Upload
juan-hoover
View
217
Download
1
Tags:
Embed Size (px)
Citation preview
1
Utilizing RM in a Submission for Developing Critical Process Parameters and Critical to Quality Attributes
Kelly Canter, PhDRight the First Time Program Office
Pfizer Inc., Groton, CT
FDA/Industry Statistics WorkshopSeptember 2006
2
Outline
QbD Terminology and Value Proposition
Risk Assessment Process (Case Study)
Experiments, PAT and Prioritization
Creation of Design Space
QbD Terminology and Value Proposition
Risk Assessment Process (Case Study)
Experiments, PAT and Prioritization
Creation of Design Space
3
Alignment of ICH Q(8)
Enhanced knowledge of product performance . . .– Establish range of material attributes, processing options
& process parameters Demonstrated product/process understanding Results from PAT, DOE, Science of Scaling Appropriate application of risk management principles
– Establish Design Space
Flexible regulatory approaches– Risk based regulatory decisions– Mfg. process improvements w/in approved design space– Real time quality control Reduce product release
tests
Enhanced knowledge of product performance . . .– Establish range of material attributes, processing options
& process parameters Demonstrated product/process understanding Results from PAT, DOE, Science of Scaling Appropriate application of risk management principles
– Establish Design Space
Flexible regulatory approaches– Risk based regulatory decisions– Mfg. process improvements w/in approved design space– Real time quality control Reduce product release
tests
4
Quality by Design – “Right First Time”
Commercializable Manufacturing
Process (API or DP)
Risk Assessment• Prioritized
Experimental Plans• Prioritized PAT Plans
Experimentation /Method
Dev/Documentation
Design Space Definition
Process Control Strategy
Change Control Strategy and
Implementation
Regulatory Filing/Approval
Process Capability Monitoring
Continuous Improvement
(Process Changes)
e.g. Cpk
Launch
Process Understanding
Process Control Continuous Improvement
5
Why Do QbD?(Value Proposition)
Work Impact During Development Decrease ICH re-do’s Decrease Validation
re-do’s Decrease Clinical
Batch re-do’s Transparent
assessment of risk Prioritization
Work Impact During Development Decrease ICH re-do’s Decrease Validation
re-do’s Decrease Clinical
Batch re-do’s Transparent
assessment of risk Prioritization
Improvements to our Products and Processes Decrease Variability Assure market supply Faster change implementation Science support Quality investigtations Reduce COG Streamline regulatory reviews (S&E) Framework for decreased regulatory
burden Standardization
Improvements to our Products and Processes Decrease Variability Assure market supply Faster change implementation Science support Quality investigtations Reduce COG Streamline regulatory reviews (S&E) Framework for decreased regulatory
burden Standardization
Getting at the Right Process Knowledge = Value to Pfizer, FDA and Patients
6
People
Equipment
Measurement
Process
Materials
Environment
INPUTS
(X)
Process Understanding
y = ƒ(x)
OUTPUT
y
Inputs to the processcontrol variability
of the Output
J. Scott, ASTM, London 2004
Process
Parameters
Quality Attri
butes
7
What is a Quality Attribute?
Definitions
Quality Attribute– A physical, chemical or micorbiological property or
characteristic of a material.
Key Quality Attribute (KQA)– Potential to impact product quality or process effectiveness– Evaluated by an associated analytical method.
Critical Quality Attribute (CQA)– impacts the safety or efficacy of a drug products
Definitions
Quality Attribute– A physical, chemical or micorbiological property or
characteristic of a material.
Key Quality Attribute (KQA)– Potential to impact product quality or process effectiveness– Evaluated by an associated analytical method.
Critical Quality Attribute (CQA)– impacts the safety or efficacy of a drug products
8
What is a Process Parameter?
