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7/13/2010
1
Control Strategy for GlycosylationUsing a QbD Approach:
Monoclonal Antibody with EffectorFunction from the A-Mab Case Study
CMC Forum Washington, DCWorkshop I - CQAs
July , 2010
Presented by Victor Vinci, Eli Lilly
CMC BWG – A-Mab Case StudyWorking Group Members
• Amgen Team: Joseph Phillips (Lead), Bob Kuhn
• Abbott Team: Ed Lundell (Lead), Hans-Juergen Krause, Christine Rinn, Michael Siedler, and Carsten Weber
• Eli Lilly Team: Victor Vinci (Lead), Michael DeFelippis, John R Dobbins, Matthew Hilton, Bruce Meiklejohn, and Guillermo Miroquesada
• Genentech Team: Lynne Krummen (Lead), Sherry Martin-Moe, and Ron Taticek
• GSK Team: Ilse Blumentals (Lead), John Erickson, Alan Gardner, Dave Paolella, Prem Patel, Joseph Rinella, Mary Stawicki, Greg Stockdale
• MedImmune Team: Mark Schenerman (Lead), Sanjeev Ahuja, Laurie Kelliher , Cindy Oliver , Kripa Ram, Orit Scharf, and Gail Wasserman
• Pfizer Team: Leslie Bloom (Lead) and Amit Banerjee, Carol Kirchhoff, Wendy Lambert, Satish Singh
• Facilitator Team: John Berridge, Ken Seamon, and Sam Venugopal
• Plus help from many others
2Vinci/Defelippis - CMC BWG
QbD Case StudyLilly - Company Confidential 2010
3
QbD Development ParadigmCreation of a Control Strategy
Product Quality
Attributes
Criticality
Assessment
1.Quality attributes to be
considered and/or controlled
by manufacturing process
2. Acceptable ranges for
quality attributes to ensure
drug safety and efficacy
Attributes that do not need to
be considered or controlled
by manufacturing process
Safety and
Efficacy Data
Process Targets
for Quality
Attributes
Process
Development and
Characterization
Co
ntin
uo
us P
roce
ss V
erifica
tio
nProcedural Controls
Characterization &
Comparability Testing
Process Parameter
Controls
Specifications
Input Material Controls
In-Process Testing
Process Monitoring
Co
ntr
ol S
tra
teg
y E
lem
en
ts
High Criticality
Attributes
Low Criticality
Attributes
Product Understanding Process Understanding
Clinical
Studies
Animal
Studies
In-Vitro
Studies
Prior
Knowledge
Design
Space
Process Controls
Testing
Vinci/Defelippis - CMC BWG QbD Case
StudyLilly - Company Confidential 2010
7/13/2010
2
Creating a Biotech Case Study:“A-Mab”
• Based on a monoclonal antibody drug substance and drug product– “A-Mab”– Humanized IgG1 (w/ effector function)
– IV Administered Drug (liquid)– Expressed in CHO Cells– Treatment of NHL– Molecule designed to maximize
clinical outcomes and minimize impact on quality attributes (TPP)
• Publically and freely available as a teaching tool for industry and agencies at CASSS or ISPE
Why Monoclonal Antibody?
Represents a significant number of products in development
Good product and process exp. in dev. & manufacture
Reasonable level of complexity
Vinci/Defelippis - CMC BWG
QbD Case Study4Lilly - Company Confidential 2010
CQA Risk Ranking & Filtering ToolA Continuum of Criticality (Tool #1 Ex.)
• Assess relative safety and efficacy risks using two factors:– Impact and Uncertainty used to rank risks
• Impact = impact on safety or efficacy, i.e. consequences– Determined by available knowledge for attribute in question (prior, clinical, etc)
– More severe impact = higher score
• Impact on biological activity, PK/PD, immunogenicity, adverse effects
• Uncertainty = uncertainty that attribute has expected impact– Determined by relevance of knowledge for each attribute
– High uncertainty = high score (no information with variant or published lit. only)
– Low uncertainty = low score (data from material used in clinical trials)
• Severity = risk that attribute impacts safety or efficacy
Severity = Impact x Uncertainty
Vinci/Defelippis - CMC BWG
QbD Case Study5Lilly - Company Confidential 2010
Vinci/Defelippis - CMC BWG QbD Case
StudyLilly - Company Confidential 2010 6
Attribute
Prior
Knowledge
In-vitro
Studies
Non-clinical
Studies
Clinical
Experience
Claimed
Acceptable
Range
Galactose
Content
Clinical
experience of 10-
40% G0 for Y-
Mab, another
antibody with
CDC activity as
part of MOA; no
negative impact
on clinical
outcome
0-100% has
statistical
correlation with
CDC activity with
A-Mab
No animal studies 10-30% 10-40%
aFucosylation 1-11%; Clinical
experience with
X-Mab and Y-
Mab; both X-Mab
and Y-Mab have
ADCC as part of
MOA
A-Mab with 2-
13% afucosylation
tested in ADCC
assay; linear
correlation; 70-
130%
Animal model
available;
modeled material
(15%) shows no
significant
difference from
5%
5-10%;
Phase II and
Phase III
2-13%
Platform and Product Specific Experience
7/13/2010
3
Criticality Ratings for Glycosylation
Attribute Criticality
Aggregation 60
aFucosylation 60
Galactosylation 48
Deamidation 4
Oxidation 12
HCP 36
DNA 6
Protein A 16
C-terminal lysine
variants (charge
variants)
4
Glycoslyation - High Criticality
• Example is for afucosylation
and galactosylation; other
glycan structures require
individual consideration
• Primarily impacted by
production BioRx
• No clearance or modification in
DS
• Not impacted by DP process or
stability
Vinci/Defelippis - CMC BWG QbD
Case Study7Lilly - Company Confidential 2010
Note: Assessment at beginning of development
Experimental DesignProgression of Studies for Production Bioreactor
Prior knowledge and risk assessments inform designed experiments:
• Risk analysis tools guide informed assessments
• Risk assessment links product attributes with parameters
• DOE’s allow understanding of the impact of process parameters and attributes
• Risk assessments are iterative and continue through the lifecycle of product
8Vinci/Defelippis - CMC BWG QbD
Case StudyLilly - Company Confidential 2010
9
Risk Assessment ApproachMultiple Assessments Throughout the
A-Mab Development Lifecycle for Entire Process
Prior Knowledge
Process Understanding
Product Understanding
Process
