27. Parampalli A, Eskridge K, Smith L, Meagher MM, Mowry MC, Subramanian A (2007)
Developement of serum-free media in CHO-DG44 cells using a central composite statistical
design. Cytotechnology 54:57–68
28. Montgomery DC (2013) Design and analysis of experiments.8th edn. Wiley, Hoboken
29. Nasri Nasrabadi MR, Razavi SH (2010) Use of response surface methodology in a fed-batch
process for optimization of tricarboxylic acid cycle intermediates to achieve high levels of
canthaxanthin from Dietzia natronolimnaea HS-1. J Biosci Bioeng 109:361–368
30. Zhang H, Wang H, Liu M, Zhang T, Zhang J, Wang X, Xiang W (2013) Rational development
of a serum-free medium and fed-batch process for a GS-CHO cell line expressing recombinant
antibody. Cytotechnology 65:363–378
31. Horvath B, Mun M, Laird MW (2010) Characterization of a monoclonal antibody cell culture
production process using a quality by design approach. Mol Biotechnol 45:203–206
32. Mandenius C-F, Graumann K, Schultz TW, Premstaller A, Olsson I-M, Petiot E, Clemens C,
Welin M (2009) Quality-by-design for biotechnology-related pharmaceuticals. Biotechnol J
4:600–609
33. Mandenius C-F, Brundin A (2008) Bioprocess optimization using design-of-experiments methodology. Biotechnol Prog 24:1191–1203
34. Duvar S, Hecht V, Finger J, Gullans M, Ziehr H (2013) Developing an upstream process for a
monoclonal antibody including medium optimization. BMC Proc 7
35. Legmann R, Schreyer HB, Combs RG, McCormick EL, Russo AP, Rodgers ST (2009) A
predictive high-throughput scale-down model of monoclonal antibody production in CHO cells.
Biotechnol Bioeng 104:1107–1120
36. Moran EB, McGowan ST, McGuire JM, Frankland JE, Oyebade IA, Waller W, Archer LC,
Morris LO, Pandya J, Nathan SR, Smith L, Cadette ML, Michalowski JT (2000) A systematic
approach to the validation of process control parameters for monoclonal antibody production in
fed-batch culture of a murine myeloma. Biotechnol Bioeng 69:242–255
37. Dubey KK, Behera BK (2011) Statistical optimization of process variables for the production of
an anticancer drug (colchicine derivatives) through fermentation: at scale-up level. New
Biotechnol 28:79–85
38. Kleppmann W (2013) Versuchsplanung: Produkte und Prozesse optimieren.8th edn. Hanser,
München
39. Myers RH, Anderson-Cook C, Montgomery DC (2016) Response surface methodology:
process and product optimization using designed experiments. Wiley, Hoboken
40. Sandadi S, Ensari S, Kearns B (2006) Application of fractional factorial designs to screen active
factors for antibody production by Chinese hamster ovary cells. Biotechnol Prog 22:595–600
41. Siebertz K, van Bebber D, Hochkirchen T (2010) Statistische Versuchsplanung: design of
experiments (DoE). Springer, Berlin
42. Asghar A, Abdul Raman AA, Daud WMAW (2014) A comparison of central composite design
and Taguchi method for optimizing Fenton process. TheScientificWorldJOURNAL
2014:869120
43. Del Castillo E (2007) Process optimization: a statistical approach. Springer, New York
44. Ferreira SLC, Bruns RE, Ferreira HS, Matos GD, David JM, Brandão GC, da Silva EGP,
Portugal LA, dos Reis PS, Souza AS, dos Santos WNL (2007) Box-Behnken design: an
alternative for the optimization of analytical methods. Anal Chim Acta 597:179–186
45. Goel T, Haftka RT, Shyy W, Watson LT (2008) Pitfalls of using a single criterion for selecting
experimental designs. Int J Numer Methods Eng 75:127–155
46. Santner TJ, Williams BJ, Notz WI (2003) The design and analysis of computer experiments.
Springer, New York
47. Lee GM, Kim EJ, Kim NS, Yoon SK, Ahn YH, Song JY (1999) Development of a serum-free
medium for the production of erythropoietin by suspension culture of recombinant Chinese
hamster ovary cells using a statistical design. J Biotechnol 69:85–93
48. Chun C, Heineken K, Szeto D, Ryll T, Chamow S, Chung JD (2003) Application of factorial
design to accelerate identification of CHO growth factor requirements. Biotechnol Prog
