Quality by Design for Legacy Products - A Contradiction ?

Qualification and Verification of Manufacturing Processthroughout the Product Life Cycle

1

Quality by Design for Legacy ProductsA Contradiction ?

Dr. Joerg GampferWCBP 2015- CASSS ConferenceWashington DC Jan 27-29

WCBP/ CASSS Washington DC January 2015

2

FDA Process Validation guideline 2011

Stage IProcessDesign

Stage II2.1 Equipment Qualification2.2 ProcessPerformance Qualification

Stage IIIContinuedProcess

Verification

Applies to:

• Entire product lifecycle:

Development Commercialization

PV guideline does not mention “QbD” but instead references science & risk-based principles described in ICH Q8,9,10,11

Defines commercial process based on knowledge

gained through development and scale-up

Confirms process design is capable of

reproducible commercial manufacturing

Assures continuous state of control during production

QbD as basis for Process Validation


3

Legacy Products:

Development Products:

Stepwise towards pro-active Design

QbD principals can be applied to both legacy products and new development

FDA Process validation guideline requires:

o New Developments: Stage I, Stage II, Stage III (“Process Design” is an integral part of process validation)

o Legacy Products: Stage III (Continued Process Verification)

QbD applies to Legacy and Development


4

Potential Patient Harm Quality Attribute

Variation

Process Parameter

VariationInput Variation

Time

pH

Temperature

Time

pH

Temperature

PotencyPotency

Upper SpecUpper Spec

Lower SpecLower Spec

LSLLSL USLUSL

USLUSLLSLLSL

LSLLSL USLUSL

PPPP

Waste / Loss of Profits

C C C

C Control StrategyControl Strategy

CPPsCPPs CQAsCQAs

Potential Patient Harm Quality Attribute

Variation

Process Parameter

VariationInput Variation

Time

pH

Temperature

Potency

Upper Spec

Lower Spec

LSL USL

USLLSL

LSL USL

PP

Waste / Loss of Profits

CC CC CC

CC Control Strategy

CPPs CQAs

Establish Knowledge which impact process variation has on our product and the impact product variation has on the patient.

QbD: Risk Management Principles


5

TPP QTPPQuality andBusinessattributes

RiskEvaluation

CQAs,

CBAs (*)

ProductDescription

ProcessRisk

Evaluation

CQAs

CBAs

ProcessSteps

& Parameters

PP, CPPs

Process Knowledge:

PP, CPPs, RPN

Customer, Business and Market Driven Definition of Product

Build Process Knowledege CorrelatingProcess Parameters to Product Attributes

(Quality) Target product profile isused to establish product

attributes.Criticality can be assessed for business or quality

aspects ( CQAs / CBAs)

(*) Critical Business Attributes (CBA):

Attributes influencing business

needs and manufacturability

Relating Product and Process


Linking QbD and Process Validation

6

TPP QTPPCQA

CPPProcess Flow

Control Strategy

PPQ

EQ

CPV

PV Stage II:Confirm Control

Strategy

M&C

Continuous Improvement

CBA

PV Stage I: Establish Control Strategy

PV Stage III: Update

Control Strategy

Process Validation following QbD principles ensures efficient Lifecycle Management

Establishing feedback loops between Process Design, Qualification andVerification ensures pre-defined product quality and optimal business results


7

A control strategy is the development and implementation of adequate controls to ensure the continued repeatability of process performance and

the ongoing assurance of finished product quality.

Control Strategy


8

From Development

Opportunities for Legacy Products

Data from Routine

Manufacturing

Platform

Knowledge

Continously update

Control Strategy for

maintaining or

improving:

• Process

Performance

• Product

Quality

Continous collection of process data increases process knowledge:

• Opportunities for identification of criticality

• Opportunities for identification more efficient controls

Use for improvement

of process performance

and product Quality


9

Identification of CQA/CPP relationship

Process Qualification

Process Design

Quality Target Product Profile

Identify Critical Quality Attributes

Identify Critical Process Parameters

Establish Process Controls

Continued Process Verification

Capturing Product and Process Knowledge


1010

Defining CQAs for Legacy Products

Definition of

a list of QA

• Product Specification

• Characterization studies

• Manufacturing Experience

workshop

• Organized with all critical functions

Identificatio

n of CQA

• CQA Assessment report

• Inclusion of CQAs in the Manufacturing Process Control Plan (MPCP)

• Issuance of the RACT (Risk Assessment and Control Table) for legacy product

Methodology used to define CQA:

Assessment performed with participants from all related facilities. Representatives of

the Pre-Clinical and Clinical Affairs group participated.


