Risk Assessment in QbD David R. González Barreto 1 QbD Risk Assessment in QbD Introduction and Few...

Risk Assessment in QbDDavid R. González Barreto

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Risk Assessment in QQbbDD

Introduction and Few Tools

David R. González Barreto


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QQbbDD – a systematic approach

TO

OLS

Ishikawa

Capability

FMEA

Pareto

DOE


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• Target the product profile• Determine Critical Quality Attributes (CQAs)• Link input material attributes and process

parameters to CQAs and perform risk assessment

• Develop a design space• Design and implement a control strategy• Manage product lifecycle, including continual

improvement


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• 2.3 Linking Material Attributes and Process Parameters to CQAs – Risk Assessment – Risk assessment is a valuable science-based process

used in quality risk management (see ICH Q9) that can aid in identifying which material attributes and process parameters have an effect on product CQAs. While the risk assessment is typically performed early in the pharmaceutical development, it can be helpful to repeat the risk assessment as information and greater knowledge become available.

Q8(R1) Pharmaceutical Development Revision 1 – from the Guidelines


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• 2.3 Linking Material Attributes and Process Parameters to CQAs – Risk Assessment continued – Risk assessment tools can be used to identify and rank

parameters (e.g., operational, equipment, input material) with potential to have an impact on product quality based on prior knowledge and initial experimental data. For an illustrative example, see Appendix 2. The initial list of potential parameters can be quite extensive, but is likely to be narrowed as process understanding is increased. The list can be refined further through experimentation to determine the significance of individual variables and potential interactions. Once the significant parameters are identified, they can be further studied (e.g., through a combination of design of experiments, mathematical models, or studies that lead to mechanistic understanding) to achieve a higher level of process understanding.


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• 2.4 Design Space – The linkage between the process inputs (input

variables and process parameters) and the critical quality attributes can be described in the design space.


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• 2.4.1 Selection of variables. – The risk assessment and process development experiments can

not only lead to an understanding of the linkage and effect of process inputs on product CQAs, but also help identify the variables and their ranges within which consistent quality can be achieved.

– An explanation should be provided in the application to describe what variables were considered, how they affect the process and product quality, and which parameters were included or excluded in the design space. An input variable or process parameter need not be included in the design space if it has no effect on delivering CQAs when the input variable or parameter is varied over the full potential range of operation. The control of these variables would be under good manufacturing practices (GMP). However, the knowledge gained from studies should be described in the submission.


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FMEA - Objectives

• Failure Mode and Effects Analysis (FMEA) and Failure Modes, Effects identify potential failure modes for a product or process, – to assess the risk associated with those failure

modes, – to rank the issues in terms of importance and – to identify and carry out corrective actions to address

the most serious concerns.


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FMEA Overview

• In general, Failure Modes, Effects Analysis (FMEA) requires the identification of the following basic information:– Item(s)– Function(s)– Failure(s)– Effect(s) of Failure– Cause(s) of Failure– Current Control(s)– Recommended Action(s)– Plus other relevant details


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FMEA Overview

• Basic Analysis Procedure for FMEAThe basic steps for performing an Failure Mode and Effects Analysis (FMEA) or Failure Modes, Effects Analysis include:– Assemble the team.– Establish the ground rules.– Gather and review relevant information.– Identify the item(s) or process(es) to be analyzed.– Identify the function(s), failure(s), effect(s), cause(s) and

control(s) for each item or process to be analyzed.– Evaluate the risk associated with the issues identified by the

analysis.– Prioritize and assign corrective actions.– Perform corrective actions and re-evaluate risk.– Distribute, review and update the analysis, as appropriate.