Definitions
Process Parameters– Broadly defined as machines, materials, people, processes,
measurements and environments
Key Process Parameter (KPP)– Influences product quality or process effectiveness
Critical Process Parameter (CPP)– Influences a CQA and that must be controlled within predefined
limits to ensure the API or product meets its pre-defined limits
Definitions
Process Parameters– Broadly defined as machines, materials, people, processes,
measurements and environments
Key Process Parameter (KPP)– Influences product quality or process effectiveness
Critical Process Parameter (CPP)– Influences a CQA and that must be controlled within predefined
limits to ensure the API or product meets its pre-defined limits
9
Risk Assessment Work Process
10
Risk Assessment and PrioritizationDecide what’s important to evaluate
Process Consensus decisions Use process experience Use project process knowledge Focus on the “Voice of the
Customer”
Process Cause and Effect Matrix with
“Effects” focused on KQAs
Vital Few Y’s: Key Quality Attributes
Vital Few X’s: Key Process Parameters
Many Y’s
Quality Attributes
Many X’s
Process Parameters
11
The QbD Work Process at a “High Level”
Risk Assessment
Experimental Planning
Prioritization
Experimentation
Process Understanding
12
Risk Assessment Case Study
Dry Granulation Tablet
13
Risk Assessment Objectives
Gain agreement on process scope
Decide what’s important to evaluate
Prioritize parameters based on risk
Gain agreement on high level experimental strategy
Identify and prioritize PAT applications
Gain agreement on process scope
Decide what’s important to evaluate
Prioritize parameters based on risk
Gain agreement on high level experimental strategy
Identify and prioritize PAT applications
14
Risk Assessment Work Process
Risk Assessment
15
Risk Assessment Meeting Participants
R&D Co-Facilitator API
– Analytical – Formulation*– Chemical
DP– Analytical– Formulation– Chemical*
Ext. Subject matter experts
PAT R&D Statistician Scribe (workbook) Line management Team Co-Leader
R&D Co-Facilitator API
– Analytical – Formulation*– Chemical
DP– Analytical– Formulation– Chemical*
Ext. Subject matter experts
PAT R&D Statistician Scribe (workbook) Line management Team Co-Leader
Pfizer Global Manufacturing Co-Facilitator API Tech Services DP Tech Services Manufacturing Supervisor QC QA Team Co-Leader Subject matter experts PAT PGM Line management
Pfizer Global Manufacturing Co-Facilitator API Tech Services DP Tech Services Manufacturing Supervisor QC QA Team Co-Leader Subject matter experts PAT PGM Line management
16
Risk Assessment Work Flow
Create a Process Map with Focus Areas
Identify all Quality Attributes and Determine How To Measure
Identify and Prioritize all Process Parameters (KPPs)
Group KPPs into Experiments
Create PAT Prioritization Matrix
DocumentYellow font =Pre-work required.
17
Risk AssessmentStep 1. Create a Process MapDescribes the composition and boundaries of each focus area.
Focu
s A
rea
1
Raw Material Dispensing
Preblending
CP-526, 555-18, Cellulose microcr, PH200, Calcium Hydrogrenphosphate (amhydrous),
colloidal Silicon dioxide, Croscarmellose Sodium
300 L bin15 minutes
Sieving
Focu
s A
rea
2 Comil0.8 mm sieve
Lube Blend
Focu
s A
rea
3 300 L bin2 minutes
Dry Granulation and Blend Bepex K 200/50Roll: Deep Pocket
Screen Size: 0.8 mm
Focu
s A
rea
4
Blending 300 L bin3 minutes
Lube Blend
Focu
s A
rea
5 300 L bin3 minutes
Compression
Focu
s A
rea
6
IMA Comprima 300
Film Coating
Focu
s A
rea
7
Glatt GC 1250
Process Step Commercial Manufacture Boundaries
Raw Material Dispensing
Initial Blend
Initial Blend
De-lumped Unlubed Blend
De-lumped Unlubed Blend
Lubed Blend
Lubed Blend
Unlubed Granulation
Unlubed Granulation
Final Blend
Final Blend
Tablet Cores
Tablet Cores
Film Coated Tablets
18
Key Attribute Y Y Y Y N Y YRank 7 7 7 7 5 10 10
Process ParameterSieve Cut Potency
Blend Uniformity
Particle Size Distribution
Mill Choking
Surface Area
Hardness (Focus Area
6)
Content Uniformity
(Focus Area 6)
ScoreExp./
Approach
Operator Training Procedures
10 10 10 10 0 10 10 840 FMEA
Roll Force 10 10 10 1 0 10 10 777 DOEScreen Size 10 10 10 10 0 5 5 632 DOEGap Width 10 10 5 5 0 5 5 585 DOEMaterial Throughput 10 1 5 10 0 1 1 437 DOERoller Compaction Calibration
5 5 5 1 0 5 5 427 FMEA
Sampling Size 10 10 10 1 0 1 5 421 MSARoll Speed 5 5 5 10 0 1 1 370 DOEEquipment Aging 5 1 10 1 0 1 1 286Transfer Distance into Roller
10 5 1 1 0 1 5 278
