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Model Based Scale up of Depth Filtration for Clarification of Monoclonal Antibodies (mAb) Cell Culture Harvest Vishwanath S Hebbi 1 , Sandeep Hadpe 1 , Muthukumar Sampath 1 , Souhardhya Roy 1 , Anurag S Rathore 1,* 1 Indian Institute of Technology Delhi, New Delhi, India * Corresponding author. Tel: +91-11-26591098, Fax: +91-11-26581120, E-mail: [email protected] Depth filtration is generally used post centrifugation for reducing Normalized Turbidity Units (NTU), HCP and HCDNA levels. The operation of depth filtration and its scale up is straightforward. However, due to various issues such as fouling and variability in feed, 15-20% of area is considered in excess of calculated area during the scale up. Therefore it is important to know the plugging behavior of depth filters and their effect on scale up. The present work targets this issue by proposing a model based scale up wherein the different fouling mechanisms are investigated for constant flow depth filtration. Interestingly, amongst the various models investigated, combined model explains the fouling mechanism and the corresponding parameters of the same model are used for scale up. The model based scale up provides insights in deciding the accurate filter area during scale up. Abstract Methodology Filtrate from Primary filter D0HC 30SP B1HC 90ZA Cell culture Secondary Filtration Primary Filtration Empirical modelling Model based scale up Validation scale up trails Empirical modelling-Primary filtration Observations 0 2 4 6 8 10 12 14 0 250 500 750 1000 1250 1500 1750 P/P 0 Time, t (s) D0HC Experimental Cake Intermediate Complete Standard Cake Complete Cake Intermediate Complete Standrd Intermediate Standard Cake Standard 0 5 10 15 20 25 0 250 500 750 1000 1250 1500 P/P 0 Time, t (s) 30SP Figure 1. Modelling of primary filtration for D0HC and 30SP Model Plugging parameter Error Kb Kc Ki Ks SSE RMSE Cake 1.19E+06 13.00 1.62 Intermediate 22.43 3.93 0.89 Complete 5.18E-04 79.70 3.99 Standard 11.41 39.02 2.79 Cake Complete 2.44E-04 5.67E+05 1.58 0.63 Cake Intermediate 3.18E+05 7.56 1.01 0.50 Complete Standard 1.00E-04 11.60 32.06 2.83 Intermediate Standard 22.44 0.00 4.99 1.12 Cake Standard 4.79E+05 11.62 2.81 0.96 Table1. Model parameters of primary filtration for D0HC Model Plugging parameter Error Kb Kc Ki Ks SSE RMSE Cake 2.98E+06 53.68 3.28 Intermediate 31.62 51.56 3.21 Complete 5.36E-04 510.50 10.10 Standard 13.63 311.90 8.83 Cake Complete 2.38E-04 1.49E+06 5.57 1.36 Cake Intermediate 9.74E+05 7.41 3.34 1.06 Complete Standard 1.00E-04 14.29 270.00 8.22 Intermediate Standard 21.50 0.91 220.80 7.43 Cake Standard 1.61E+06 14.12 13.65 1.85 Table2. Model parameters of primary filtration for 30SP Empirical modelling-Secondary filtration 0 5 10 15 20 0 250 500 750 1000 1250 1500 P/P 0 Time, t (s) B1HC Experimental Cake Intermediate Complete Standard Cake Complete Cake Intermediate Complete Standrd Intermediate Standard Cake Standard 0 5 10 15 20 25 0 400 800 1200 1600 2000 2400 P/P 0 Time, t (s) 90ZA Table 3. Model parameters of secondary filtration for B1HC Model Plugging parameter Error Kb Kc Ki Ks SSE RMSE Cake 8.16E+06 13.67 1.65 Intermediate 18.37 0.24 0.22 Complete 5.03E-04 17.84 1.89 Standard 10.85 4.78 0.98 Cake Complete 3.38E-04 2.27E+05 0.29 0.31 Cake Intermediate 8.85E+04 10.59 0.23 0.28 Complete Standard 1.00E-04 10.36 