Development
Risk
Assessment
Process
Characterization
Risk
Assessment
Risk
Assessment
Process
Performance
Verification
Risk
Assessment
Life Cycle
Management
Final Control
Strategy
Process
Parameters
Quality
Attributes
Design Space
Draft Control
Strategy
Process 2
Process 1 2
Vinci/Defelippis - CMC BWG QbD
Case StudyLilly - Company Confidential 2010
You Are Here
7/13/2010
4
10
Example of Risk Assessment ToolApproach to Process Characterization
Aggredates
Fucosylation
Galactosylation
CEX AV
HCP
DNA
N-1 Bioreactor
FeedGlucose Feed
Production
BioreactorHarvest
Medium
Procedures
Temperature
pH
Seed
In Vitro Cell
Age
Seed Density
Viability
Operations
Time of Feeding
Volume of
Feed
Preparation
Concentration
pH
Age
DO
pH
Temperature
CO2
Agitation
Shear/
Mixing
Gas
Transfer
Airflow
Antifoam
Scale
Effects
Amount Delivered
Number of
Feeds
TimingPreparation
[Glucose]
Osmolality
Concentration
Procedures
Age
Duration
Working
Volume
[NaHCO3]
Pre-filtration
hold time
Storage
Temperature
[Antifoam]
Procedures
Age
Storage
Temperature
Pre-filtration hold
time
Filtration
Filtration
# of
Impellers
Vessel
Design
Baffles
Control
Parameters
Operations
Impeller
Design
Sparger Design
Nominal
Volumne
Step 1. Use a Fish-bone (Ishikawa) diagram to identify parameters and attributes that
might affect product quality and process performance
Vinci/Defelippis - CMC BWG QbD Case
StudyLilly - Company Confidential 2010
11
A-Mab: Mid-Development Risk Assessment Approach
Quality Attributes Process Attributes Risk Mitigation
Process Parameter in Production Bioreactor
Agg
rega
te
aFuc
osyl
atio
n
Gal
acto
syla
tion
Dea
mid
atio
n
HC
P
DN
A
Pro
duct
Yie
ld
Via
bilit
y at
Har
vest
Tur
bidi
ty a
t
harv
est
Inoculum Viable Cell Concentr DOE
Inoculum Viability Linkage Studies
Inoculum In Vitro Cell Age EOPC Study
N-1 Bioreactor pH Linkage Studies
N-1 Bioreactor Temperature Linkage Studies
Osmolality DOE
Antifoam Concentration Not Required
Nutrient Concentration in medium
DOE
Medium storage temperature Medium Hold Studies
Medium hold time before filtration
Medium Hold Studies
Medium Filtration Medium Hold Studies
Medium Age Medium Hold Studies
Timing of Feed addition Not Required
Volume of Feed addition DOE
Component Concentration in Feed
DOE
Timing of glucose feed addition
DOE-Indirect
Amount of Glucose fed DOE-Indirect
Dissolved Oxygen DOE
Dissolved Carbon Dioxide DOE
Temperature DOE
pH DOE
Culture Duration (days) DOE
Remnant Glucose Concentration
DOE-Indirect
Potential impact to
significantly affect a
process attribute
such as yield or
viability
Potential impact to QA
with effective control of
parameter or less
robust control
Rank parameters and attributes from Step 1 based on severity of impact and control capability.
Identify interactions to include in DOE studies
Vinci/Defelippis - CMC BWG
QbD Case StudyLilly - Company Confidential 2010
Note: pH is red or
critical at this stage due
to linkage to
glycosylation
MCC BioreactorControl Strategy Elements by System - pH
Raw Materials (Reg/QMS) – vendor qualification; media (or buffer) make-up based on instructions, weight based; pH check post make-up
Equipment (QMS) – bioreactor design (probe type/placement), probe vendor qualification, receipt verification, linked to IQ/OQ and PV for bioreactor
Automation (QMS) – control loop qualified (CSV) and controlled via DCS, alert/action alarms aligned with process, data monitored continuously and archived
DOE and Models (QMS/Reg) – small-scale models use parameter ranges intended for large-scale; confirm during pivotal and commercial tech transfer
In Process/Operations (QMS) – pH probe calibration (pre-run), batch record instructions on how to do daily check and adjustment, data trended
Specification Limits/Tests (Reg/QMS) – Control Strategy in place, validated methods reflecting QbD analytical development
Process Verification/Continuous Monitoring (QMS/Reg) – MVA (PLS) or SPC monitoring of performance over manufacturing lifecycle
Vinci/Defelippis - CMC BWG
QbD Case StudyLilly - Company Confidential 2010 12
7/13/2010
5
13
DOE Studies to Define Design SpaceBringing Together Process and Product Attributes
Example of DOE Results from Screening Study (Process 2). N=20.
3
4
5
Tite
r (g
/L)
3.7
43131
±0.076052
4
6
8
aF
ucosyla
tion
6.4
39933
±0.226948
24
28
32
Gala
cto
syla
tion
(%)
29.2
8939
±0.674582
4e+5
6e+5
8e+5
1e+6
HC
P (
ppm
)
695538
±16518.3
1500
2000
2500
DN
A (
ppm
)
1935.3
43
±89.55908
24
28
32
CE
X %
Acid
ic
Variants
27.6
6898
±0.480814
1.8
2.2
2.6
3.0
Aggre
gate
s
(%)
2.5
15119
±0.03524
34
34.5 35
35.5 36
35
Temperature
(C)
30
40
50
60
70
50
DO (%)
40
60
80
100
120
140
160
100
CO2 (%)
6.6
6.7
6.8
6.9 7
7.1
6.85
pH
.8 1
1.2
1.4
1.6
1.2
[Medium]
(X)
360
380
400
420
440
400
Osmo (mOsm)
9
10
11
12
13
14
15
12
Feed (X)
.7 .8 .9 1
1.1
1.2
1.3
1
IVCC (e6
cells/mL)
15
16
17
18
19
17
Duration
(d)
-0.1 .1 .3 .5 .7 .9
1.1
0.21
Curvature
Prediction Profiler
Vinci/Defelippis - CMC BWG QbD
Case StudyLilly - Company Confidential 2010
Influence of Glycosylation on ADCC and CDC Effector Functions
Vinci/Defelippis - CMC BWG QbD
Case StudyLilly - Company Confidential 2010 14
CQA Linkage to Process Knowledge
afucosylation and galactosylation are assigned as CQAs due to linkage to ADCC and CDC activity and proposed NHL therapeutic need
Analytical characterization method for afucosylation and galactosylation is CE-LIF:
Bioassay development led to a robust assay with a linear correlation between aFuc (2-13%) and ADCC activity (range of 70 – 130%)
Bioassay for CDC showed no impact over the range of galactosylation (10 – 40%)
Ranges of afucosylation and galactosylation can be ensured by control of bioreactor process parameters found to have influence on these structures.
Release testing of Biopotency assay (acceptance criterion 70 – 130%) confirms appropriate product quality.
