6. DiMasi JA, Grabowski HG, Hansen RW (2016) Innovation in the pharmaceutical industry: new
estimates of R&D costs. J Health Econ 47:20–33
7. Abt V, Barz T, Cruz-Bournazou MN, Herwig C, Kroll P, Möller J, Pörtner R, Schenkendorf R
(2018) Model-based tools for optimal experiments in bioprocess engineering. Curr Opin Chem
Eng 22:244–252
8. Möller J, Pörtner R (2017) Model-based design of process strategies for cell culture
bioprocesses: state of the art and new perspectives. In: Gowder SJT (ed) New insights into
cell culture technology. InTech
9. Puskeiler R, Kreuzmann J, Schuster C, Didzus K, Bartsch N, Hakemeyer C, Schmidt H,
Jacobs M, Wolf S (2011) The way to a design space for an animal cell culture process according
to Quality by Design (QbD). BMC Proc 5(Suppl 8):P12
10. Abu-Absi SF, Yang L, Thompson P, Jiang C, Kandula S, Schilling B, Shukla AA (2010)
Defining process design space for monoclonal antibody cell culture. Biotechnol Bioeng
106:894–905
11. Möller J, Kuchemüller KB, Steinmetz T, Koopmann KS, Pörtner R (2019) Model-assisted
design of experiments as a concept for knowledge-based bioprocess development. Bioprocess
Biosyst Eng 42:867–882
12. Möller J, Hernández Rodríguez T, Müller J, Arndt L, Kuchemüller KB, Frahm B, Eibl R,
Eibl D, Pörtner R (2020) Model uncertainty-based evaluation of process strategies during scaleup of biopharmaceutical processes. Comput Chem Eng 134:106693
13. Kuchemüller KB, Pörtner R, Möller J (2020) Efficient optimization of process strategies with
model-assisted design of experiments. Methods Mol Biol 2095:235–249
14. Wu P, Ray NG, Shuler ML (1992) A single-cell model for CHO cells. Ann N Y Acad Sci
665:152–187
15. Möhler L, Flockerzi D, Sann H, Reichl U (2005) Mathematical model of influenza A virus
production in large-scale microcarrier culture. Biotechnol Bioeng 90:46–58
16. López-Meza J, Araíz-Hernández D, Carrillo-Cocom LM, López-Pacheco F, Rocha-Pizaña
MDR, Alvarez MM (2016) Using simple models to describe the kinetics of growth, glucose
consumption, and monoclonal antibody formation in naive and infliximab producer CHO cells.
Cytotechnology 68:1287–1300
17. Caramihai M, Severi I (2014) Bioprocess modeling and control. In: Matovic MD (ed) Biomass
now – sustainable growth and use. InTech, Rijeka
18. Provost A, Bastin G (2004) Dynamic metabolic modelling under the balanced growth condition. J Process Control 14:717–728
19. Frahm B, Lane P, Atzert H, Munack A, Hoffmann M, Hass VC, Pörtner R (2002) Adaptive,
model-based control by the open-loop-feedback-optimal (OLFO) controller for the effective
fed-batch cultivation of hybridoma cells. Biotechnol Prog 18:1095–1103
20. Kern S, Platas-Barradas O, Pörtner R, Frahm B (2016) Model-based strategy for cell culture
seed train layout verified at lab scale. Cytotechnology 68:1019–1032
21. Amribt Z, Niu H, Bogaerts P (2013) Macroscopic modelling of overflow metabolism and model
based optimization of hybridoma cell fed-batch cultures. Biochem Eng J 70:196–209
22. Möller J, Korte K, Pörtner R, Zeng A-P, Jandt U (2018) Model-based identification of cellcycle-dependent metabolism and putative autocrine effects in antibody producing CHO cell
culture. Biotechnol Bioeng 115:2996–3008
23. Kroll P, Hofer A, Stelzer IV, Herwig C (2017) Workflow to set up substantial target-oriented
mechanistic process models in bioprocess engineering. Process Biochem 62:24–36
24. Möller J, Bhat K, Riecken K, Pörtner R, Zeng A-P, Jandt U (2019) Process-induced cell cycle
oscillations in CHO cultures: Online monitoring and model-based investigation. Biotechnol
Bioeng 116:2931–2943
25. Kalil SJ, Maugeri F, Rodrigues MI (2000) Response surface analysis and simulation as a tool
for bioprocess design and optimization. Process Biochem 35:539–550
26. Costa AC, Atala DIP, Maugeri F, Maciel R (2001) Factorial design and simulation for the
optimization and determination of control structures for an extractive alcoholic fermentation.