3.37 0.82 Intermediate Standard 17.52 0.24 0.21 0.23 Cake Standard 1.23E+05 11.23 0.46 0.39 Model Plugging parameter Error Kb Kc Ki Ks SSE RMSE Cake 7.74E+05 8.28 1.09 Intermediate 15.80 1.05 0.39 Complete 3.74E-04 43.21 2.49 Standard 8.90 16.93 1.56 Cake Complete 1.90E-04 3.45E+05 0.41 0.29 Cake Intermediate 2.09E+05 5.81 0.25 0.22 Complete Standard 1.00E-04 8.12 13.87 1.41 Intermediate Standard 15.66 0.00 1.34 0.47 Cake Standard 2.90E+05 8.64 0.50 0.29 Scale up strategy Filter Small Large Volume (L) area (m 2 ) Volume (L) area (m 2 ) 30SP 0.35L 270L 270L 1.9 90ZA 0.40L 350L 350L 1.4 Figure 2. Modelling of Secondary filtration for B1HC and 90ZA Table 4. Model parameters of secondary filtration for 90ZA Scale up validation 0 2 4 6 8 10 12 14 16 0 2000 4000 6000 P/P 0 Time, t (s) 30SP Experimental Cake Intermediate Complete Standard Cake Complete Cake Intermediate Complete Standrd Intermediate Standard Cake Standard 0 5 10 15 20 25 30 0 2000 4000 6000 8000 P/P 0 Time, t (s) 90ZA Model Plugging parameter Error Kb Kc Ki Ks SSE RMSE Cake 1.59E+06 34.15 1.76 Intermediate 14.69 0.70 0.25 Complete 1.77E-04 34.99 1.78 Standard 8.58 6.72 0.78 Cake Complete 1.27E-04 3.56E+05 0.86 0.29 Cake Intermediate 4.28E+04 11.62 0.95 0.31 Complete Standard 1.00E-05 8.30 8.82 0.90 Intermediate Standard 12.70 0.57 0.87 0.29 Cake Standard 2.86E+05 8.06 0.80 0.28 Model Plugging parameter Error Kb Kc Ki Ks SSE RMSE Cake 2.88E+06 45.72 2.32 Intermediate 15.53 196.00 4.43 Complete 1.47E-04 10.35 1.71 Standard 7.50 602.00 8.18 Cake Complete 4.95E-05 1.80E+06 13.68 1.23 Cake Intermediate 1.99E+06 1.40 6.96 0.88 Complete Standard 1.00E-04 4.43 679.20 8.24 Intermediate Standard 1.46 5.65 792.20 9.38 Cake Standard 2.12E+06 6.43 24.99 1.67 30SP and 90ZA are found to be the best filters for clarification of cell culture broth Cake intermediate model fits the experimental data with least error for both primary as well as secondary filtraions Plugging behavior changed for primart filtration at 1.6 m 2 scale NTU Filtrate (ml) D0HC 354 300 30SP 130 350 NTU Filtrate (ml) B1HC 3.8 350 90ZA 1.8 350 Conclusion Depth filters are useful in clarification od mammalian cell culture broth Combined models demonstrates the plugging mechanism in depth filtrations Model parameters can be useful in sizing of depth filters Future work Incorporation of flow behavior terms into scale up strategy at larger scale filtration Generalization of scale up criteria for depth filtration To study the effect of other variables such as cell viability, NTU variation in the load on plugging mechanism Table 1. Performance of primary and secondary filters References 1. Yavorsky, David, et al. "The clarification of bioreactor cell cultures for biopharmaceuticals." Pharmaceutical technology 27.3 (2003): 62-77. 2. Ho, WS Winston, and Kamalesh K. Sirkar, eds. Membrane handbook. Springer Science & Business Media, 1992. Figure 3. Scheme for scale up for depth ffiltration Time versus pressure data is generated for filter Determination of plugging parameters V small and V large ,Time Assume area A large and fix P max Calculate P from model equation If p calc =P max Yes Assumed area is the final area Assume diff value for A large No Table 5. Scale up result Figure 4. Validation of scale up for 30SP and 90ZA Table 6. Model parameters for scale up run for 30SP Table 7. Model parameters for scale up run for 90ZA