Vinci/Defelippis - CMC BWG QbD
Case StudyLilly - Company Confidential 2010 15
7/13/2010
6
Continuity of RangesAttributes and Parameters in Study
Vinci/Defelippis - CMC BWG QbD
Case StudyLilly - Company Confidential 2010 16
Levels of CQAs:
CQA Lower Limit Higher LimitAfucosylation (%) 2 13Galactosylation (%) 10 40
Parameter Ranges:Platform (2 liters and at-scale FHD) pH 6.6 – 7.1 (initial set pt*)
Screening Study (Central Composite) pH 6.6 – 7.1 (2 liter)
Design Space Proposal pH 6.6 -7.1 (commercial)
Batch Record (Pivotal and Comm.) pH 6.95 (initial ref pt)
Automation Alarms pH 6.85 lo/pH 6.95 hi alert-control space
pH 6.7 lo/pH 7.1 action-design space*Note that pH variable is set at initial as ref pt and moves through low (base) and high (acid or CO2) control
Moving Toward Design SpaceFollow-up Studies and Analysis
Augment the screening design to enable estimation of a full response surface:
all main effects
two-way interactions
quadratic effects
Additional runs form Central Composite Design (when comb. w/ previous runs):
8 additional runs form full factorial on important parameters.
8 axial points allow to estimate non-linear relationships
4 parameters and 6 QA’s (responses)
8 center points total
17Vinci/Defelippis - CMC BWG QbD
Case StudyLilly - Company Confidential 2010
Response surface model captures all input – output
relationships and is suitable to define the design space
N=40 total bioreactor runs
(4 blocks of 10, ~12 weeks)
18
Develop Multivariate Models to define Design Space
A better way to look at the data:
One model for each CQA: describes
relationships with CPPs
Intersection of all CQA models define the
Design Space
For the production bioreactor the limits of
Design Space are defined by a subset of
CQAs:
Galactosylation
aFucosylation
All other CQAs did not exceed Quality Limits
when process operated within Knowledge
Space & Design Space
*Note that DO and Feed Conc from earlier study
are controlled in same range
HorizVert
Tem perature (C)
DO (%)
CO2 (%)
pH
[Medium] (X)
Osm olality (m Osm)
Feed (X)
IVCC (e6 cells /mL)
Culture Duration (days)
Factor
34.999293
50
100
6.85
1.2
440
12
1
15
Current X
Titer (g/L)
aFucosylation
Galactosylation (%)
HCP (ppm )
DNA (ppm )
CEX % Acidic Variants
Aggregates (%)
Response
0
2
20
15000000
19000
40
3
Contour
4.2
5.7
30.3
490873.2
1498.3
26.7
1.3
Current Y
.
2
20
.
.
20
.
Lo Limit
.
11
40
15000000
.
40
3
Hi Limit
6.6
6.7
6.8
6.9
7
7.1
pH
aFucosylation
Galactosylation (%)
34 34.5 35 35.5 36
Tem perature (C)
Contour Profiler
CO2
Osmolality
< 2%
HorizVert
Tem perature (C)
DO (%)
CO2 (%)
pH
[Medium] (X)
Osm olality (m Osm)
Feed (X)
IVCC (e6 cells /mL)
Culture Duration (days)
Factor
35
50
100
6.85
1.2
360
12
1
15
Current X
Titer (g/L)
aFucosylation
Galactosylation (%)
HCP (ppm )
DNA (ppm )
CEX % Acidic Variants
Aggregates (%)
Response
0
11
40
15000000
19000
40
3
Contour
4.8
8.3
33.4
513494.5
1471.7
28.2
1.3
Current Y
.
2
20
.
.
20
.
Lo Limit
.
11
40
15000000
.
40
3
Hi Limit
6.6
6.7
6.8
6.9
7
7.1
pH
aFucosylation
34 34.5 35 35.5 36
Tem perature (C)
Contour Profiler
>11%
HorizVert
Tem perature (C)
DO (%)
CO2 (%)
pH
[Medium] (X)
Osm olality (m Osm)
Feed (X)
IVCC (e6 cells /mL)
Culture Duration (days)
Factor
35
50
40
6.85
1.2
360
12
1
15
Current X
Titer (g/L)
aFucosylation
Galactosylation (%)
HCP (ppm )
DNA (ppm )
CEX % Acidic Variants
Aggregates (%)
Response
0
11
40
15000000
19000
40
3
Contour
5.2
9.8
36.8
469303.1
1465.4
33.1
1.3
Current Y
.
2
20
.
.
20
.
Lo Limit
.
11
40
15000000
.
40
3
Hi Limit
6.6
6.7
6.8
6.9
7
7.1
pH
aFucosylation
Galactosylation (%)
34 34.5 35 35.5 36
Tem perature (C)
Contour Profiler
HorizVert
Tem perature (C)
DO (%)
CO2 (%)
pH
[Medium] (X)
Osm olality (m Osm)
Feed (X)
IVCC (e6 cells /mL)
Culture Duration (days)
Factor
35
50
70
6.85
1.2
400
12
1
15
Current X
Titer (g/L)
aFucosylation
Galactosylation (%)
HCP (ppm )
DNA (ppm )
CEX % Acidic Variants
Aggregates (%)
Response
0
2
40
15000000
19000
40
3
Contour
4.7
7.8
33.7
495754.0
1552.2
30.2
1.2
Current Y
.
2
20
.
.
20
.
Lo Limit
.
11
40
15000000
.
40
3
Hi Limit
6.6
6.7
6.8
6.9
7
7.1
pH
Galactosylation (%)
34 34.5 35 35.5 36
Tem perature (C)
Contour Profiler
360mOsm 440mOsm HorizVert
Tem perature (C)
DO (%)
CO2 (%)
pH
[Medium] (X)
Osm olality (m Osm)
Feed (X)
IVCC (e6 cells /mL)
Culture Duration (days)
Factor
35
50
40
6.85
1.2
440
12
1
15
Current X
Titer (g/L)
aFucosylation
Galactosylation (%)
HCP (ppm )
DNA (ppm )
CEX % Acidic Variants
Aggregates (%)
Response
0
2
40
15000000
19000
40
3
Contour
4.5
6.6
34.4
458789.8
1479.0
31.0
1.3
Current Y
.
2
20
.
.
20
.
Lo Limit
.
11
40
15000000
.
40
3
Hi Limit
6.6
6.7
6.8
6.9
7
7.1
pH
Galactosylation (%)
34 34.5 35 35.5 36
Tem perature (C)
Contour Profiler
160 mmHg
40 mmHg
100 mmHg
400mOsm
>40% >40%
>40%
<20%
<20%
>11%
>11%
HorizVert
Tem perature (C)
DO (%)
CO2 (%)
pH
[Medium] (X)
Osm olality (m Osm)
Feed (X)
IVCC (e6 cells /mL)
Culture Duration (days)
Factor
34.999293
50
100
6.85
1.2
440
12
1
15
Current X
Titer (g/L)
aFucosylation
Galactosylation (%)
HCP (ppm )
DNA (ppm )
CEX % Acidic Variants
Aggregates (%)
Response
0
2
20
15000000
19000
40
3
Contour
4.2
5.7
30.3
490873.2
1498.3
26.7
1.3
Current Y
.