Process Biochem 37:125–137
Digital Twins and Their Role in Model-Assisted Design of Experiments
57
estimates of R&D costs. J Health Econ 47:20–33
7. Abt V, Barz T, Cruz-Bournazou MN, Herwig C, Kroll P, Möller J, Pörtner R, Schenkendorf R
(2018) Model-based tools for optimal experiments in bioprocess engineering. Curr Opin Chem
Eng 22:244–252
8. Möller J, Pörtner R (2017) Model-based design of process strategies for cell culture
bioprocesses: state of the art and new perspectives. In: Gowder SJT (ed) New insights into
cell culture technology. InTech
9. Puskeiler R, Kreuzmann J, Schuster C, Didzus K, Bartsch N, Hakemeyer C, Schmidt H,
Jacobs M, Wolf S (2011) The way to a design space for an animal cell culture process according
to Quality by Design (QbD). BMC Proc 5(Suppl 8):P12
10. Abu-Absi SF, Yang L, Thompson P, Jiang C, Kandula S, Schilling B, Shukla AA (2010)
Defining process design space for monoclonal antibody cell culture. Biotechnol Bioeng
106:894–905
11. Möller J, Kuchemüller KB, Steinmetz T, Koopmann KS, Pörtner R (2019) Model-assisted
design of experiments as a concept for knowledge-based bioprocess development. Bioprocess
Biosyst Eng 42:867–882
12. Möller J, Hernández Rodríguez T, Müller J, Arndt L, Kuchemüller KB, Frahm B, Eibl R,
Eibl D, Pörtner R (2020) Model uncertainty-based evaluation of process strategies during scaleup of biopharmaceutical processes. Comput Chem Eng 134:106693
13. Kuchemüller KB, Pörtner R, Möller J (2020) Efficient optimization of process strategies with
model-assisted design of experiments. Methods Mol Biol 2095:235–249
14. Wu P, Ray NG, Shuler ML (1992) A single-cell model for CHO cells. Ann N Y Acad Sci
665:152–187
15. Möhler L, Flockerzi D, Sann H, Reichl U (2005) Mathematical model of influenza A virus
production in large-scale microcarrier culture. Biotechnol Bioeng 90:46–58
16. López-Meza J, Araíz-Hernández D, Carrillo-Cocom LM, López-Pacheco F, Rocha-Pizaña
MDR, Alvarez MM (2016) Using simple models to describe the kinetics of growth, glucose
consumption, and monoclonal antibody formation in naive and infliximab producer CHO cells.
Cytotechnology 68:1287–1300
17. Caramihai M, Severi I (2014) Bioprocess modeling and control. In: Matovic MD (ed) Biomass
now – sustainable growth and use. InTech, Rijeka
18. Provost A, Bastin G (2004) Dynamic metabolic modelling under the balanced growth condition. J Process Control 14:717–728
19. Frahm B, Lane P, Atzert H, Munack A, Hoffmann M, Hass VC, Pörtner R (2002) Adaptive,
model-based control by the open-loop-feedback-optimal (OLFO) controller for the effective
fed-batch cultivation of hybridoma cells. Biotechnol Prog 18:1095–1103
20. Kern S, Platas-Barradas O, Pörtner R, Frahm B (2016) Model-based strategy for cell culture
seed train layout verified at lab scale. Cytotechnology 68:1019–1032
21. Amribt Z, Niu H, Bogaerts P (2013) Macroscopic modelling of overflow metabolism and model
based optimization of hybridoma cell fed-batch cultures. Biochem Eng J 70:196–209
22. Möller J, Korte K, Pörtner R, Zeng A-P, Jandt U (2018) Model-based identification of cellcycle-dependent metabolism and putative autocrine effects in antibody producing CHO cell
culture. Biotechnol Bioeng 115:2996–3008
23. Kroll P, Hofer A, Stelzer IV, Herwig C (2017) Workflow to set up substantial target-oriented
mechanistic process models in bioprocess engineering. Process Biochem 62:24–36
24. Möller J, Bhat K, Riecken K, Pörtner R, Zeng A-P, Jandt U (2019) Process-induced cell cycle
oscillations in CHO cultures: Online monitoring and model-based investigation. Biotechnol
Bioeng 116:2931–2943
25. Kalil SJ, Maugeri F, Rodrigues MI (2000) Response surface analysis and simulation as a tool
for bioprocess design and optimization. Process Biochem 35:539–550
26. Costa AC, Atala DIP, Maugeri F, Maciel R (2001) Factorial design and simulation for the
optimization and determination of control structures for an extractive alcoholic fermentation.
Process Biochem 37:125–137
Digital Twins and Their Role in Model-Assisted Design of Experiments
57