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Connecting People, Science and Regulation ®

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Risk Assessment and DoE must be usedin Synergy for the success of QbD

Alain Poncin

Process Development Unit Manager

LFB Biotechnologies

Quality by Design, Frankfurt


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Quality by Design

� Science

� Statistics

� Risk Management

Knowledge

- of the productionprocess

- of the product

summarized in the RiskAssessment Report


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Risk Management� Technical report 42, PDA (2005)

� ICH Q8 : Pharmaceutical Development (2005) and annex(2007)

� ICH Q9 : Quality Risk Management (2005)

� ICH Q10 : Pharmaceutical Quality System (2008)

� ICH Q11 : Development and Manufacture of Drug Substance (concept paper, 2008, draft expected in 2009)

Focused on Product Quality

� ISO13485 : Medical devices – Quality management systems– Requirementsfor regulatory purposes

� ISO14971 : Medical devices – Application of Risk Management to medicaldevices

Focused on Product Quality + Product Availability

Pharma :

Compliance

Medical Device

Compliance

Economy


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Risk Management at LFB Biotechnology

WhenWhenStandard initial Risk analysis (FMEA) as soon as a first lab process gives

satisfactory resultsUpdated during product/process development, clinical development and post

approval.HowBased on standardised ‘’blocks’’ (Upstream, Harvest, Chromatography,

Ultra/diafiltration,…) ‘’Personnalised’’ using what is known : protein stability, ease/difficulty of steps,

occurrence of hasard,…

Ranks the work to be performed during development and process characterisationReflects and summarisesall what is known about the protein and the process


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Initial Risk analysis

1- Process Flow ChartPreculture Fermentation Harvest Filtration

Chromatography 1Viral inactivationChromatography 2

Ultrafiltration FiltrationFiltration

Vialing


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2- Table of content

Cleaning after purification5.6

Purification5.5

Sample preparation5.4

Storage of intermediates5.3

System assembly5.2

Cleaning beforechromatography

5.1

Capture of targetproduct after harvest

Capture by Chromatography

5

JustificationSub systemSystemN°


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3- Risk Analysis

� Based on previous experience, building of new blocks for thisfirst Risk Analysis at LFB Biotechnologies

� Copy and paste to a ‘’white’’ Risk Assessment

� Missing blocks (viral inactivation, nanofiltration,…) speciallyfor plasma product

� Not adapted to LFB Biotechnologies (history,…)

� Final analysis not homogeneous


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Lack of homogeneity:

1055Written SOP

Trained staff

3Human error7Contamination/loss of sample

Wrong buffer for equilibration

Ultra/

Diafiltration

6.8

243Trained staff

WrittenSOP/method of production

2Human error

(inversion of buffers)

4Contamination of targetproduct

Wrong buffer for equilibration/wash and or elution

Purification5.5

543Qualifiedequipment, preventivemaintenance

Trained staff

Calibration beforeuse

3Defectiveequipment (pH, scale,…)

6Ultra/diafiltration failure, contamination or degradationof targetproduct

Wrong buffer (pH, conductivity)

Buffer preparation

2.2

RPNDRisk controlPPossible causeSPossible Effect(harm)

Possible Hazard/

Failure

Product, Part, System, Fonction

N#


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To increase homogeneity and quality of RA:� Define risks

� For the Product safety/efficacy/availability-contamination (physical, chemical,…)-degradation (lower yield, production failure, immunogenicity)

� Identify risks for a general ‘’process’’

� Identify Possibles causes (human, material,…)

� Identify the measures to reduce the risk

� Adapt for each kind of process : fermentation, chromatography, ultrafiltration,…


10Storage of Matrix/column5.8

Cleaning after purification5.7

Product recovery5.6

Purification5.5


Storage and expiration time of intermediates

5.3

Cleaning beforechromatography

5.2

System assembly and calibration5.1

Capture of targetproduct after harvest


5



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2- Table of content

Membrane/carter Storage6.8

Cleaning afterultra/diafiltration

6.7

Product recovery6.6

Ultra/diafiltration6.5


Storage and expiration time of intermediates

6.3

Cleaning beforeultra/diafiltration

6.2

System assembly and calibration

6.1

Buffer ExchangeUltra/diafiltration6



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5- Quantification of Residual Risk