2
20
.
.
20
.
Lo Limit
.
11
40
15000000
.
40
3
Hi Limit
6.6
6.7
6.8
6.9
7
7.1
pH
aFucosylation
Galactosylation (%)
34 34.5 35 35.5 36
Tem perature (C)
Contour Profiler
CO2
Osmolality
< 2%
HorizVert
Tem perature (C)
DO (%)
CO2 (%)
pH
[Medium] (X)
Osm olality (m Osm)
Feed (X)
IVCC (e6 cells /mL)
Culture Duration (days)
Factor
35
50
100
6.85
1.2
360
12
1
15
Current X
Titer (g/L)
aFucosylation
Galactosylation (%)
HCP (ppm )
DNA (ppm )
CEX % Acidic Variants
Aggregates (%)
Response
0
11
40
15000000
19000
40
3
Contour
4.8
8.3
33.4
513494.5
1471.7
28.2
1.3
Current Y
.
2
20
.
.
20
.
Lo Limit
.
11
40
15000000
.
40
3
Hi Limit
6.6
6.7
6.8
6.9
7
7.1
pH
aFucosylation
34 34.5 35 35.5 36
Tem perature (C)
Contour Profiler
>11%
HorizVert
Tem perature (C)
DO (%)
CO2 (%)
pH
[Medium] (X)
Osm olality (m Osm)
Feed (X)
IVCC (e6 cells /mL)
Culture Duration (days)
Factor
35
50
40
6.85
1.2
360
12
1
15
Current X
Titer (g/L)
aFucosylation
Galactosylation (%)
HCP (ppm )
DNA (ppm )
CEX % Acidic Variants
Aggregates (%)
Response
0
11
40
15000000
19000
40
3
Contour
5.2
9.8
36.8
469303.1
1465.4
33.1
1.3
Current Y
.
2
20
.
.
20
.
Lo Limit
.
11
40
15000000
.
40
3
Hi Limit
6.6
6.7
6.8
6.9
7
7.1
pH
aFucosylation
Galactosylation (%)
34 34.5 35 35.5 36
Tem perature (C)
Contour Profiler
HorizVert
Tem perature (C)
DO (%)
CO2 (%)
pH
[Medium] (X)
Osm olality (m Osm)
Feed (X)
IVCC (e6 cells /mL)
Culture Duration (days)
Factor
35
50
70
6.85
1.2
400
12
1
15
Current X
Titer (g/L)
aFucosylation
Galactosylation (%)
HCP (ppm )
DNA (ppm )
CEX % Acidic Variants
Aggregates (%)
Response
0
2
40
15000000
19000
40
3
Contour
4.7
7.8
33.7
495754.0
1552.2
30.2
1.2
Current Y
.
2
20
.
.
20
.
Lo Limit
.
11
40
15000000
.
40
3
Hi Limit
6.6
6.7
6.8
6.9
7
7.1
pH
Galactosylation (%)
34 34.5 35 35.5 36
Tem perature (C)
Contour Profiler
360mOsm 440mOsm HorizVert
Tem perature (C)
DO (%)
CO2 (%)
pH
[Medium] (X)
Osm olality (m Osm)
Feed (X)
IVCC (e6 cells /mL)
Culture Duration (days)
Factor
35
50
40
6.85
1.2
440
12
1
15
Current X
Titer (g/L)
aFucosylation
Galactosylation (%)
HCP (ppm )
DNA (ppm )
CEX % Acidic Variants
Aggregates (%)
Response
0
2
40
15000000
19000
40
3
Contour
4.5
6.6
34.4
458789.8
1479.0
31.0
1.3
Current Y
.
2
20
.
.
20
.
Lo Limit
.
11
40
15000000
.
40
3
Hi Limit
6.6
6.7
6.8
6.9
7
7.1
pH
Galactosylation (%)
34 34.5 35 35.5 36
Tem perature (C)
Contour Profiler
160 mmHg
40 mmHg
100 mmHg
400mOsm
>40% >40%
>40%
<20%
<20%
>11%
>11%
Design Space for Culture Duration 15 Days
CO2
Osmolality
360mOsm 440mOsm
160 mmHg
40 mmHg
100 mmHg
HorizVert
Tem perature (C)
DO (%)
CO2 (%)
pH
[Medium] (X)
Osm olality (m Osm)
Feed (X)
IVCC (e6 cells /mL)
Culture Duration (days)
Factor
35
50
70
6.85
1.2
400
12
1
17
Current X
Titer (g/L)
aFucosylation
Galactosylation (%)
HCP (ppm )
DNA (ppm )
CEX % Acidic Variants
Aggregates (%)
Response
0
2
40
15000000
19000
40
3
Contour
5.0
6.5
29.8
697946.1
2040.3
30.2
1.5
Current Y
.
2
20
.
.
20
.
Lo Limit
.
11
40
15000000
.
40
3
Hi Limit
6.6
6.7
6.8
6.9
7
7.1
pH
34 34.5 35 35.5 36
Tem perature (C)
Contour Profiler
HorizVert
Tem perature (C)
DO (%)
CO2 (%)
pH
[Medium] (X)
Osm olality (m Osm)
Feed (X)
IVCC (e6 cells /mL)
Culture Duration (days)
Factor
35
50
100
6.85
1.2
440
12
1
17
Current X
Titer (g/L)
aFucosylation
Galactosylation (%)
HCP (ppm )
DNA (ppm )
CEX % Acidic Variants
Aggregates (%)
Response
0
2
20
15000000
19000
40
3
Contour
4.6
5.2
25.7
694855.9
1966.2
26.9
1.6
Current Y
.
2
20
.
.
20
.
Lo Limit
.
11
40
15000000
.
40
3
Hi Limit
6.6
6.7
6.8
6.9
7
7.1
pH
aFucosylationGalactosylation (%)
34 34.5 35 35.5 36
Tem perature (C)
Contour Profiler
400mOsm
HorizVert
Tem perature (C)
DO (%)
CO2 (%)
pH
[Medium] (X)
Osm olality (m Osm)
Feed (X)
IVCC (e6 cells /mL)
Culture Duration (days)
Factor
35
50
100
6.85
1.2
360
12
1
17
Current X
Titer (g/L)
aFucosylation
Galactosylation (%)
HCP (ppm )
DNA (ppm )
CEX % Acidic Variants
Aggregates (%)
Response
0
2
20
15000000
19000
40
3
Contour
5.1
6.3
29.1
702394.3
1965.8
28.4
1.6
Current Y
.
