Design Space

1 R. A. Lipper – PAT/QbD Workshop – Sept 11, 2006

Case Study: Implementation of Design Space Concepts in Development of an

Active-Coated Tablet

Robert A. Lipper, Ph.D.,Robert A. Lipper, Ph.D.,Divyakant Desai, Ph.D., San Kiang, Ph.D.Divyakant Desai, Ph.D., San Kiang, Ph.D.

Bristol-Myers Squibb Pharmaceutical Research InstituteBristol-Myers Squibb Pharmaceutical Research Institute

Real World Applications of PAT and QbD in Drug Process Development and Approval – September 11, 2006 – Arlington, VA


Outline

Philosophy/Things to PonderPhilosophy/Things to Ponder Technical Challenge and ApproachTechnical Challenge and Approach Analysis of VariablesAnalysis of Variables

FormulationFormulation Coating ProcessCoating Process

Uniformity of InputUniformity of Input Spray CharacterizationSpray Characterization DOEDOE Control of CoatingControl of Coating

ResultsResults Scale-Up and Technology TransferScale-Up and Technology Transfer Model DevelopmentModel Development SummarySummary

Philosophy/Things to PonderPhilosophy/Things to Ponder Technical Challenge and ApproachTechnical Challenge and Approach Analysis of VariablesAnalysis of Variables

FormulationFormulation Coating ProcessCoating Process

Uniformity of InputUniformity of Input Spray CharacterizationSpray Characterization DOEDOE Control of CoatingControl of Coating

ResultsResults Scale-Up and Technology TransferScale-Up and Technology Transfer Model DevelopmentModel Development SummarySummary


Design Space Ponderables

“The multidimensional combination and interaction of input variables. . .and process parameters that have been demonstrated to provide assurance of quality.” [from ICH Q8] How many dimensions? How many combinations and interactions? How demonstrated?

Homogeneous vs. heterogeneous systems Likelihood of “stealth” variables

“The multidimensional combination and interaction of input variables. . .and process parameters that have been demonstrated to provide assurance of quality.” [from ICH Q8] How many dimensions? How many combinations and interactions? How demonstrated?

Homogeneous vs. heterogeneous systems Likelihood of “stealth” variables


QbD Philosophy

QbD is about connecting the molecule and the patient. Science-based product/process design begins with the

API molecular entity and is geared to meet patient needs for pharmacotherapy which is safe, effective, convenient and of consistently high quality.

All products are designed and developed to be of high quality; QbD provides a structured framework for documenting and presenting development rationale, experience and knowledge of the formulation and the process, and to ensure manufacture of products consistently fit for patient use.

QbD is about connecting the molecule and the patient. Science-based product/process design begins with the

API molecular entity and is geared to meet patient needs for pharmacotherapy which is safe, effective, convenient and of consistently high quality.

All products are designed and developed to be of high quality; QbD provides a structured framework for documenting and presenting development rationale, experience and knowledge of the formulation and the process, and to ensure manufacture of products consistently fit for patient use.


Patient Requirements

Content UniformityContent Uniformity PotencyPotency StabilityStability PurityPurity Consistent BioavailabilityConsistent Bioavailability Cover Range of PotenciesCover Range of Potencies Readily Available in Distribution ChannelsReadily Available in Distribution Channels Convenient and Pharmaceutically ElegantConvenient and Pharmaceutically Elegant

Content UniformityContent Uniformity PotencyPotency StabilityStability PurityPurity Consistent BioavailabilityConsistent Bioavailability Cover Range of PotenciesCover Range of Potencies Readily Available in Distribution ChannelsReadily Available in Distribution Channels Convenient and Pharmaceutically ElegantConvenient and Pharmaceutically Elegant


Properties of the Molecule: Technical Challenge

pKa near neutral BCS Class III Hydrochloride Salt Acidic pH favors stability Dose ≤ 10 mg Primary degradation reaction occurs both in solid

state and in solution Accelerates in presence of commonly used tablet

excipients Accelerates with common processing conditions (roller

compaction, wet granulation, compression)

pKa near neutral BCS Class III Hydrochloride Salt Acidic pH favors stability Dose ≤ 10 mg Primary degradation reaction occurs both in solid

state and in solution Accelerates in presence of commonly used tablet

excipients Accelerates with common processing conditions (roller

compaction, wet granulation, compression)