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Ishikawa Diagram


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Ishikawa Diagram – Minitab Procedure

Worksheet Window – Data Structure


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Input - Menu Selection


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Input Window


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Output Window


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Group Exercise - Ishikawa

• Select a process or sub-process and draw an Ishikawa diagram considering the correspondent, input parameters (Cpp’s or not) and their relationship with CQA’s


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Pareto Diagram


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Pareto Diagram – Minitab Procedure



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Pareto Diagram – Minitab ProcedureInput - Menu Selection


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Input Window


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Output Window

Issues:

-Weighted Paretos

- Nested Paretos

Issues:

-Weighted Paretos

- Nested Paretos


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Risk Priority Numbers

• Most analyses of this type also include some method to assess the risk associated with the issues identified during the analysis and to prioritize corrective actions. A common method is to calculate:

• Risk Priority Numbers (RPNs)


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Risk Priority Numbers• Risk Evaluation Methods

A typical failure modes and effects analysis incorporates some method to evaluate the risk associated with the potential problems identified through the analysis. Many variations of Risk Priority are used. The most typical one follows.

– Risk Priority NumbersTo use the Risk Priority Number (RPN) method to assess risk, the analysis team must:

– Rate the severity of each effect of failure.– Rate the likelihood of occurrence for each cause of failure.– Rate the likelihood of prior detection for each cause of failure (i.e. the likelihood

of detecting the problem before it reaches the end user or customer).– RPN = Severity x Occurrence x Detection– The RPN can then be used to compare issues within the analysis and to

prioritize problems for corrective action. This risk assessment method is commonly associated with Failure Mode and Effects Analysis (FMEA).


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Guidelines for Ocurrence

PROBABILITY of Failure Failure Prob Ranking

Very High: Failure is almost inevitable >1 in 2 10

1 in 3 9

High: Repeated failures 1 in 8 8

1 in 20 7

Moderate: Occasional failures 1 in 80 6

1 in 400 5

1 in 2,000 4

Low: Relatively few failures 1 in 15,000 3

1 in 150,000 2

Remote: Failure is unlikely <1 in 1,500,000 1

Probability


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Guidelines for Severity

Hazardous without warning

Very high severity ranking when a potential failure mode effects safe system operation without warning

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Hazardous with warning

Very high severity ranking when a potential failure mode affects safe system operation with warning

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Very High System inoperable with destructive failure without compromising safety 8

High System inoperable with equipment damage 7

Moderate System inoperable with minor damage 6

Low System inoperable without damage 5

Very Low System operable with significant degradation of performance 4

Minor System operable with some degradation of performance 3

Very Minor System operable with minimal interference 2

None No effect 1

Severity


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Guidelines for Detectability

Detection Likelihood of DETECTION by Design Control Ranking

Absolute Uncertainty Design control cannot detect potential cause/mechanism and subsequent failure mode 10

Very RemoteVery remote chance the design control will detect potential cause/mechanism and subsequent failure mode

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Remote Remote chance the design control will detect potential cause/mechanism and subsequent failure mode 8

Very Low Very low chance the design control will detect potential cause/mechanism and subsequent failure mode 7

Low Low chance the design control will detect potential cause/mechanism and subsequent failure mode 6

Moderate Moderate chance the design control will detect potential cause/mechanism and subsequent failure mode 5

Moderately HighModerately High chance the design control will detect potential cause/mechanism and subsequent failure mode

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High High chance the design control will detect potential cause/mechanism and subsequent failure mode 3

Very High Very high chance the design control will detect potential cause/mechanism and subsequent failure mode 2

Almost Certain Design control will detect potential cause/mechanism and subsequent failure mode 1

Detectability


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FMEA Example - 1


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FMEA Example - 2


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Group Exercise - FMEA

• Using the previously drawn Ishikawa diagram from the selected process or sub-process , and the guidelines for O, S, and D, include several items on the FMEA table and calculate the RPN


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Guidelines for Defining CCP’s


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Using the Criticality Matrix

• To use the qualitative criticality analysis method to evaluate risk and prioritize corrective actions, the analysis team must:

• Rate the severity of the potential effects of failure.• Rate the likelihood of occurrence for each

potential failure mode.• Compare failure modes via a Criticality Matrix,

which identifies severity on the horizontal axis and occurrence on the vertical axis.

• These risk assessment methods are commonly associated with Failure Modes.


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Criticality Matrix


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FMEA - Applications and Benefits

• The Failure Modes, Effects and Analysis (FMEA) procedure is a tool that has been adapted in many different ways for many different purposes. It can contribute to improved designs for products and processes, resulting in higher reliability, better quality, increased safety, enhanced customer satisfaction and reduced costs.