2
20
.
.
20
.
Lo Limit
.
11
40
15000000
.
40
3
Hi Limit
6.6
6.7
6.8
6.9
7
7.1
pH
34 34.5 35 35.5 36
Tem perature (C)
Contour Profiler
HorizVert
Tem perature (C)
DO (%)
CO2 (%)
pH
[Medium] (X)
Osm olality (m Osm)
Feed (X)
IVCC (e6 cells /mL)
Culture Duration (days)
Factor
35
50
40
6.85
1.2
360
12
1
17
Current X
Titer (g/L)
aFucosylation
Galactosylation (%)
HCP (ppm )
DNA (ppm )
CEX % Acidic Variants
Aggregates (%)
Response
0
2
40
15000000
19000
40
3
Contour
5.7
7.5
33.5
669715.6
1973.9
32.9
1.5
Current Y
.
2
20
.
.
20
.
Lo Limit
.
11
40
15000000
.
40
3
Hi Limit
6.6
6.7
6.8
6.9
7
7.1
pH
Galactosylation (%)
34 34.5 35 35.5 36
Tem perature (C)
Contour Profiler
HorizVert
Tem perature (C)
DO (%)
CO2 (%)
pH
[Medium] (X)
Osm olality (m Osm)
Feed (X)
IVCC (e6 cells /mL)
Culture Duration (days)
Factor
35
50
40
6.85
1.2
440
12
1
17
Current X
Titer (g/L)
aFucosylation
Galactosylation (%)
HCP (ppm )
DNA (ppm )
CEX % Acidic Variants
Aggregates (%)
Response
0
2
20
15000000
19000
40
3
Contour
4.9
5.9
30.9
674274.3
1961.3
30.7
1.6
Current Y
.
2
20
.
.
20
.
Lo Limit
.
11
40
15000000
.
40
3
Hi Limit
6.6
6.7
6.8
6.9
7
7.1
pH
Galactosylation (%)
34 34.5 35 35.5 36
Tem perature (C)
Contour Profiler
>40%
<20%
< 2%<20%
Design Space for Culture Duration 17 Days
CO2
Osmolality
360mOsm 440mOsm
160 mmHg
40 mmHg
100 mmHg
HorizVert
Tem perature (C)
DO (%)
CO2 (%)
pH
[Medium] (X)
Osm olality (m Osm)
Feed (X)
IVCC (e6 cells /mL)
Culture Duration (days)
Factor
35
50
70
6.85
1.2
400
12
1
17
Current X
Titer (g/L)
aFucosylation
Galactosylation (%)
HCP (ppm )
DNA (ppm )
CEX % Acidic Variants
Aggregates (%)
Response
0
2
40
15000000
19000
40
3
Contour
5.0
6.5
29.8
697946.1
2040.3
30.2
1.5
Current Y
.
2
20
.
.
20
.
Lo Limit
.
11
40
15000000
.
40
3
Hi Limit
6.6
6.7
6.8
6.9
7
7.1
pH
34 34.5 35 35.5 36
Tem perature (C)
Contour Profiler
HorizVert
Tem perature (C)
DO (%)
CO2 (%)
pH
[Medium] (X)
Osm olality (m Osm)
Feed (X)
IVCC (e6 cells /mL)
Culture Duration (days)
Factor
35
50
100
6.85
1.2
440
12
1
17
Current X
Titer (g/L)
aFucosylation
Galactosylation (%)
HCP (ppm )
DNA (ppm )
CEX % Acidic Variants
Aggregates (%)
Response
0
2
20
15000000
19000
40
3
Contour
4.6
5.2
25.7
694855.9
1966.2
26.9
1.6
Current Y
.
2
20
.
.
20
.
Lo Limit
.
11
40
15000000
.
40
3
Hi Limit
6.6
6.7
6.8
6.9
7
7.1
pH
aFucosylationGalactosylation (%)
34 34.5 35 35.5 36
Tem perature (C)
Contour Profiler
400mOsm
HorizVert
Tem perature (C)
DO (%)
CO2 (%)
pH
[Medium] (X)
Osm olality (m Osm)
Feed (X)
IVCC (e6 cells /mL)
Culture Duration (days)
Factor
35
50
100
6.85
1.2
360
12
1
17
Current X
Titer (g/L)
aFucosylation
Galactosylation (%)
HCP (ppm )
DNA (ppm )
CEX % Acidic Variants
Aggregates (%)
Response
0
2
20
15000000
19000
40
3
Contour
5.1
6.3
29.1
702394.3
1965.8
28.4
1.6
Current Y
.
2
20
.
.
20
.
Lo Limit
.
11
40
15000000
.
40
3
Hi Limit
6.6
6.7
6.8
6.9
7
7.1
pH
34 34.5 35 35.5 36
Tem perature (C)
Contour Profiler
HorizVert
Tem perature (C)
DO (%)
CO2 (%)
pH
[Medium] (X)
Osm olality (m Osm)
Feed (X)
IVCC (e6 cells /mL)
Culture Duration (days)
Factor
35
50
40
6.85
1.2
360
12
1
17
Current X
Titer (g/L)
aFucosylation
Galactosylation (%)
HCP (ppm )
DNA (ppm )
CEX % Acidic Variants
Aggregates (%)
Response
0
2
40
15000000
19000
40
3
Contour
5.7
7.5
33.5
669715.6
1973.9
32.9
1.5
Current Y
.
2
20
.
.
20
.
Lo Limit
.
11
40
15000000
.
40
3
Hi Limit
6.6
6.7
6.8
6.9
7
7.1
pH
Galactosylation (%)
34 34.5 35 35.5 36
Tem perature (C)
Contour Profiler
HorizVert
Tem perature (C)
DO (%)
CO2 (%)
pH
[Medium] (X)
Osm olality (m Osm)
Feed (X)
IVCC (e6 cells /mL)
Culture Duration (days)
Factor
35
50
40
6.85
1.2
440
12
1
17
Current X
Titer (g/L)
aFucosylation
Galactosylation (%)
HCP (ppm )
DNA (ppm )
CEX % Acidic Variants
Aggregates (%)
Response
0
2
20
15000000
19000
40
3
Contour
4.9
5.9
30.9
674274.3
1961.3
30.7
1.6
Current Y
.
2
20
.
.
20
.
Lo Limit
.
11
40
15000000
.
