QbD based Development and
Characterization of a Cell Culture
Process for Therapeutic Proteins
2015. 06. 09
Green Cross Corp.
Green Cross Research Center
Yong Jae Kim ([email protected])
Agenda
•
Company Introduction
•
QbD and Cell Culture Process Development
1967
1971
1983
1988
1993
2009
Production of the Nation’s First Plasma Fractionation Product
World’s 1st Epidemic Hemorrhagic Fever Vaccine (
Hantavax
)
World’s 2nd Varicella Vaccine (
Suduvax
)
Established as Sudo Microorganism Medical Supplies Co.
Hepatitis B Vaccine for the 3rd Time in the World
(Hepavax
)
Approval of Seasonal Influenza Vaccine (
GC Flu
)
H1N1 Influenza Vaccine (
GreenFlu
)
2009
Construction of Ochang Plant for Bioproducts
2009
Construction of Hwasun Plant for Vaccine Products
2010
Approval of Recombinant Human Factor VIII (
GreenGene F
)
2011
Approval of
Shinbaro
(
Herbal Drug
)
2012
Approval of
Hunterase
(
Hunter Syndrome
)
2013
Construction of R&D Center
Sales Trends
Established
IPO(KOSPI)
Employees
Market Capital
1967
1978
1,500
$1.37B
2013
$807M
2014
$887M
$950M
Operating
Profit
$71.6M
$84.6M
$85.4M
2015(E)
Investment in R&D
2013
2014
2015(E)
$71M
$80M
$91M
8.8%
9.0%
9.6%
R&D Spending
as a % of Sales
Sales Composition
R&D Spending
PD
32.5%
Vx
31.6%
Rx
19.4%
Others
16.5%
Seoul
Ochang Plant
Eumseong Plant
Hwasun Plant
Head Office and R&D Center
Yongin
Facility Overview
- Plasma Fractionation
- Recombinant
- Vaccine (FLU and
Others)
R&D Capability
Recombinant Protein
Vaccine
Antibody Engineering
Plasma Fractionation
What is Quality by Design?
QRM
DOE
MVDA
Statistics
Process
Understanding
Risk Assessment
Design Space
QbD
Systematic
Approach
Overall QbD Approach
European Journal of Pharmaceutics and Biopharmaceutics 81 (2012) 426-437
FDA’s “GMPs for the 21
stCentury” and the PAT initiative
QbD related guidelines
ICH Q8, 9, 10, 11
Systematic approach to Applying QbD
Upstream Process Development
Upstream Manufacturing Process
Cell Culture Process Operating Parameters
Affect Process Performance & Product Quality
Identification of Operational Parameters
•
Potential Critical Process Parameters in Cell Culture Production
–
Temperature
–
pH
–
Agitation
–
Dissolved oxygen
–
Medium constituents
–
Feed type and rate
Combination of Risk Assessment &
Process Development and Characterization
Case I : Flask Inoculum Expansion
•
Project: Therapeutic Proteins I
•
Cell line: CHO-DG44
•
Medium: Commercial Medium
•
Culture vessel: Shake Flask
•
Culture volume: 100mL
Operational Parameters Analysis of the
Flask Inoculum Expansion
Failure Mode Effect Analysis (FMEA)
- Severity of the excursion: S
- Occurrence of the excursion: O
- Detection of the excursion: D
Design of Experiments
Run Initial VCD Temp. CO2 Duration Remarks (E5 cells/mL) (℃) (%) (hr) 1 -1 -1 -1 -1 Resolution IV 4 center points 2 -1 -1 +1 +1 3 -1 +1 -1 +1 4 -1 +1 +1 -1 5 +1 -1 -1 +1 6 +1 -1 +1 -1 7 +1 +1 -1 -1 8 +1 +1 +1 +1 9 0 0 0 0 10 0 0 0 0 11 0 0 0 0 12 0 0 0 0 13 +1 0 0 0 Augmentation Axial points 14 -1 0 0 0 15 0 +1 0 0 16 0 -1 0 0 17 0 0 +1 0 18 0 0 -1 0 19 0 0 0 +1 20 0 0 0 -1
Prediction Formulas
Response Polynomial equation of the response in terms of coded factors
Statistical significance R2 R2 Adj p-Value
VCD CP*+3.23A-6.09B+2.39C+4.41D-0.58AB-4.32B2+2.06C2-3.08BD-4.61D2 0.983 0.970 <0.0001
Viability CP*-10.57B+5.56C-2.2D-7.96B2+5.86BC-2.19BD-4.11D2 0.961 0.942 <0.0001
A: Initial VCD, B: Temp., C: CO2, D: Duration
Design Space (Contour Plots)
Process Development and Characterization
Case II : Production Bioreactor
•
Project: Therapeutic Proteins II
•
Cell line: CHO-DG44
•
Medium: In-house medium
•
Culture system: Glass type STR
•
Culture volume: 2.5 L
Failure Mode Effect Analysis (FMEA)
- Severity of the excursion: S
- Occurrence of the excursion: O
- Detection of the excursion: D
- Risk Priority Number(RPN) = S X O X D
Operational Parameters Analysis of the
Production Bioreactor
Design of Experiments
Run Temp. pH Timing of Prod. shift (℃) (E5 cells/mL) 1 -1 -1 -1 2 -1 -1 +1 3 -1 +1 -1 4 -1 +1 +1 5 +1 -1 -1 6 +1 -1 +1 7 +1 +1 -1 8 +1 +1 +1 9 0 0 0 10 0 0 0 11 0 0 0Response Polynomial equation of the response in terms of coded factors Statistical significance R2 R2 Adj p-Value
Yield CP*-416A+156B+662C-439AB-327AC-435BC–901A2+101ABC 0.998 0.991 0.0074
Impurities#1 CP*+1.07A+1.59B+6.04C+3.25AC+1.61BC-8.79C2 0.937 0.843 0.0216
Impurities#2 CP*+7207A+5040B+2401C+3425AB+967AC+700BC+5116C2 0.994 0.979 0.0026
QA#1 CP*+3.72A+5.90B+1.97C-2.00AB+1.54AC–0.77BC–8.62B2–2.07ABC 0.999 0.999 0.0009
QA#2 CP*+11.91A+7.92B+1.61C–0.88AB+1.55AC-0.02BC-13.39A2–2.51ABC 0.999 0.999 0.0009
QA#3 CP*+8.25A+5.99B –2.11AB–12.54A2 0.915 0.858 0.0023
QA#4 CP*+1.1A+1.13B+0.15C–0.19AB+0.33AC+0.24BC–2.25B2–0.64ABC 0.996 0.982 0.0141
QA#5 CP*+8.68A+4.83B+0.41C+0.44AB–1.52AC+3.36BC–9.07A2–1.23ABC 0.999 0.995 0.0040
A: Production Temp., B: Production pH, C: Timing of production shift CP*: prediction of the response at the Center Point
Regression models for the production
bioreactor responses
X : pH , Y : Temp. X : Prod. shift timing , Y : pH X : Prod. shift timing , Y : Temp.
*NOR: Normal Operational Range