital Grabs, welches der Akutversorgung im schweizerischen Kanton St. Gallen dient, bot einige Jahre lang ein wichtiges Anwendungs- und Analysefeld f r verschiedene Konzepte des Qualit tsmanagements in Gesundheitsorganisationen. Sie wurden bereits aus dem Blickwinkel des Anwenders (M ller et al. 2003) und auch im wissenschaftlichen Kontext (M ller et al. 2005) dargelegt. Das vorliegende Buch steht in einer Entwicklungslinie mit den o.g. Werken und markiert den vorerst letzten Beitrag dieser kleinen Schriftenreihe. Darin wurde am Beispiel des Prozesskriteriums aufgezeigt, welche Erkenntnisse eine systematische Meta-Analyse von Anwendungen des Qualit tsmanagements in Gesundheitseinrichtungen hervor bringen kann. Es bleibt dem Leser berlassen, die gew hlte Vorgehensweise auf andere Kriterien des EFQM-Modells oder andere Gesundheitseinrichtungen zu bertragen und daraus ebenfalls Nutzen f r die eigene Organisation zu ziehen.