40
3
Hi Limit
6.6
6.7
6.8
6.9
7
7.1
pH
Galactosylation (%)
34 34.5 35 35.5 36
Tem perature (C)
Contour Profiler
>40%
<20%
< 2%<20%
CO2
Osmolality
360mOsm 440mOsm
160 mmHg
40 mmHg
100 mmHg
HorizVert
Tem perature (C)
DO (%)
CO2 (%)
pH
[Medium] (X)
Osm olality (m Osm)
Feed (X)
IVCC (e6 cells /mL)
Culture Duration (days)
Factor
35
50
70
6.85
1.2
400
12
1
17
Current X
Titer (g/L)
aFucosylation
Galactosylation (%)
HCP (ppm )
DNA (ppm )
CEX % Acidic Variants
Aggregates (%)
Response
0
2
40
15000000
19000
40
3
Contour
5.0
6.5
29.8
697946.1
2040.3
30.2
1.5
Current Y
.
2
20
.
.
20
.
Lo Limit
.
11
40
15000000
.
40
3
Hi Limit
6.6
6.7
6.8
6.9
7
7.1
pH
34 34.5 35 35.5 36
Tem perature (C)
Contour Profiler
HorizVert
Tem perature (C)
DO (%)
CO2 (%)
pH
[Medium] (X)
Osm olality (m Osm)
Feed (X)
IVCC (e6 cells /mL)
Culture Duration (days)
Factor
35
50
100
6.85
1.2
440
12
1
17
Current X
Titer (g/L)
aFucosylation
Galactosylation (%)
HCP (ppm )
DNA (ppm )
CEX % Acidic Variants
Aggregates (%)
Response
0
2
20
15000000
19000
40
3
Contour
4.6
5.2
25.7
694855.9
1966.2
26.9
1.6
Current Y
.
2
20
.
.
20
.
Lo Limit
.
11
40
15000000
.
40
3
Hi Limit
6.6
6.7
6.8
6.9
7
7.1
pH
aFucosylationGalactosylation (%)
34 34.5 35 35.5 36
Tem perature (C)
Contour Profiler
400mOsm
HorizVert
Tem perature (C)
DO (%)
CO2 (%)
pH
[Medium] (X)
Osm olality (m Osm)
Feed (X)
IVCC (e6 cells /mL)
Culture Duration (days)
Factor
35
50
100
6.85
1.2
360
12
1
17
Current X
Titer (g/L)
aFucosylation
Galactosylation (%)
HCP (ppm )
DNA (ppm )
CEX % Acidic Variants
Aggregates (%)
Response
0
2
20
15000000
19000
40
3
Contour
5.1
6.3
29.1
702394.3
1965.8
28.4
1.6
Current Y
.
2
20
.
.
20
.
Lo Limit
.
11
40
15000000
.
40
3
Hi Limit
6.6
6.7
6.8
6.9
7
7.1
pH
34 34.5 35 35.5 36
Tem perature (C)
Contour Profiler
HorizVert
Tem perature (C)
DO (%)
CO2 (%)
pH
[Medium] (X)
Osm olality (m Osm)
Feed (X)
IVCC (e6 cells /mL)
Culture Duration (days)
Factor
35
50
40
6.85
1.2
360
12
1
17
Current X
Titer (g/L)
aFucosylation
Galactosylation (%)
HCP (ppm )
DNA (ppm )
CEX % Acidic Variants
Aggregates (%)
Response
0
2
40
15000000
19000
40
3
Contour
5.7
7.5
33.5
669715.6
1973.9
32.9
1.5
Current Y
.
2
20
.
.
20
.
Lo Limit
.
11
40
15000000
.
40
3
Hi Limit
6.6
6.7
6.8
6.9
7
7.1
pH
Galactosylation (%)
34 34.5 35 35.5 36
Tem perature (C)
Contour Profiler
HorizVert
Tem perature (C)
DO (%)
CO2 (%)
pH
[Medium] (X)
Osm olality (m Osm)
Feed (X)
IVCC (e6 cells /mL)
Culture Duration (days)
Factor
35
50
40
6.85
1.2
440
12
1
17
Current X
Titer (g/L)
aFucosylation
Galactosylation (%)
HCP (ppm )
DNA (ppm )
CEX % Acidic Variants
Aggregates (%)
Response
0
2
20
15000000
19000
40
3
Contour
4.9
5.9
30.9
674274.3
1961.3
30.7
1.6
Current Y
.
2
20
.
.
20
.
Lo Limit
.
11
40
15000000
.
40
3
Hi Limit
6.6
6.7
6.8
6.9
7
7.1
pH
Galactosylation (%)
34 34.5 35 35.5 36
Tem perature (C)
Contour Profiler
>40%
<20%
< 2%<20%
Design Space for Culture Duration 17 Days
Design Space for Culture Duration 19 Days
CO2
Osmolality
360mOsm 440mOsm
160 mmHg
40 mmHg
100 mmHg
400mOsm HorizVert
Tem perature (C)
DO (%)
CO2 (%)
pH
[Medium] (X)
Osm olality (m Osm)
Feed (X)
IVCC (e6 cells /mL)
Culture Duration (days)
Factor
35
50
40
6.85
1.2
440
12
1
19
Current X
Titer (g/L)
aFucosylation
Galactosylation (%)
HCP (ppm )
DNA (ppm )
CEX % Acidic Variants
Aggregates (%)
Response
0
2
20
15000000
19000
40
3
Contour
5.4
5.2
27.3
889758.9
2443.6
30.5
1.9
Current Y
.
2
20
.
.
20
.
Lo Limit
.
11
40
15000000
.
40
3
Hi Limit
6.6
6.7
6.8
6.9
7
7.1
pH
Galactosylation (%)
34 34.5 35 35.5 36
Tem perature (C)
Contour Profiler
HorizVert
Tem perature (C)
DO (%)
CO2 (%)
pH
[Medium] (X)
Osm olality (m Osm)
Feed (X)
IVCC (e6 cells /mL)
Culture Duration (days)
Factor
35
50
40
6.85
1.2
360
12
1
19
Current X
Titer (g/L)
aFucosylation
Galactosylation (%)
HCP (ppm )
DNA (ppm )
CEX % Acidic Variants
Aggregates (%)
Response
0
2
20
15000000
19000
40
3
Contour
6.1
5.3
30.2
870128.1
2482.5
32.8
1.8
Current Y
.
2
20
.
.
20
.
Lo Limit
.
11
40
15000000
.
40
3
Hi Limit
6.6
6.7
6.8
6.9
7
7.1
pH
34 34.5 35 35.5 36
Tem perature (C)
Contour Profiler
HorizVert
Tem perature (C)
DO (%)
CO2 (%)
pH
[Medium] (X)
Osm olality (m Osm)
Feed (X)
IVCC (e6 cells /mL)
Culture Duration (days)
Factor
35
50
100
6.85
1.2
360
12
1
19
Current X
Titer (g/L)
aFucosylation
Galactosylation (%)
HCP (ppm )
DNA (ppm )
CEX % Acidic Variants
Aggregates (%)
Response
0
2
20
15000000
19000
40
3
Contour
5.4
4.3
24.8
891294.0
2459.8
28.6
1.8
Current Y
.