Risk AssessmentStep 2. Identify QAs and How MeasuredStep 3. Identify and Prioritize PPsFocus Area 4 - Dry Granulate + Blend
19
KQA1 KQA2 KQA3 KQA4 KQA5
Risk AssessmentStep 4. Group Key PPs by ExperimentsFocus Area 4 - Dry Granulate + Blend
Raw Raw MaterialsMaterials
. . . . . . . …
Define Process Flowchart
Define Focus Areas
Identify KQAs and Associated
Measurement
Identify and Prioritize KPPs
Define Experiments
KPP1 KPP2 KPP3 KPP4 KPP5
Experiment1 Experiment2 Experiment3
Unit OpUnit Op11
. . . . . . . …
Unit OpUnit Op22. . . . . . . …
Prioritize Experiments
Next step:
. . . . . . . …
20
Risk AssessmentStep 5. Create PAT Prioritization Matrix Focus Area 4 - Dry Granulate and Blend
Focus Area
Quality Attributes
Metric/Unit
Measurement System
Probability of Success (H/M/L)
Criticality/Benefit (H/M/L)
Cost (H/M/L)
KeyAttribute
(Y/N)
4 Sieve cut potency
% Intent HPLC M L M Y
4 Flowability L L H Y
4 Blend Uniformity % rsd HPLC M M H Y
4 Segregation Index % rsd J&J Tester L L H Y
4 Particle Size Distribution Size Sieve Analysis H L H Y
21
Risk AssessmentStep 6. Document the Process Understanding
Risk Assessment
Experimental Strategy
Protocols
Primary Data
Scientific Reports
Global Document Management System
Risk Assessment
Experimental Strategy
Protocols
Primary Data
Scientific Reports
Global Document Management System
22
Initial Risk Assessment Complete
23
The Work Process
Risk Assessment
Experimental Planning
24
Experimental Planning“Example DOE”Focus Area 4 - Dry Granulate + Blend
Key Attribute Y Y Y Y N Y YRank 7 7 7 7 5 10 10
ParameterSieve Cut Potency
Blend Uniformity
Particle Size Distribution
Mill choking
Surface Area
Hardness (Focus Area
6)
Content Uniformity
(Focus Area 6)
ScoreExp.
Strategy
Operator Training Procedures
10 10 10 10 0 10 10 840 FMEA
Roll Force 10 10 10 1 0 10 10 777 DOEScreen Size 10 10 10 10 0 5 5 632 DOEGap Width 10 10 5 5 0 5 5 585 DOEMaterial Throughput 10 1 5 10 0 1 1 437 DOERoller Compaction Calibration
5 5 5 1 0 5 5 427 FMEA
Sampling Size 10 10 10 1 0 1 5 421 MSARoll Speed 5 5 5 10 0 1 1 370 DOEEquipment Aging 5 1 10 1 0 1 1 286Transfer Distance into Roller
10 5 1 1 0 1 5 278
26
DOE Regression ModelsModel Coefficients (p - values)
Main Effects Interactions Quad.
Quality Attributes(Intercept) Roll Force Gap Width
Mill Screen
SizeMill Speed
Roll Force x
Gap Width
Roll Force x Mill Screen
Size
Mill Screen Size 2
Gran Particle Size (216) 51 (<0.0001) ---
68(<0.0001
)--- --- 38
(0.0006) ---
Sieve Cut RSD (41.4) -6.4 (<0.0001) --- 1.2
(0.2650) --- --- --- -17.9(<0.0001)
Log (Gran RSD) (-0.07) 0.10 (0.0758) --- 0.17
(0.0051) --- --- --- ---
Log (Tablet Potency RSD) (-0.15)
-0.08 (0.0025)
-0.06 (0.0308)
0.06(0.0180) --- --- --- ---
CF @ Tablet Hard. = 7 kP (6.8)
2.0 (<0.0001)
-0.6(<0.0001) --- --- -0.5
(0.0002) --- ---
FRI @ Tablet Hard. = 7 kP (0.06) --- --- 0.02
(0.0320) --- --- ---
27
Requirements to Map Design Space
Boundary Conditions
Process Parameters
Gap Width 1.7 – 3.5 mm
Mill Screen 0.8 – 1.5 mm
Quality Attributes
Sieve Cut Variability (% RSD) <35%
% Bypass <15%
Compression Force
at 7 kP Hardness<8.5 kN
Tablet Uniformity <1.0%
28
DESIGN-EXPERT Plot
Overlay Plot Design Points
X = A: Roll Force Y = B: Gap Width
Actual Factors C: Sieve Size = 0.80 D: Log_Gran_Sp = 1.40
Overlay Plot
A: Roll Force
B: G
ap W
idth
4.00 6.00 8.00 10.00 12.00 1.70
2.15
2.60
3.05
3.50
CF@Hard=7kP: 8.5
2 2
Revised Process Parameter
Initial Process Parameter
Rationale for Process Ranges within Design Space (0.8 mm Mill Screen Size and 50 rpm Granulator Speed)
Yellow Region: Acceptable combinations of process
parameters.Unacceptable
space
29
Rationale for Process Ranges within Design Space Contour Map – Bypass Weight %
Bypass Wt %
A: Roll Force (kN)
B:
Gap
Wid
th (
mm
)
4 6 8 10 12
1.4
2.0
2.6
3.2
3.8
1
1
2
3
4
567
8
910
12.515
Bypass Wt %
A: Roll Force (kN)
B:
Gap
Wid
th (
mm
)
4 6 8 10 12
1.4
2.0
2.6
3.2
3.8
1
1
2
3
4
567
8
910
12.515
Bypass weight loss is highest in upper left quadrant of Roll Force vs Gap Width
Bypass weight loss is highest in upper left quadrant of Roll Force vs Gap Width
Response(intercept)
RF
Coefficient(p-value)
GW
Coefficient(p-value)
RF*GW
Coefficient(p-value)
Ln [Bypass Wt%]
(0.70)-0.71
(0.0045)0.37
(0.0479)-0.81
(0.0046)
Statistics and Model
Roll Force
4 6 8 10 12
1.4
2.0
2.6
3.2
3.8
Gap
Wid
th (
mm
)
Unacceptable space
30
Conclusions from DOE (D-Optimal)
Increasing roll force improved (lowered RSD) granulation and tablet uniformity.