QbD Approach--Tablet FormulationActive Film Coating

Inert tablet core

Inner layer: seal coat of coating material

Middle layer: drug + same coating material

Outer layer: with same coating material

This approach avoids•compaction process•granulation process•direct drug contact with excipients

Protects drug from environmental moistureAcidic environment used for all three layers

[SCHEMATIC]


Manufacturing Process

ConventionalExcipients

Lubricant COURTOYR-100

COURTOYR-100

COURTOYR-100

200 mgtablet cores

Polymer coat

pH 2Polymer coat

pH 2

APIPolymer coat

pH 2

Tablet Printing

Blend (5 minutes) Blend (3 minutes)Tablet Compression

Middle Layer Coat Outer Layer Coat

In process monitoring: Weight gain Weight gain Weight gain Raman HPLC

Inner Layer Coat


CQAs:

Content Uniformity &

Potency

• Formulation optimization- API-to-polymer ratio - Suspension pH- Suspension Uniformity- Suspension viscosity and solids content- Coat thickness

• Spray Nozzle optimization

- Optimize air flow of spray gun for droplet size and spatial distribution- Angle and distance of nozzles

• Thermodynamic optimization

-Spray rate -Inlet temperature-Air flow

• Tablet bed optimization in coater- Baffle configuration- Pan load- Pan speed

Variables Considered to Define Design Space


Formulation Factors

HPMC- and PVA-based coating formulations were HPMC- and PVA-based coating formulations were evaluated. evaluated. Opadry II, a PVA-based coating formulation, provided Opadry II, a PVA-based coating formulation, provided

the best stabilitythe best stability

Tablets were most stable when pH of the coating Tablets were most stable when pH of the coating suspension was adjusted to around 2 for all three suspension was adjusted to around 2 for all three layerslayers

Three layer-coated tablets were more stable than Three layer-coated tablets were more stable than those coated with two layers (i.e., omission of either those coated with two layers (i.e., omission of either inner or outer layer decreased stability)inner or outer layer decreased stability)

HPMC- and PVA-based coating formulations were HPMC- and PVA-based coating formulations were evaluated. evaluated. Opadry II, a PVA-based coating formulation, provided Opadry II, a PVA-based coating formulation, provided

the best stabilitythe best stability

Tablets were most stable when pH of the coating Tablets were most stable when pH of the coating suspension was adjusted to around 2 for all three suspension was adjusted to around 2 for all three layerslayers

Three layer-coated tablets were more stable than Three layer-coated tablets were more stable than those coated with two layers (i.e., omission of either those coated with two layers (i.e., omission of either inner or outer layer decreased stability)inner or outer layer decreased stability)


Elements of QbD: Preliminaries to Studying the Coating Process

Placebo cores are subjected to 100% on-line weight check; Placebo cores are subjected to 100% on-line weight check; controlled to 200 mg controlled to 200 mg ± ± 2%.2%.

A round biconvex tablet shape was chosen for durability, ease of A round biconvex tablet shape was chosen for durability, ease of coating and improved content uniformity.coating and improved content uniformity.

The process for dissolution of API in the coating vehicle was The process for dissolution of API in the coating vehicle was qualified using a UV fiber-optic probe.qualified using a UV fiber-optic probe.

A re-circulation loop was designed in the tank to prevent A re-circulation loop was designed in the tank to prevent sedimentation of pigments in the coating dispersion. A Raman sedimentation of pigments in the coating dispersion. A Raman probe was used to confirm the homogeneity of the coating probe was used to confirm the homogeneity of the coating dispersion. (Mixing design was optimized before undertaking spray dispersion. (Mixing design was optimized before undertaking spray characterization.)characterization.)

Brooks air flow controllers are used for monitoring atomization air Brooks air flow controllers are used for monitoring atomization air feed into the spray guns.feed into the spray guns.