2
20
.
.
20
.
Lo Limit
.
11
40
15000000
.
40
3
Hi Limit
6.6
6.7
6.8
6.9
7
7.1
pH
aFucosylation
Galactosylation (%)
34 34.5 35 35.5 36
Tem perature (C)
Contour Profiler
HorizVert
Tem perature (C)
DO (%)
CO2 (%)
pH
[Medium] (X)
Osm olality (m Osm)
Feed (X)
IVCC (e6 cells /mL)
Culture Duration (days)
Factor
35
50
100
6.85
1.2
440
12
1
19
Current X
Titer (g/L)
aFucosylation
Galactosylation (%)
HCP (ppm )
DNA (ppm )
CEX % Acidic Variants
Aggregates (%)
Response
0
2
20
15000000
19000
40
3
Contour
4.9
4.7
21.1
898827.7
2434.0
27.0
1.9
Current Y
.
2
20
.
.
20
.
Lo Limit
.
11
40
15000000
.
40
3
Hi Limit
6.6
6.7
6.8
6.9
7
7.1
pH
Galactosylation (%)
34 34.5 35 35.5 36
Tem perature (C)
Contour Profiler
HorizVert
Tem perature (C)
DO (%)
CO2 (%)
pH
[Medium] (X)
Osm olality (m Osm)
Feed (X)
IVCC (e6 cells /mL)
Culture Duration (days)
Factor
35
50
70
6.85
1.2
400
12
1
19
Current X
Titer (g/L)
aFucosylation
Galactosylation (%)
HCP (ppm )
DNA (ppm )
CEX % Acidic Variants
Aggregates (%)
Response
0
2
20
15000000
19000
40
3
Contour
5.4
5.1
25.9
900138.3
2528.5
30.1
1.8
Current Y
.
2
20
.
.
20
.
Lo Limit
.
11
40
15000000
.
40
3
Hi Limit
6.6
6.7
6.8
6.9
7
7.1
pH
34 34.5 35 35.5 36
Tem perature (C)
Contour Profiler
<20%
<20%
< 2%
<20%
Design Space for Culture Duration 19 Days
CO2
Osmolality
360mOsm 440mOsm
160 mmHg
40 mmHg
100 mmHg
400mOsm HorizVert
Tem perature (C)
DO (%)
CO2 (%)
pH
[Medium] (X)
Osm olality (m Osm)
Feed (X)
IVCC (e6 cells /mL)
Culture Duration (days)
Factor
35
50
40
6.85
1.2
440
12
1
19
Current X
Titer (g/L)
aFucosylation
Galactosylation (%)
HCP (ppm )
DNA (ppm )
CEX % Acidic Variants
Aggregates (%)
Response
0
2
20
15000000
19000
40
3
Contour
5.4
5.2
27.3
889758.9
2443.6
30.5
1.9
Current Y
.
2
20
.
.
20
.
Lo Limit
.
11
40
15000000
.
40
3
Hi Limit
6.6
6.7
6.8
6.9
7
7.1
pH
Galactosylation (%)
34 34.5 35 35.5 36
Tem perature (C)
Contour Profiler
HorizVert
Tem perature (C)
DO (%)
CO2 (%)
pH
[Medium] (X)
Osm olality (m Osm)
Feed (X)
IVCC (e6 cells /mL)
Culture Duration (days)
Factor
35
50
40
6.85
1.2
360
12
1
19
Current X
Titer (g/L)
aFucosylation
Galactosylation (%)
HCP (ppm )
DNA (ppm )
CEX % Acidic Variants
Aggregates (%)
Response
0
2
20
15000000
19000
40
3
Contour
6.1
5.3
30.2
870128.1
2482.5
32.8
1.8
Current Y
.
2
20
.
.
20
.
Lo Limit
.
11
40
15000000
.
40
3
Hi Limit
6.6
6.7
6.8
6.9
7
7.1
pH
34 34.5 35 35.5 36
Tem perature (C)
Contour Profiler
HorizVert
Tem perature (C)
DO (%)
CO2 (%)
pH
[Medium] (X)
Osm olality (m Osm)
Feed (X)
IVCC (e6 cells /mL)
Culture Duration (days)
Factor
35
50
100
6.85
1.2
360
12
1
19
Current X
Titer (g/L)
aFucosylation
Galactosylation (%)
HCP (ppm )
DNA (ppm )
CEX % Acidic Variants
Aggregates (%)
Response
0
2
20
15000000
19000
40
3
Contour
5.4
4.3
24.8
891294.0
2459.8
28.6
1.8
Current Y
.
2
20
.
.
20
.
Lo Limit
.
11
40
15000000
.
40
3
Hi Limit
6.6
6.7
6.8
6.9
7
7.1
pH
aFucosylation
Galactosylation (%)
34 34.5 35 35.5 36
Tem perature (C)
Contour Profiler
HorizVert
Tem perature (C)
DO (%)
CO2 (%)
pH
[Medium] (X)
Osm olality (m Osm)
Feed (X)
IVCC (e6 cells /mL)
Culture Duration (days)
Factor
35
50
100
6.85
1.2
440
12
1
19
Current X
Titer (g/L)
aFucosylation
Galactosylation (%)
HCP (ppm )
DNA (ppm )
CEX % Acidic Variants
Aggregates (%)
Response
0
2
20
15000000
19000
40
3
Contour
4.9
4.7
21.1
898827.7
2434.0
27.0
1.9
Current Y
.
2
20
.
.
20
.
Lo Limit
.
11
40
15000000
.
40
3
Hi Limit
6.6
6.7
6.8
6.9
7
7.1
pH
Galactosylation (%)
34 34.5 35 35.5 36
Tem perature (C)
Contour Profiler
HorizVert
Tem perature (C)
DO (%)
CO2 (%)
pH
[Medium] (X)
Osm olality (m Osm)
Feed (X)
IVCC (e6 cells /mL)
Culture Duration (days)
Factor
35
50
70
6.85
1.2
400
12
1
19
Current X
Titer (g/L)
aFucosylation
Galactosylation (%)
HCP (ppm )
DNA (ppm )
CEX % Acidic Variants
Aggregates (%)
Response
0
2
20
15000000
19000
40
3
Contour
5.4
5.1
25.9
900138.3
2528.5
30.1
1.8
Current Y
.
2
20
.
.
20
.
Lo Limit
.
11
40
15000000
.