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Page 1: BPI 2015 Hebbi

Model Based Scale up of Depth Filtration for Clarification of

Monoclonal Antibodies (mAb) Cell Culture Harvest

Vishwanath S Hebbi1, Sandeep Hadpe1, Muthukumar Sampath1, Souhardhya Roy1, Anurag S Rathore1,*

1Indian Institute of Technology Delhi, New Delhi, India

* Corresponding author. Tel: +91-11-26591098, Fax: +91-11-26581120, E-mail: [email protected]

Depth filtration is generally used post centrifugation for reducing Normalized

Turbidity Units (NTU), HCP and HCDNA levels. The operation of depth filtration

and its scale up is straightforward. However, due to various issues such as

fouling and variability in feed, 15-20% of area is considered in excess of

calculated area during the scale up. Therefore it is important to know the

plugging behavior of depth filters and their effect on scale up.

The present work targets this issue by proposing a model based scale up

wherein the different fouling mechanisms are investigated for constant flow

depth filtration. Interestingly, amongst the various models investigated,

combined model explains the fouling mechanism and the corresponding

parameters of the same model are used for scale up. The model based scale

up provides insights in deciding the accurate filter area during scale up.

Abstract

Methodology

Filtrate from Primary filter

D0HC 30SP B1HC 90ZA

Cell culture

Secondary FiltrationPrimary Filtration

Empirical modelling

Model based scale up

Validation scale up trails

Empirical modelling-Primary filtration

Observations

0

2

4

6

8

10

12

14

0 250 500 750 1000 1250 1500 1750

P/P

0

Time, t (s)

D0HC

Experimental Cake Intermediate

Complete Standard Cake Complete

Cake Intermediate Complete Standrd Intermediate Standard

Cake Standard

0

5

10

15

20

25

0 250 500 750 1000 1250 1500

P/P

0

Time, t (s)

30SP

Figure 1. Modelling of primary filtration for D0HC and 30SP

ModelPlugging parameter Error

Kb Kc Ki Ks SSE RMSE

Cake 1.19E+06 13.00 1.62

Intermediate 22.43 3.93 0.89

Complete 5.18E-04 79.70 3.99

Standard 11.41 39.02 2.79

Cake Complete 2.44E-04 5.67E+05 1.58 0.63

Cake Intermediate 3.18E+05 7.56 1.01 0.50

Complete Standard 1.00E-04 11.60 32.06 2.83

Intermediate Standard 22.44 0.00 4.99 1.12

Cake Standard 4.79E+05 11.62 2.81 0.96

Table1. Model parameters of primary filtration for D0HC

ModelPlugging parameter Error

Kb Kc Ki Ks SSE RMSE

Cake 2.98E+06 53.68 3.28

Intermediate 31.62 51.56 3.21

Complete 5.36E-04 510.50 10.10

Standard 13.63 311.90 8.83

Cake Complete 2.38E-04 1.49E+06 5.57 1.36

Cake Intermediate 9.74E+05 7.41 3.34 1.06

Complete Standard 1.00E-04 14.29 270.00 8.22

Intermediate Standard 21.50 0.91 220.80 7.43

Cake Standard 1.61E+06 14.12 13.65 1.85

Table2. Model parameters of primary filtration for 30SP

Empirical modelling-Secondary filtration

0

5

10

15

20

0 250 500 750 1000 1250 1500

P/P

0

Time, t (s)

B1HC

Experimental Cake Intermediate

Complete Standard Cake Complete

Cake Intermediate Complete Standrd Intermediate Standard

Cake Standard

0

5

10

15

20

25

0 400 800 1200 1600 2000 2400

P/P

0

Time, t (s)