12 R. A. Lipper – PAT/QbD Workshop – Sept 11, 2006Proprietary Information

4

6

8

10

12

14

16

18

4 8 12 16 20 24 28 32

Time (h)

Op

adry

Co

nce

ntr

atio

n (

wt%

)

Add Opadryover 10 min(200 rpm)

Start Pump (22 psig)Reduce stirring to 100 rpm

Move probe to 2" below surface

Replace probe 5" below surfaceLeave overnight

Turn off stirringPump running

Turn on stirring(100 rpm)

Turn off pumpTurn stirring (100 rpm)off-on-off

Leaveover weekend

In-Line Raman Monitoring for Coating Suspension System Design


Spray Characterization and Design

GoalGoal Identify spray system hardware, configuration and operating parameters Identify spray system hardware, configuration and operating parameters

to produce:to produce: Flat, focused spray pattern with uniform droplet size and intensity Flat, focused spray pattern with uniform droplet size and intensity

(narrow(narrow RSD)RSD) Uniform and stable spray coneUniform and stable spray cone

ApproachApproach Characterize spray with two-camera imaging system (Off-line)Characterize spray with two-camera imaging system (Off-line)

Profile camera measures spray cone angle, spray intensity, and spray Profile camera measures spray cone angle, spray intensity, and spray axis angleaxis angle

Droplet camera measures droplet size distribution (DV50 and DV90), mean droplet speed, and droplet density

Effect of various parameters (Off-line)Effect of various parameters (Off-line) Nozzle typesNozzle types Nozzle operation under controlled air flow rates Solid content in coating suspensionSolid content in coating suspension Air/liquid ratioAir/liquid ratio

GoalGoal Identify spray system hardware, configuration and operating parameters Identify spray system hardware, configuration and operating parameters

to produce:to produce: Flat, focused spray pattern with uniform droplet size and intensity Flat, focused spray pattern with uniform droplet size and intensity

(narrow(narrow RSD)RSD) Uniform and stable spray coneUniform and stable spray cone

ApproachApproach Characterize spray with two-camera imaging system (Off-line)Characterize spray with two-camera imaging system (Off-line)

Profile camera measures spray cone angle, spray intensity, and spray Profile camera measures spray cone angle, spray intensity, and spray axis angleaxis angle

Droplet camera measures droplet size distribution (DV50 and DV90), mean droplet speed, and droplet density

Effect of various parameters (Off-line)Effect of various parameters (Off-line) Nozzle typesNozzle types Nozzle operation under controlled air flow rates Solid content in coating suspensionSolid content in coating suspension Air/liquid ratioAir/liquid ratio


Comparison of Nozzle Types I and II :

Selection criteria: flat, focused spray pattern with uniform droplet size and intensity.

Cone angle of (A) Type I and (B) Type II nozzles

A B

Effect of Nozzle Type


• Cone angle, droplet size, and droplet density are affected by suspension formulation (API-to-polymer ratio) and flow rate. Spray parameters are customized to assure content uniformity at different API-to-polymer ratios.

• Droplet size and cone angle decrease with increased air flow rate

• Too high a ratio of pattern air to atomizing air can create a hollow spray cone which (in this case) would adversely affect content uniformity

• Air volume is much preferred over air pressure to control the droplet size distribution and pattern of the spray, and is independent of coater scale or “plumbing”

Spray Characterization: Summary


Coating Control: Use of Raman to Monitor the Inner Layer

Opadry

A.U

.