• The tool can also be used to establish and optimize maintenance plans for repairable systems and/or contribute to control plans and other quality assurance procedures. It provides a knowledge base of failure mode and corrective action information that can be used as a resource in future troubleshooting efforts and as a training tool for new engineers.


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Control Plan – for CQA’s

Product:Line:

Voice of the CustomerVoice of the

Process

Lower Spec Limit

TargetUpper Spec Limit

units Data TypeSample

FrequencyInstrument

UsedGage Capability

Process Cpk or PPM

Monitoring System Response Plan

Product Characteristic

[Area name here] Control PlanPrioritization Method Used:(e.g. FMEA, Business Matrix, etc.)

Reference Documents No. and Revision:

Measurement System Control Tools

Remarks

Measurement

Cri

tica

l

Process Steps


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Capability Analysis for CQA

Esp.

Inf.

Esp.

Sup.


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Process Bandwith

Tolerance Bandwith

LTL Nominal

UTL


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LEI LESCpk = 1


LEI LESCpk = 2

LEI LESCpk = 1


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Capability Analysis – Minitab Procedure



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Input - Menu Selection


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Input Window


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Output Window


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Experimentación

Proceso o Proceso o

SistemaSistema

• Variables de Entrada

• Variables Controlables

• Factores

Recursos

• Personal

• Equipo de Medidas

• Otros

X y

• Variables de Salida

• Variables de Respuesta

En DOE las variables X’s son manipuladas sistemáticamente. Típicamente resulta en una matriz de variables no correlacionadas

CPP’s CQA’s


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Experimentación

y = f ( X ) +

Aspiramos a obtener un modelo matemático de la forma:


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1

2

3

4

5

6

7

8

Low HighTime

Low HighTime

Low HighRotational Speed

No

Yes

Hom

ogen

eity No

Yes

Hom

ogen

eity No

Yes

Hom

ogen

eity

Particle

Size

Time

RotationalSpeed

Particle

Size

TimeStep 3Step 1

Step 2 – 2k Factorial ExperimentLow Rotational Speed

High Rotational SpeedLow Particle Size

High Particle Size

High Particle Size

Low Particle Size

k=3

Experimental Space

Experimental Space

Design Space Process Variables Output

Case Number

TimeRotational Speed

Particle Size

Homogeneity

1 High High High Yes2 High High Low Yes3 High Low High Yes4 High Low Low No5 Low High High No6 Low High Low Yes7 Low Low High No

8 Low Low Low No

Particle

Size

RotationalSpeed

RotationalSpeed

Time

Time

RotationalSpeed

Parti

cle

Size

Design Space

Control Space

Step 4

Copyright © IBS Caribe, Inc. 2008


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TO

OLS

Ishikawa

Capability

FMEA

Pareto

DOE


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GLOSSARYControl Strategy: A planned set of controls, derived from current product and process understanding, that assures process performance and product quality. The controls can include parameters and attributes related to drug substance and drug product materials and components, facility and equipment operating conditions, in-process controls, finished product specifications, and the associated methods and frequency of monitoring and control. (ICH Q10) Critical Quality Attribute (CQA): A physical, chemical, biological or microbiological property or characteristic that should be within an appropriate limit, range, or distribution to ensure the desired product quality. Critical Process Parameter: A process parameter whose variability has an impact on a critical quality attribute and therefore should be monitored or controlled to ensure the process produces the desired quality.


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GLOSSARY

Edge of Failure: The boundary to a variable or parameter, beyond which the relevant quality attributes or specification cannot be met. Proven Acceptable Range: A characterized range of a process parameter for which operation within this range, while keeping other parameters constant, will result in producing a material meeting relevant quality criteria. Quality by Design: A systematic approach to development that begins with predefined objectives and emphasizes product and process understanding and process control, based on sound science and quality risk management. Real-time release: The ability to evaluate and ensure the acceptable quality of in-process and/or final product based on process data, which typically include a valid combination of assessed material attributes and process controls.

Risk Assessment in QbD David R. González Barreto 1 QbD Risk Assessment in QbD Introduction and Few...

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