90ZA

Table 3. Model parameters of secondary filtration for B1HC

ModelPlugging parameter Error

Kb Kc Ki Ks SSE RMSE

Cake 8.16E+06 13.67 1.65

Intermediate 18.37 0.24 0.22

Complete 5.03E-04 17.84 1.89

Standard 10.85 4.78 0.98

Cake Complete 3.38E-04 2.27E+05 0.29 0.31

Cake Intermediate 8.85E+04 10.59 0.23 0.28

Complete Standard 1.00E-04 10.36 3.37 0.82

Intermediate Standard 17.52 0.24 0.21 0.23

Cake Standard 1.23E+05 11.23 0.46 0.39

ModelPlugging parameter Error

Kb Kc Ki Ks SSE RMSE

Cake 7.74E+05 8.28 1.09

Intermediate 15.80 1.05 0.39

Complete 3.74E-04 43.21 2.49

Standard 8.90 16.93 1.56

Cake Complete 1.90E-04 3.45E+05 0.41 0.29

Cake Intermediate 2.09E+05 5.81 0.25 0.22

Complete Standard 1.00E-04 8.12 13.87 1.41

Intermediate Standard 15.66 0.00 1.34 0.47

Cake Standard 2.90E+05 8.64 0.50 0.29

Scale up strategy

Filter

Small Large

Volume (L) area (m2) Volume (L) area (m2)

30SP 0.35L 270L 270L 1.9

90ZA 0.40L 350L 350L 1.4

Figure 2. Modelling of Secondary filtration for B1HC and 90ZA

Table 4. Model parameters of secondary filtration for 90ZA

Scale up validation

0

2

4

6

8

10

12

14

16

0 2000 4000 6000

P/P

0

Time, t (s)

30SP

Experimental Cake Intermediate Complete

Standard Cake Complete Cake Intermediate Complete Standrd

Intermediate Standard Cake Standard

0

5

10

15

20

25

30

0 2000 4000 6000 8000

P/P

0

Time, t (s)

90ZA

ModelPlugging parameter Error

Kb Kc Ki Ks SSE RMSE

Cake 1.59E+06 34.15 1.76

Intermediate 14.69 0.70 0.25

Complete 1.77E-04 34.99 1.78

Standard 8.58 6.72 0.78

Cake Complete 1.27E-04 3.56E+05 0.86 0.29

Cake Intermediate 4.28E+04 11.62 0.95 0.31

Complete Standard 1.00E-05 8.30 8.82 0.90

Intermediate Standard 12.70 0.57 0.87 0.29

Cake Standard 2.86E+05 8.06 0.80 0.28

ModelPlugging parameter Error

Kb Kc Ki Ks SSE RMSE

Cake 2.88E+06 45.72 2.32

Intermediate 15.53 196.00 4.43

Complete 1.47E-04 10.35 1.71

Standard 7.50 602.00 8.18

Cake Complete 4.95E-05 1.80E+06 13.68 1.23

Cake Intermediate 1.99E+06 1.40 6.96 0.88

Complete Standard 1.00E-04 4.43 679.20 8.24

Intermediate Standard 1.46 5.65 792.20 9.38

Cake Standard 2.12E+06 6.43 24.99 1.67

• 30SP and 90ZA are found to be the best filters for clarification of cell culture

broth

• Cake intermediate model fits the experimental data with least error for both

primary as well as secondary filtraions

• Plugging behavior changed for primart filtration at 1.6 m2 scale

NTU Filtrate (ml)

D0HC 354 300

30SP 130 350

NTU Filtrate (ml)

B1HC 3.8 350

90ZA 1.8 350

Conclusion

• Depth filters are useful in clarification od mammalian cell culture broth

• Combined models demonstrates the plugging mechanism in depth filtrations

• Model parameters can be useful in sizing of depth filters

Future work

• Incorporation of flow behavior terms into scale up strategy at larger scale

filtration

• Generalization of scale up criteria for depth filtration

• To study the effect of other variables such as cell viability, NTU variation in the

load on plugging mechanism

Table 1. Performance of primary and secondary filters

References

1. Yavorsky, David, et al. "The clarification of bioreactor cell cultures for

biopharmaceuticals." Pharmaceutical technology 27.3 (2003): 62-77.

2. Ho, WS Winston, and Kamalesh K. Sirkar, eds. Membrane handbook.

Springer Science & Business Media, 1992.

Figure 3. Scheme for scale up for depth ffiltration

Time versus pressure data is generated for filter

Determination of plugging parameters

Vsmall and Vlarge ,Time

Assume area Alarge and fix Pmax

Calculate P from model equation

If

pcalc=Pmax

Yes

Assumed area is the final area

Assume diff value for Alarge

No

Table 5. Scale up result

Figure 4. Validation of scale up for 30SP and 90ZA

Table 6. Model parameters for scale up run for 30SP

Table 7. Model parameters for scale up run for 90ZA