model-assisted DoE (mDoE) can be used as an alternative to decrease the number of
experiments significantly. mDoE enables a knowledge-driven bioprocess development including the definition of a mathematical process model in the early development stages. In this chapter, digital twins and their role in mDoE are discussed.
First, statistical DoE methods are introduced as the basis of mDoE. Second, the
combination of a mathematical process model and DoE into mDoE is examined.
This includes mathematical model structures and a selection scheme for the choice of
DoE designs. Finally, the application of mDoE is discussed in a case study for the
medium optimization in an antibody-producing Chinese hamster ovary cell culture
process.
Graphical Abstract
Model-assisted Design of Experiments
+
Improvement of digital twin
Simulation and
evaluation of DoE
Definition of
DoE
Mathematical
model
Initial
cultivation
Recommendation of
experimental setting
Digital twin
Keywords Cell culture, Experimental design, Fed-batch strategy, Process design
and optimization, Quality by design
Abbreviations
A
Average
Amm
Ammonium
ANOVA Analysis of variance
BBD
Box-Behnken design
CCC
Central composite circumscribed
CCD
Central composite designs
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K. B. Kuchemüller et al.