247

30

30

RPN

7

3

3

D

7

5

5

S

5

2

2

P

Identification of critical factors

Trained staff

WrittenSOP/method of production

Automation

Description/QC of raw material

Approvedsuppliers

Risk Control, Measures of Risk reduction, Tests

To be determinedContamination of Drug Product

Ineffective purification

Purification5.5.6

Human errorContamination of Drug product

Wrongbuffer (pH, conductivity)

Purification5.5.1

Reagentsidentity/Quality

Purification failure,

Production stopped

Wrongpreparation(saltaddition, …

Samplepreparation

5.4.5

Possible causePossible effect(harm) of the hazard/failure

Possible hazard/

failure

Product, Part, System, Function, Process

N#


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Risk Priority Number

� RPN = Severity x Probability x Detectability

� Require Internal Policy Definition� At LFB Biotechnology : 4 levels :

o 1 to 100 : broadly acceptable region o 101 to 150 : as low as reasonable practicable region (ALARP), part I o 151 to 250 : as low as reasonable practicable region (ALARP), par II

o 251 to 1000 : intolerable region


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6- Initial Risk Analysis conclusions

Final choice of filter type0.22 µm filtration8

Well known and controlled step, yet close to the optimum (load, wash and elution)

Chromatography7

Need first evaluation of viral clearance before First in Man

Viral Inactivation6

Not used in standard conditions, need identification of critical parameters to obtain a reproducibleprocess


5

Final choice of filter type0.22 µm filtration4

Need further comparability studies to assessstarting material equivalency

Clarification3

Current status/notesSystemStep


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� From initial Risk analysis : identification of capture purification step as a high risk Step

� To reduce this risk : identification of critical factor s and critical quality attributes.

Experience (int./ex.) Process development Initial Risk AssesmentPublication review First lab scale productionPatent review

Identification of critical factors by

DoE


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Particularity of DoE in Process Development

Protein folding : protein concentration, pH, Salt, Organic solvent,… 14 factors

Chromatography : pH and conductivity for equilibration and elution, sample load, matrix and

column resolution,… 10 factors

Ultrafiltration : pump speed, Pin, Pout, membrane, temperature, volume of buffer,…8 factors

Design space highly multidimensional

2 n experiments (full factorial) cannot be used,

2 n-k experiments (semi factorial) used for identification of critical factors


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Even 2 n-k experiments are a huge amount of work (process+ analytics)

Before starting experiments :

� Are Analytic tools sufficient ?

� Which Design : (semi) factorial ?

� Which factors to test ?

� Which Range (Design Space) ?


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Which Design ?

Full

Semi


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� Which factors and which Design space ?


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Experimental Work


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Output (Quality attributes)

� capture step : high yield, reproducible

Quantification of target protein biological activity

Quantification of total proteins

Purity by SDS-PAGE

On Load, Flow Through and Peak (23 samples)

Calculation of step yield and specific activity


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Results : usually nice graphics

Design-Expert® Software

Yield92

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X1 = B: Conductivity sampleX2 = D: pH elution

Actual FactorsA: pH sample = 7.07C: Load = 30.00E: Gradient = 15.41

2.50

4.38

6.25

8.13

10.00

6.50

7.00

7.50

8.00

8.50

0

25

50

75

100

Y

ield

B: Conductivity sample D: pH elution


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But in another region of the space…


Yield92

10



2.50

4.38

6.25

8.13

10.00

6.50

7.00

7.50

8.00

8.50

0

25

50

75

100

Y

ield



Yield92

10



2.50

4.38

6.25

8.13

10.00

6.50

7.00

7.50

8.00

8.50

0

25

50

75

100

Y

ield



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Results : critical factors : half normal plot of effects

Design-Expert® SoftwareYield

Error from replicates

Shapiro-Wilk testW-value = 0.962p-value = 0.794A: pH sampleB: Conductivity sampleC: LoadD: pH elutionE: Gradient

Positive Effects Negative Effects

Half-Normal Plot

Ha

lf-N

orm

al

% P

rob

ab

ility

|Standardized Effect|

0.00 7.63 15.25 22.88 30.50

01020

30

50

70

80

90

95

99

A

C

E

- + Factor Effect = slope/2

E

A

C


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Or pareto chart


A: pH sampleB: Conductivity sampleC: LoadD: pH elutionE: Gradient

Positive Effects Negative Effects

Pareto Chart

t-V

alu

e o

f |E

ffe

ct|

Rank

0.00

1.56

3.12

4.68

6.24

Bonf erroni Limit 4.38176

t-Value Limit 2.57058

1 2 3 4 5 6 7

E

A

C


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Are they significants ? ANOVA

ANOVA for selected factorial modelAnalysis of variance table [Partial sum of squares - Type III]

Sum of Mean F p-valueSource Squares df Square Value Prob > FModel 4129 3 1376 28,8 0.0014 A-pH sample 1301 1 1301 27,2 0.0034 C-Load 968 1 968 20,3 0.0064 E-Gradient 1861 1 1861 38,9 0.0015Curvature 960 1 960 20,1 0.0065Residual 239 5 48Lack of Fit 207 4 52 1,6 0.5244Pure Error 32 1 32Cor Total 5328 9

- +Factor


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ANOVA : Statistical analysis : can you do it ?


