Preface
This book is divided into two volumes that together provide an overview of the latest
advances in the generation and application of digital twins in the field of bioprocess
design and optimization. Both tasks have undergone significant transformations over
the past few decades, moving from data-driven approaches into the twenty-first
century digitalization of the bioprocess industry. Moreover, the high demand for
biotechnological products calls for smart and efficient methods during research and
development, as well as during tech transfer and routine manufacturing. In this
regard, one promising tool is the application of digital twins, which offer a virtual,
also known as “in silico”, representation of the bioprocess. They mostly reflect the
mechanistic of the biological system and the interactions between process parameters, key performance indicators, and product quality attributes in the form of
mathematical process models of diverse nature. 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 and control them.
In Volume 1 “Digital Twins: Tools and Concepts for Smart Biomanufacturing,” a
special focus is given to the needs, expectations, and challenges of digital twins in
the manufacturing industry. The first chapters focus on the development of digital
twins, their economic assessments and the regulatory aspects during industrial
implementation. Then, different tools incorporating digital twins are discussed for
the design, scale-up, and optimization of bioprocesses.
Volume 2 “Digital Twins: Applications to the Design and Optimization of
Bioprocesses” discusses the usage of digital twins in bioprocesses. First, different
concepts for digital twin-guided design of experiments are shown, followed by
examples for the online implementation of digital twins for bioprocess control
strategies. Then, a broad overview about the challenges and opportunities of the
implementation of digital twins into existing and newly planned operating value
chains are reviewed and their role in the bio(pharma) industry is discussed. In the
end, more insights into bioprocesses hydrodynamics and related cellular responses
are shown focusing on computer-based methods.
v
This book is divided into two volumes that together provide an overview of the latest
advances in the generation and application of digital twins in the field of bioprocess
design and optimization. Both tasks have undergone significant transformations over
the past few decades, moving from data-driven approaches into the twenty-first
century digitalization of the bioprocess industry. Moreover, the high demand for
biotechnological products calls for smart and efficient methods during research and
development, as well as during tech transfer and routine manufacturing. In this
regard, one promising tool is the application of digital twins, which offer a virtual,
also known as “in silico”, representation of the bioprocess. They mostly reflect the
mechanistic of the biological system and the interactions between process parameters, key performance indicators, and product quality attributes in the form of
mathematical process models of diverse nature. 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 and control them.
In Volume 1 “Digital Twins: Tools and Concepts for Smart Biomanufacturing,” a
special focus is given to the needs, expectations, and challenges of digital twins in
the manufacturing industry. The first chapters focus on the development of digital
twins, their economic assessments and the regulatory aspects during industrial
implementation. Then, different tools incorporating digital twins are discussed for
the design, scale-up, and optimization of bioprocesses.
Volume 2 “Digital Twins: Applications to the Design and Optimization of
Bioprocesses” discusses the usage of digital twins in bioprocesses. First, different
concepts for digital twin-guided design of experiments are shown, followed by
examples for the online implementation of digital twins for bioprocess control
strategies. Then, a broad overview about the challenges and opportunities of the
implementation of digital twins into existing and newly planned operating value
chains are reviewed and their role in the bio(pharma) industry is discussed. In the
end, more insights into bioprocesses hydrodynamics and related cellular responses
are shown focusing on computer-based methods.
v