1111

Defining CPPs

List of CPPs

&

Report issued

Validation data Development

reports

Divisional

methodology

Manufacturingexperience,

Platform data

Identifying Process impact on Product Quality


2G. POTENTIAL CAUSES / INPUT CONTROLS 2H. TEST CONTROLS

Potential Causes

of Failure

Input Controls O Test Controls D PN Actions / Rationale

(Status)

S O D PN

Incorrect

amounts of

components

Speci fications for

buffer

components

1 In-l ine pH s ens or 1 5 Not requi red 5 1 1 5

2I. RISK EVALUATION / ACTIONS

Identify Controls for CPPs

Complete Process FMEA

• Process input variation and errors which could cause the failures are identified.

• The probability of occurrence and detection is estimated, given the implemented

controls. A Priority Number is calculated to evaluate risk and drive action, if needed.

pH | �� Process Spread �� |

LSL USL

LSL USL

| �� Process Spread �� |

Acceptable, no further

action required

Not acceptable, reduction

required

1-12

ActionsPriority

13-52

52-125

Acceptable, but investigate

reduction

Sources of Data

SPC Charts / Capability Analysis

Product Control Records

Occ

urr

en

ce

De

tect

ion

12WCBP/ CASSS Washington DC January 2015

1313

Stage three deployment: objective

Deployment of Control Strategy

The process includes the following steps:

1- Selecting Process Elements,

2- Selecting Monitoring Points & Limits,

3- Collecting Process Data,

4- Consolidating & Trending Data, and finally,

5- Reacting to Significant Events.

Evaluating current Control Strategy andidentifying opportunity for improvements


14

Improving the Control Strategy along Life Cycle

• Taking long range variation into account

• Capture influence of additional factors ( e.g. change in raw materials)

• Apply new technologies

• React to new requirements ( e.g. metal impurities)

• Further shift from end-product testing to controlling unit operations

What is driving changes to Control Strategy ?


5550454035302520

17,5

15,0

12,5

10,0

7,5

5,0

Avg Detection Risk

Av

g T

ota

l R

isk

12

16

30

36

40

45

risk

single

Max

A 22

Nanofiltration skid

Media Hold Tank

Harv esting, filtration and dilution

C hemostat

Buildup- 40 L; 320 L ; 2500L bioreactors

Inoculum Roller bottles

Inoculum Roux F lasks

Scatterplot of Avg Total Risk vs Avg Detection Risk

15

• Improve the „Detection“ in the overall risk (S*O*D)

• If required improve „input controls“ to reduced „Occurence“

Use of PFMEA to identify Opportunities for better Controls

Systematically decrease Process Risks


Better Process Control by Process Understanding

16

Prediction of Protease Activation Time usingupstream process conditions

Plasma factor concentrates are a complex mix of a multitude of coagulation factors withmultiple interactions and feed back reactions. Low yields were attributed to the inability to reliably predict the generation time to achieve a desired activation profile.This time variation is a major issue for manufacturing, i.e. the lack of resource planning.

Using MVDA a set of 8 parameter in various upstream processes have been identified, which allow to predict the generation time with an accuracy of some hours. The prediction was often better than the parallel IPC testing in two labs.

Example 1


0.400.350.300.250.200.150.10

0.45

0.40

0.35

0.30

0.25

0.20

0.15

UV-Start CIT

De

lta

CIT

Atypical

Evolution

Typical

Typical-ref

Visual class

Scatterplot of Delta CIT vs UV-Start CIT

Delta C IT =0.9473 (UV RT-Start C IT)+0.03560

Regression fit (E3)

Control of MAb Elutionsprofile

Affinity chromatography is used for purification manufacturing. Chromatograhpic columnstend to compound with frequent use resulting in reduced purification and yield.

Small changes in the shape of the elution profile have been identified (Multivariate Analysis) , which are associated with this trend. Based on this, the operator dependent decisioncould by replaced by an operator independent model.

Typical elution profile with theparameters used at 280 nm peak.

Blue = ReferenceGreen = typical elution profileRed = aging columnBlack = critical state

Better Process Control by Process Understanding

Example 2


CONFIDENTIAL

18

Approach to Continous Improvement

PPQ Initial CPV Late CPV

Initial CPV Plan

Update riskevaluation

CPV report

Continous

Improvement

Plan

• Periodic CPV report

• Annual ProductReview

late CPV Plan

Update Controls Strategy Process Changes

Continued Process Verification can be used to support efficient continous

improvement activities along the product life cycle

Continued Process Verification governs process improvements

WCBP/ CASS Washington DC January 2015

19

Thank you for your attention


Date post:	15-Apr-2017
Category:	Health & Medicine
Upload:	anthony-grenier
View:	152 times
Download:	2 times

Quality by Design for Legacy Products - A Contradiction ?

Health & Medicine