19:52–57
58
K. B. Kuchemüller et al.
Developement of serum-free media in CHO-DG44 cells using a central composite statistical
design. Cytotechnology 54:57–68
28. Montgomery DC (2013) Design and analysis of experiments.8th edn. Wiley, Hoboken
29. Nasri Nasrabadi MR, Razavi SH (2010) Use of response surface methodology in a fed-batch
process for optimization of tricarboxylic acid cycle intermediates to achieve high levels of
canthaxanthin from Dietzia natronolimnaea HS-1. J Biosci Bioeng 109:361–368
30. Zhang H, Wang H, Liu M, Zhang T, Zhang J, Wang X, Xiang W (2013) Rational development
of a serum-free medium and fed-batch process for a GS-CHO cell line expressing recombinant
antibody. Cytotechnology 65:363–378
31. Horvath B, Mun M, Laird MW (2010) Characterization of a monoclonal antibody cell culture
production process using a quality by design approach. Mol Biotechnol 45:203–206
32. Mandenius C-F, Graumann K, Schultz TW, Premstaller A, Olsson I-M, Petiot E, Clemens C,
Welin M (2009) Quality-by-design for biotechnology-related pharmaceuticals. Biotechnol J
4:600–609
33. Mandenius C-F, Brundin A (2008) Bioprocess optimization using design-of-experiments methodology. Biotechnol Prog 24:1191–1203
34. Duvar S, Hecht V, Finger J, Gullans M, Ziehr H (2013) Developing an upstream process for a
monoclonal antibody including medium optimization. BMC Proc 7
35. Legmann R, Schreyer HB, Combs RG, McCormick EL, Russo AP, Rodgers ST (2009) A
predictive high-throughput scale-down model of monoclonal antibody production in CHO cells.
Biotechnol Bioeng 104:1107–1120
36. Moran EB, McGowan ST, McGuire JM, Frankland JE, Oyebade IA, Waller W, Archer LC,
Morris LO, Pandya J, Nathan SR, Smith L, Cadette ML, Michalowski JT (2000) A systematic
approach to the validation of process control parameters for monoclonal antibody production in
fed-batch culture of a murine myeloma. Biotechnol Bioeng 69:242–255
37. Dubey KK, Behera BK (2011) Statistical optimization of process variables for the production of
an anticancer drug (colchicine derivatives) through fermentation: at scale-up level. New
Biotechnol 28:79–85
38. Kleppmann W (2013) Versuchsplanung: Produkte und Prozesse optimieren.8th edn. Hanser,
München
39. Myers RH, Anderson-Cook C, Montgomery DC (2016) Response surface methodology:
process and product optimization using designed experiments. Wiley, Hoboken
40. Sandadi S, Ensari S, Kearns B (2006) Application of fractional factorial designs to screen active
factors for antibody production by Chinese hamster ovary cells. Biotechnol Prog 22:595–600
41. Siebertz K, van Bebber D, Hochkirchen T (2010) Statistische Versuchsplanung: design of
experiments (DoE). Springer, Berlin
42. Asghar A, Abdul Raman AA, Daud WMAW (2014) A comparison of central composite design
and Taguchi method for optimizing Fenton process. TheScientificWorldJOURNAL
2014:869120
43. Del Castillo E (2007) Process optimization: a statistical approach. Springer, New York
44. Ferreira SLC, Bruns RE, Ferreira HS, Matos GD, David JM, Brandão GC, da Silva EGP,
Portugal LA, dos Reis PS, Souza AS, dos Santos WNL (2007) Box-Behnken design: an
alternative for the optimization of analytical methods. Anal Chim Acta 597:179–186
45. Goel T, Haftka RT, Shyy W, Watson LT (2008) Pitfalls of using a single criterion for selecting
experimental designs. Int J Numer Methods Eng 75:127–155
46. Santner TJ, Williams BJ, Notz WI (2003) The design and analysis of computer experiments.
Springer, New York
47. Lee GM, Kim EJ, Kim NS, Yoon SK, Ahn YH, Song JY (1999) Development of a serum-free
medium for the production of erythropoietin by suspension culture of recombinant Chinese
hamster ovary cells using a statistical design. J Biotechnol 69:85–93
48. Chun C, Heineken K, Szeto D, Ryll T, Chamow S, Chung JD (2003) Application of factorial
design to accelerate identification of CHO growth factor requirements. Biotechnol Prog
19:52–57
58
K. B. Kuchemüller et al.