Color points by value ofYield:

82

5

Internally Studentized Residuals

No

rma

l %

Pro

ba

bil

ity

Normal Plot of Residuals

-1.94 -0.97 0.00 0.97 1.94

1

5

10

20

30

50

70

80

90

95

99


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What is the value of the model obtained ?


Color points by value ofYield:

82

5

2

Actual

Pre

dic

ted

Predicted vs. Actual

5.00

24.25

43.50

62.75

82.00

5.00 24.25 43.50 62.75 82.00


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Finally, capture step can be optimised


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Capture step by DoE and rangesDesign-Expert® Software

AS

Design Points

X1 = D: Conductivity

Actual FactorsA: Contact Time = 90B: pH load = 7.5C: Column Volume = 8E: Elution temperature = 20

20 25 30 35 40

8

25.75

43.5

61.25

79

D: Conductivity

AS

One Factor

25 + 5 mS/cm

NOR

PAR

Edge of failure

?

Definition of Criticals

Parameters Nice results isn’t ?


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But following purification results did not correlated wellwith prediction from this model.

A new analysis was performed with more powerfull tools.

Two main raisons were implied in the failure of the first model

� One critical factor not identified� High collinearity of some factors


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How many factors to select ?

Adjusted R-Squared or Mallows’CP statistics

Selection of number of factor

0

20

40

60

80

100

0 1 2 3 4 5

Number of factor

R S

quar

ed

0

500

1000

1500

2000

Cp


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High collinearity : regression by least square not efficient

-0.2684

-2.9287

Factor 3

-0.1870

-1.5614

Factor 2

0.67410.01 (ridge regression)

4.26370.0 (classical regression)

Factor 1Ridge parameter

Use of Ridge statistics


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Lack of detection of one critical factor

- +

FactorEffect = 0 D : pH elution

The new Model is predictible for the purifications performed (up to now)


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Finally, update of the initial Risk Analysis

2477Identification of critical factors

5To be determined7Contamination of Drug Product


Purification5.5.6

303Description/QC of raw material

Approvedsuppliers

2Reagentsidentity/Quality

5Purification failure,

Production stopped

Wrongpreparation(saltaddition, …

Samplepreparation

5.4

RPNDRisk Control, PPossible causeSPossible effectHazardSystem, N#

1205Qualification of equipment, preventivemaintenance

Trained staff

4Contact Time tooshort (< 2 min)

Other factorsunder control

6Contamination of Drug Product


Purification5.5.6

1255Quantification of proteolyticactivities

Written SOP

Automation

5Reagentsidentity/Quality

5Increase of proteolyticactivities

Production failure

Wrongpreparation(buffer addition)

Samplepreparation

5.4


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Synergy of Risk Management and DoEExperience (int./ex.) First lab scale Initial Risk AssesmentPublication review ProductionPatent review Process

Identification of criticalfactors by DoE

Risk Assesment Update

Process optimisation

Process capability indices Risk Assesment Update(Six Sigma)

Process Characterisation

Risk Assesment update

Process Validation

Statistics Risk Assesment update Phamacovigilance(trends,…)

Process Development

Phase I

Phase II/IIII

First in Man

GMP for Phase I

CTDPhase IV

Product discontinuation


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And in the future

� Increased number of experiments (// chromatography, 96 wells technology)

� Application to ultra/diafiltration

� Introduction of additional statistic tools (bayesianstatistics, Monte Carlo simulation, …)

� More applications of Six Sigma

� PAT


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Economical impact of QbD : example

Eurogentec s.a.

010

203040

5060

87 88 89 90 91 92 93 94 95 96 97 98 99-00

00-01

01-02

02-03

03-04

04-05

05-06

06-07

07-08

Turnover in millions € Nber of employees x 10

slides pda qbd

Documents

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risk assessment report2

n product

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