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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

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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

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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

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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

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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

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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

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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

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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

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Risk Assessment Work Process

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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

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The QbD Work Process at a “High Level”

Risk Assessment

Experimental Planning

Prioritization

Experimentation

Process Understanding

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Risk Assessment Case Study

Dry Granulation Tablet

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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

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Risk Assessment Work Process

Risk Assessment

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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

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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.

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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

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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

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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

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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:

. . . . . . . …

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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

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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

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Initial Risk Assessment Complete

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The Work Process

Risk Assessment

Experimental Planning

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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

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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) --- --- ---

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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%

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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

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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

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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)

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The Work Process

Risk Assessment

Experimental Planning

Prioritization

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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…

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The Work Process

Risk Assessment

Experimental Planning

Prioritization

Experimentation

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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

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Control-, Design- and Knowledge space

Knowledge SpaceKnowledge Space

Design Space

Control Space

Proven Acceptable Range

Normal Operating Range

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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

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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