Coating Progress

Tablet Core

A U

Wave number (cm-1)


Setup of Raman Probe for In-Line Coating Monitoring

Pan size: 36”Pan size: 36”

Pan speed: 12 rpmPan speed: 12 rpm

Distance from the bed: ~ 4 Distance from the bed: ~ 4 inchesinches

Scan time: 24 secScan time: 24 sec


0

5

10

15

20

25

30

35

40

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6

Time (hours)

Inte

gra

ted

Pea

k A

rea

Bed Temperature Adjustment

Coating Initiated

Coating Kinetics of the Inner Layer Followed by In-Line Raman Spectroscopy

El Hagrasy, A., Chang S-Y., Desai, D. and Kiang, S. American Pharmaceutical Review 9(1):40-45 (2006)


Middle (Active) Layer Monitoring (2.5 mg API Coated tablets)

40

50

60

70

80

90

100

110

30 40 50 60 70 80 90 100 110

% Theoretical Potency (Based on Weight Gain)

Act

ual

Po

ten

cy,

%

% Target Weight Gain

% Potency

50.0 47.873.5 70.990.3 87.5

102.0 99.7


Raman Prediction of the Inner Layer from Different Spatial Locations60”(I)48” (I)

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

1 2 3 4 5 6Location

% W

eig

ht

Gain

Raman Gravimetric

Location

% W

eig

ht

Gain

60” (II)

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

1 2 3 4 5 6Location

% W

eig

ht

Gain

Raman Gravimetric

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

1 2 3 4 5 6Location

% W

eig

ht

Gain

Raman Gravimetric

48” (II)

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

1 2 3 4 5 6

Raman Gravimetric

El Hagrasy, A., Chang S-Y., Desai, D. and Kiang, S. Journal of Pharmaceutical Innovation. Accepted (2006)


Monitoring/Control of Coating: Summary

First coating layer can be monitored using a Raman First coating layer can be monitored using a Raman probe (feasible to do at-line as well) and/or weight gainprobe (feasible to do at-line as well) and/or weight gain

Second coating layer (active layer): API deposition can Second coating layer (active layer): API deposition can be monitored using weight gain and/or an off-line rapid be monitored using weight gain and/or an off-line rapid HPLC or UV fiber-optic methodHPLC or UV fiber-optic method

Third coating layer can be monitored using an off-line Third coating layer can be monitored using an off-line Raman probe and/or weight gainRaman probe and/or weight gain

The process has been successfully scaled using 24 inch, The process has been successfully scaled using 24 inch, 36 inch, 48 inch, and 60 inch Compu-Lab coaters (Batch 36 inch, 48 inch, and 60 inch Compu-Lab coaters (Batch sizes: 14 to 215 kg)sizes: 14 to 215 kg)


Classification of Process Variables

Inherently Variable

Tightly Controllable

Non-Critical Critical

Fix Fix, determine PAR (EOF*)

Determine target, NOR and PAR

Determine target, NOR, PAR (EOF*)

PAR = Proven Acceptable Range; NOR = Normal Operating Range; EOF = Edge of Failure

*If frank failures are observed, EOF should be estimated


Parameters Fixed for DOE

36 inch Compu-Lab coater36 inch Compu-Lab coater Batch size 50 kg (250,000 tablets)Batch size 50 kg (250,000 tablets) Large bafflesLarge baffles Type I nozzles Type I nozzles Nozzle distance from tablet bedNozzle distance from tablet bed Ratio of pattern air to atomizing airRatio of pattern air to atomizing air Coating pan speed Coating pan speed Tablet bed temperatureTablet bed temperature Dew point Dew point 10C 10C

36 inch Compu-Lab coater36 inch Compu-Lab coater Batch size 50 kg (250,000 tablets)Batch size 50 kg (250,000 tablets) Large bafflesLarge baffles Type I nozzles Type I nozzles Nozzle distance from tablet bedNozzle distance from tablet bed Ratio of pattern air to atomizing airRatio of pattern air to atomizing air Coating pan speed Coating pan speed Tablet bed temperatureTablet bed temperature Dew point Dew point 10C 10C


Formulation and Process Optimization DOE

Design:

API concentration API/Polymer Ratio

Inlet Temperature

oCTotal Spray Rate

from 3 guns (g/min)

Atomizing Air+Pattern air

per gun (SLPM)Air Volume

(CFM)LOW(-1) 2% 1:8 50.00 60.00 200.00 525.00

CENTER(0) 4% 1:4 52.50 81.00 250.00 560.00HIGH(+1) 8% 1:1 55.00 105.00 300.00 600.00

Actual Levels used for LOW(-1), CENTER(0), and HIGH(+1)