40
3
Hi Limit
6.6
6.7
6.8
6.9
7
7.1
pH
34 34.5 35 35.5 36
Tem perature (C)
Contour Profiler
<20%
<20%
< 2%
<20%
Vinci/Defelippis - CMC BWG QbD
Case StudyLilly - Company Confidential 2010
7/13/2010
7
Horiz Vert
Temperature (C)
DO (%)
CO2 (mmHg)
pH
[Medium] (X)
Osmo (mOsm)
Feed (X)
IVCC (e6 cells/mL)
Duration (d)
Factor
35
50
40
6.85
1.2
360
12
1
15
Current X
Titer (g/L)
aFucosylation
Galactosylation (%)
HCP (ppm)
DNA (ppm)
CEX % Acidic Variants
Response
3
11
40
675000
2250
40
Contour
5.3408326
9.1879682
38.227972
466955.66
1382.1644
34.420095
Current Y
3
.
.
.
.
.
Lo Limit
.
11
40
.
.
.
Hi Limit
6.6
6.7
6.8
6.9
7
7.1
pH
aFucosylation
Galactosylation (%)
34 34.5 35 35.5 36
Temperature (C)
Contour Profiler
Design Space Based on Process Capability Understanding Variability
Vinci/Defelippis - CMC BWG QbD
Case StudyLilly - Company Confidential 2010 19
Galact >40%
aFucos >11%
34 34.2 34.4 34.6 34.8 35 35.2 35.4 35.6 35.8 366.6
6.65
6.7
6.75
6.8
6.85
6.9
6.95
7
7.05
0.250.250.25
0.2
5
0.50.5
0.5
0.5
0.70.7
0.7
0.7
0.80.8
0.8
0.8
0.9
0.9
0.9
0.9
0.950.95
0.95
0.95
0.99
0.99
0.99
0.9
9
Example: Day 15, Osmo=360 mOsm
and pCO2=40 mmHg >99%
confidence of
satisfying all
CQAs
50% contour
approximates “white”
region” in contour plot
pH pH
Temperature (C) Temperature (C)
20
Risk Assessment ApproachMultiple Assessments Throughout the
A-Mab Development Lifecycle for Entire Process
Prior Knowledge
Process Understanding
Product Understanding
Process
Development
Risk
Assessment
Process
Characterization
Risk
Assessment
Risk
Assessment
Process
Performance
Verification
Risk
Assessment
Life Cycle
Management
Final Control
Strategy
Process
Parameters
Quality
Attributes
Design Space
Draft Control
Strategy
Process 2
Process 1 2
Vinci/Defelippis - CMC BWG QbD
Case StudyLilly - Company Confidential 2010
You Are Here
Control Strategy for Upstream Production
Step 2
Seed Culture Expansion
in Fixed Stirred Tank
Bioreactors
Step 3
Production Culture
Step 4
Centrifugation and Depth
Filtration
Working Cell Bank
Clarified Bulk
Step 1
Seed Culture Expansion
in Disposable Shake
Flasks and/or bags
In-Process
Quality Attributes
Bioburden
MMV
Mycoplama
Adventitious Virus
Product Yield
Turbidity
Viable Cell Concentration
Viability
Product Yield
Viability at Harvest
Turbity at Harvest
Viable Cell Concentration
Viability
Key Process
Attributes
Viable Cell Concentration
Viability
Quality-linked
Process Parameters
(WC-CPPs)
Temperature
pH
Dissolved CO2
Culture Duration
Osmolality
Remnant Glucose
Temperature
pH
Dissolved Oxygen
Culture Duration
Initial VCC/Split Ratio
Antifoam Concentration
Time of Nutrient Feed
Volume of Nutrient Feed
Time of Glucose Feed
Volume of Glucose Feed
Dissolved Oxygen
Flow Rate
Pressure
Temperature
Culture Duration
Initial VCC/Split Ratio
Key Process
Parameters
(KPPs)
Temperature
Time
Controlled within the
Design Space to
ensure consistent
product quality and
process performance
Controlled within acceptable
limits to ensure consistent
process performance
Assay results part
of batch release
specifications
Slide 21Vinci/Defelippis - CMC BWG QbD
Case StudyLilly - Company Confidential 2010
7/13/2010
8
Example of Control Strategy for Selected CQAs
CQA Criticality Process
CapabilityTesting Criteria
Other ControlElements
Aggregate High (48) High RiskDS and DP
releaseYes
Parametric Control ofDS/DP steps
aFucosylation High (60) Low RiskDS Process Monitoring
YesParametric Control of
Production BioRx
Galactosylation High (48)Low Risk DS Process
MonitoringYes
Parametric Control of Production BioRx
Host Cell Protein
High (24)Very Low
RiskCharact.
ComparabilityYes
Parametric Control of Prod BioRx, ProA, pH inact, CEX , AEX steps
DNA High (24)Very Low
RiskCharact.
ComparabilityYes
Parametric Control of Prod Biox and AEX
Steps
Deamidated Isoforms
Low (12) Low RiskCharact.
ComparabilityNo
Parametric Control of Production BioRx
Vinci/Defelippis - CMC BWG QbD
Case Study22Lilly - Company Confidential 2010
Lifecycle Management of Design SpaceDynamic Modeling
Challenge:
• Data from a limited number of batches is required for process validation
ex: n=5 or more for 3 bioreactors ; costly and often critical path
• Limited replicates are not statistically significant – at best test the “system” including facility, equipment, process, operators, etc
Alternative Lifecycle Approach or Continuous Process Verification:
• Quality Mgt System assures site’s readiness and compliance
• Use 1 or 2 batches to confirm or demonstrate validity of design space
• Utilize a multivariate statistical partial least squares (PLS) model for continuous process verification as commercial experience grows in number of runs
• Scheduled reviews of product quality data trends and design space validity during the product lifecycle
Vinci/Defelippis - CMC BWG QbD
Case StudyLilly - Company Confidential 2010 23
Design Space and Elements of Control
Successful acceptance or utilization of our evolving view of design space relies on linking the multiple elements of documented knowledge and systems:
Facilitated formal attribute rankings and parameter risk assessments to guide DOEs
Linkage of all attribute and parameter ranges used for modeling and scale
Delineation of how lifecycle oversight (control strategy) of critical and non-critical parameters and specification/limit testing occurs
Movement to best practices for engineering first principles/mechanistic models and statistical modeling as they apply to QbD paradigm
Vinci/Defelippis - CMC BWG QbD Case
StudyLilly - Company Confidential 2010 24
7/13/2010
9
Upstream Development Team
Ilse Blumentals GSK
Guillermo Miroquesada MedImmune
Kripa Ram MedImmune
Ron Taticek Genentech
Victor Vinci Lilly
*Help from many others – CMC BWG member company reps and internal resources at each company
Vinci/Defelippis - CMC BWG
QbD Case StudyLilly - Company Confidential 2010 25