Increasing roll force also reduced % bypass
However, increasing roll force increased the tablet compressional force required (Safety Margin 8.5 kN)
Acceptable process range for roll force is 5-9 kN (see Design Space)
Increasing roll force improved (lowered RSD) granulation and tablet uniformity.
Increasing roll force also reduced % bypass
However, increasing roll force increased the tablet compressional force required (Safety Margin 8.5 kN)
Acceptable process range for roll force is 5-9 kN (see Design Space)
31
The Work Process
Risk Assessment
Experimental Planning
Prioritization
32
Experimental Strategy & Prioritization Example
Fractional Factorial(Focus Areas1&2)
152 V1
2Gage R&R
(Focus Area 3)
Central CompositeFocus Areas 1&2)
Full Factorial w/centerAdd axial points to Full Factorial
3
4 FMEA (Focus Areas 2&3)
Etc…
33
The Work Process
Risk Assessment
Experimental Planning
Prioritization
Experimentation
34
Building Models: KQA = f (KPP1, KPP2, …KPPi)Conclusions:
Operating target and ranges were identified for each of the following key parameters, key attributes:
Roll force (KPP1)– Impacts particle size, blend uniformity, tablet uniformity
(KQA1, KQA2, KQA3)
Gap width (KPP2)– Impacts tablet uniformity (KQA3)
Screen size (KPP3)– Impacts sieve cut uniformity (KQA4)
Granulator speed (KPP4)– Not significant for KQAs investigated
Operating target and ranges were identified for each of the following key parameters, key attributes:
Roll force (KPP1)– Impacts particle size, blend uniformity, tablet uniformity
(KQA1, KQA2, KQA3)
Gap width (KPP2)– Impacts tablet uniformity (KQA3)
Screen size (KPP3)– Impacts sieve cut uniformity (KQA4)
Granulator speed (KPP4)– Not significant for KQAs investigated
35
Control-, Design- and Knowledge space
Knowledge SpaceKnowledge Space
Design Space
Control Space
Proven Acceptable Range
Normal Operating Range
36
Design Space
Formulation & Process
Development
Preblending and Milling
Lubrication and Compression
Dry Granulation and Milling
Film-Coating
API Particle Size VMD <35 um,
D[v, 0.9] < 100 um
Roll Force: “42-60 kN” (Bepex); “5-9 kN” (Gerteis)
Gap Width “1.7-3.5 mm
(Gerteis)”
Granulator Screen Size: Gerteis: “0.8-1.5 mm” Bepex: “0.8-1.0 mm”
Content Uniformity of Final Blend
Content Uniformity of Tablets
PS of Granulation
% By Pass
Sieve Cut Uniformity
Blend Segregation
Press Shut Off ~500 g
Parameters Parameters Parameters Parameters Parameters
Attributes Attributes Attributes Attributes Attributes
NONE
NONE NONE
NONE
NONE
KEY PARAMETER OR ATTRIBUTE CRITICAL PARAMETER OR ATTRIBUTE
37
Acknowledgements
Chris Sinko
Roger Nosal
Jim Spavins
Vince McCurdy
Tom Garcia
Christina Grillo
Mary Am Ende
Dan O’Connell
Chris Sinko
Roger Nosal
Jim Spavins
Vince McCurdy
Tom Garcia
Christina Grillo
Mary Am Ende
Dan O’Connell