Design: API Film Coated Tablets 2^(5-1) Fractional Factorial with 3 Center Points Designs – 19 Runs


Creating the Process Design Space: Process Parameters Studied

Screening for Parameter Ranges for Optimal Content

Uniformity

Ato

miz

ing/

Pat

tern

Air

Vol

ume Air Volume

Inlet Air Temperature

Spr

ay ra

te

% API in suspension

AP

I/Opa

dry

Rat

io

Sp

ray

rate

% A

PI in

susp

en

sion

Critical Parameters:

API application rate was most criticalfor content uniformity.

60

75

0.75

5

0.75 8

1:1

1:8200

300

525 600

50

55

60

105

DOE


Summary of Potency and Content Uniformity Results of Second Layer Coated Tablets

Average Potency

(%) % RSD6C4329X 102.2 100.2 3.36C4330X 99.8 98.0 2.86C4331X 99.5 97.5 2.86C4332X 99.7 100.2 2.66C4333X 99.2 98.3 2.96C4334X 100.3 99.0 3.66C4323X 102.0 98.7 3.96C4324X 101.8 100.6 3.26C4325X 101.1 99.0 3.16C4326X 100.4 98.7 2.96C4327X 99.8 97.6 2.86C4349X 100.5 97.4 2.3

Potency Lot #

In-Process Potency (%) at Coating Endpoint

Content Uniformity n = 30

5 mg

10 mg

1 mg

2.5 mg


Towards Process Understanding

Based on risk assessment around the chosen formulation Based on risk assessment around the chosen formulation and processing approach, content uniformity and potency and processing approach, content uniformity and potency of tablets are considered to be the most critical product of tablets are considered to be the most critical product quality attributesquality attributes

Variables were systematically analyzed for their potential Variables were systematically analyzed for their potential to influence the critical quality attributesto influence the critical quality attributes

Controlled experiments including DOE were conducted Controlled experiments including DOE were conducted around the key variables to establish reliable operating around the key variables to establish reliable operating rangesranges

The process has been shown to be capable of consistently The process has been shown to be capable of consistently achieving content uniformity RSD of 2.8-3.9%achieving content uniformity RSD of 2.8-3.9%

Based on risk assessment around the chosen formulation Based on risk assessment around the chosen formulation and processing approach, content uniformity and potency and processing approach, content uniformity and potency of tablets are considered to be the most critical product of tablets are considered to be the most critical product quality attributesquality attributes

Variables were systematically analyzed for their potential Variables were systematically analyzed for their potential to influence the critical quality attributesto influence the critical quality attributes

Controlled experiments including DOE were conducted Controlled experiments including DOE were conducted around the key variables to establish reliable operating around the key variables to establish reliable operating rangesranges

The process has been shown to be capable of consistently The process has been shown to be capable of consistently achieving content uniformity RSD of 2.8-3.9%achieving content uniformity RSD of 2.8-3.9%


Utilization of Design Space for Tech Transfer

Coating Suspension

Homogeneity

Nozzle

CharacterizationCoating

Process

• Optimal design of mixing tank

•Raman spectroscopy

• Real-time Imaging

Technology

• Raman Spectroscopy

Final Product

Coating Suspension

Homogeneity

Nozzle and tablet

flows

Characterization

• Optimization of spray pattern

•Support scale-up

•Specify process parameters to enhance tech transfer

Coating

Process

•Real-time monitoring of the coating kinetics

•Effect of process variables on coating uniformity

•Fast check of coating uniformity

•Develop an index of mixing efficiency

•Determination of coating end point

Final Product

•Minimize risk of sedimentation

•Continuous verification of TiO2 content

DEM and PBE models are being developed to predict coating uniformity and coating weight in production coater

• fast-HPLC

• UVFO

• Raman / NIR


DEM-1Mmodel

PBE-2 zonemodel

RSD modelfor Production

Coater

Workflow for Coating Process Model

PAT applications

Thermodynamics& mass transfer

Formulation

1.Predict RSD2.Reduce DoE batches3.Provide added insightto design space for CMC

Nozzle optimizationFeed tank optimization and scale-upAt-line uniformity analysistablet velocity characterization


Summary

A product design approach was chosen to address the A product design approach was chosen to address the chemical instability of the API in traditional formulationschemical instability of the API in traditional formulations

A clear and complete process understanding is being A clear and complete process understanding is being created during product development to assure process created during product development to assure process robustnessrobustness

Several PAT techniques, some with potential for in-line Several PAT techniques, some with potential for in-line process control, are being utilized to develop a deeper process control, are being utilized to develop a deeper process understandingprocess understanding

Reliable operating ranges have been established for key Reliable operating ranges have been established for key process variablesprocess variables

Process understanding gained through the QbD approach Process understanding gained through the QbD approach is being leveraged in scale-up and technology transferis being leveraged in scale-up and technology transfer

A product design approach was chosen to address the A product design approach was chosen to address the chemical instability of the API in traditional formulationschemical instability of the API in traditional formulations

A clear and complete process understanding is being A clear and complete process understanding is being created during product development to assure process created during product development to assure process robustnessrobustness

Several PAT techniques, some with potential for in-line Several PAT techniques, some with potential for in-line process control, are being utilized to develop a deeper process control, are being utilized to develop a deeper process understandingprocess understanding

Reliable operating ranges have been established for key Reliable operating ranges have been established for key process variablesprocess variables

Process understanding gained through the QbD approach Process understanding gained through the QbD approach is being leveraged in scale-up and technology transferis being leveraged in scale-up and technology transfer


Project Leads:Divyakant DesaiSan Kiang

Formulation and Drug Product Process:William EarlyCharles Van KirkHoward StamatoSrinivasa ParuchuriSanjeev Kothari

API Process:Steven ChanJohn Korzun

Analytical R&D:Harshad PatelLeon LiangXujin Lu

PAT:Arwa El-HagrasyDon KientzlerWei ChenShih-Ying Chang

Technical Operations:Howard MillerMegan Schroeder

DEM modeling:Fernando Muzzio (Rutgers University)

Regulatory Sciences:Steve Liebowitz

Acknowledgements


Backup slides


Formulation and Process OptimizationDOE - API versus Polymer Amounts

-- Each batch was coated up to 10-mg potency. Tablets corresponding to 2.5-mg and 5-mg were collected at the appropriate times (theoretical weight gain) and results were treated separately. -- Effectively, three separate DOEs were performed for the three strengths: 2.5 mg, 5 mg and 10-mg, respectively.

API/Polymer Ratio

% w/w in Coating Suspension

API Opadry II White

Total SolidsDissolved / Suspended

1:1 8 8 16

1:4 4 16 20

1:8 2 16 20

Amount per Tablet (mg)

2.5 mg Tablets 5 mg Tablets 10 mg Tablets

API Opadry II White

API Opadry II White

API Opadry II White

2.5 20 5 40 10 80

2.5 10 5 20 10 40

2.5 2.5 5 5 10 10


Representative Tablet Formulations

IngredientIngredient 1 mg1 mg 2.5 mg2.5 mg 5 mg5 mg 10 mg10 mg

Inert CoreInert Core 200 mg200 mg 200 mg200 mg 200 mg200 mg 200 mg200 mg

Inner LayerInner Layer

Opadry II WhiteOpadry II White 6 mg6 mg 6 mg6 mg 6 mg6 mg 6 mg6 mg

Middle LayerMiddle Layer

APIAPI 1 mg1 mg 2.5 mg2.5 mg 5 mg5 mg 10 mg10 mg

Opadry II WhiteOpadry II White 8 mg8 mg 20 mg20 mg 20 mg20 mg 10 mg10 mg

Outer LayerOuter Layer

Opadry II Opadry II ColorColor

7 mg7 mgColor AColor A

7 mg7 mgColor BColor B

7 mg7 mgColor CColor C

7 mg7 mgColor DColor D

Design Space

Technology

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