session 3 validation, risk and criticality · session 3 validation, risk and criticality presented...

Session 3Validation, Risk and Criticality

Presented by Trevor Schoerie

14 May, 2014

© PharmOut 2014

Validation, Risk and Criticality

• In process validation we want to understand and control the variationnot the risk.

• The “drug” benefit vs risk should have already been determined, (hopefully).

“GAMP 5 – Risk Based ……”

“We talk about QRM every time we meet!”

© PharmOut 2014

“Process Variation”

1. Sample Variation

2. Analytical Variation?

3. Process Variation – normally associate

Is the sample representation of the batch?

Blinded samples in lab = STD DEV

Real process variation

© PharmOut 2014

This session

Using Risk to determine no of batches

Risk vs criticality

© PharmOut 2014

How we get to validation…..

• New Chemical Entity *Stage 1 data

• Generic manufacturer

• Contract manufacturer

• New manufacturing site – Tech. Transfer

• Country where validation is a new requirement

• Expansion of regulations, i.e. export to Australia

No concurrent release of validation batches

No retrospective validation

© PharmOut 2014

Typical validation NCE – Stage 2a/b?

Real life

Start

Registration / QbD

© PharmOut 2014

How many PPQ batches?

QTPP

CQAs/

CPPs

Process Description

Analytical Methods

SOPs & Batch

Records

Design Reports

FSE Qualified

PVMP

Training Completed

Approved PV

Protocols

© PharmOut 2014

Knowledge vs # of PV batches

Prior Knowledge Process Design

Prior Knowledge

PV

Process Design PV

Comprehensive Prior Knowledge may support fewer PV batches

Limited Prior Knowledge may require more PV batches

© PharmOut 2014


This depends on the risk and the following elements:

Based on science, experience and justified (documented).

Based on statistics.

© PharmOut 2014


Step 2:Risk Assessment of Control

Strategy

Step 3:Determine Overall Residual

Risk

Step 4:Translate Overall Residual

Risk into # of PPQ Batches

Stage 1Assessment

Stage 2 ActivitiesPrepare PPQ BatchesCompare results to Acceptance Criteria

Risk Level AcceptableStep 1:Risk Assessment of Product

Knowledge & Process Understanding

Reference ISPE

© PharmOut 2014

Risk Assessment of Stage 1

Product Knowledge• Analytical understanding

of product structure• Mechanistic

understanding of product profile

• Contextual understanding of CQA’s

Process Understanding• Depth of understanding

unit operations• Level of knowledge of

process response to input variability

• Process predictability• Understanding of scale

Control Strategy• Application of

process/product understanding to production controls

• Control of raw material inputs

• Equipment capability vsprocess requirements

Assess each CQA

Can use:• Risk Charts• Relative level of

risk based on RPN

• Other QRM tools

© PharmOut 2014

Step 1: Risk Assessment of Product Knowledge

Identification of CQA and impact of CQA variation on patient:

• Level of understanding of product attributes (i.e. how a particular attribute affects patient safety & efficacy)

Product Characterisation:

• The strength of the link between the CQA and clinical performance

© PharmOut 2014

Product Knowledge Risk Ranking

Product Knowledge

Factor

Relative Risk RankingCharacteristics of ranking assignments

Low Risk Medium Risk High Risk

Identification of CQA and impact of CQA variation on patient

• Physiochemical/ biological, pharmacokinetic knowledge, and QbDapproach used to design the formulation of drug product

• Impact of variation on bioavailability explored & understood

• CQAs identified and justified

• Physiochemical/ biological, pharmacokinetic properties identified

• Some exploration of impact of variation

• Product specifications established from development trial and error

• Impact of variation known only from evaluation of incidents

Product Characterisation

• Analytical method has direct measurable linkage to clinical performance

• Complete product

• Analytical method development based on mechanism of action for the therapeutic agent but linkage to clinical performance

• Product characterisation measures quality against established empirical limits

© PharmOut 2014

Process Understanding Risk Ranking

Process Understanding

Factor



Degree of process understanding/ unit operation

-First principles understanding: based on an understanding of prevailing mechanisms and rationale

-Casual knowledge: that based on what causes interrelationships between variables

-Descriptiveknowledge: derived only from observation, reflecting basic facts

Process predictably and modelling

-Models based on first principles-Extension of empirical and mechanistic models-Highly predictable process and scale-up

-Use of models derived from basic physical, chemical, biological or microbial mechanisms of observed phenomena-Sufficient knowledge to employ PAT methods, if applicable and desired

-Primitive models reflecting only basic understanding of process and scale effects-Process predictability is questionable

Table continued on the next slide

© PharmOut 2014

Process Understanding Risk Ranking

Process Understanding

Factor



Process Response to input variability

-Design space identified using multivariate data and statistical methods-Impact of material attributes on product quality explored extensively in development-Material specific CQAs identified and well understood or no material specific CQAs

-Well-defined criticality for process based on multivariativeexperiments-Impact of material attributes on product quality explored to some degree-Material specific CQAs identified-full range of variability not explored in development

-Partially defined, primarily through univariateexperimentation-Impact of materials attributes to product quality are minimally explored-Materials specific CQAs not identified

Effects of scale -Highly predictable-dataacross different scales can be projected.

-Predictable-data across scales can be projected

-Unpredictable-Scale impact

© PharmOut 2014



Strategy


Risk






Stage 1 ActivitiesAssessments of Product Knowledge and Process Understanding

© PharmOut 2014

Step 2: Risk Assessment of Control Strategy

• How the specifications were developed.Raw Materials Specifications

• How easily the requirements for the process are accommodated by the manufacturing equipment.

Equipment Capability vs. Process

Requirements

• How consistently the process has performed historically and during development studies.

Experience with Process Performance

• How the process is monitored and variability is detected

Monitoring capability & detectability

© PharmOut 2014

Control Strategy - Risk Ranking

Control Strategy Factor

Source of Potential

Variability and/or Uncertainty



Raw Material Specifications

-Different suppliers; different manufacturing processes, -Material attributes test method-Different batches-Basis for material specification-Specification wider than experience

-Specifications of material attributes impacting product quality based on development data

-Limited justification of specifications of material attributes

-Specifications are not justified.-Compendial or supplier limits accepted without further investigation

© PharmOut 2014



Source of Potential

Variability and/or Uncertainty



Equipment Capability vs.

-Capability of equipment to

-Comparison of parameter control

-Comparison of control ranges from

-Comparison of parameter control

Process Requirements

-Control operating parameters within acceptable ranges

-Ranges from equipment qualification with process requirements indicates all parameters are well within equipment control capabilities and supported by qualification data

-Equipment qualification with process requirements indicates marginal capability to meet requirements for a limited number of process parameters

-Ranges from equipment qualification with process requirements indicates a significant number of parameters are similar to equipment control capabilities

© PharmOut 2014



Source of Potential Variability

and/or Uncertainty



Experience with process performance to date

-Variationobserved-Scaling effectsConsistency of past performance

-Underlying cause(s) for variation is understood & addressed (or variation not observed during manufacture)-Impact of scale is well understood-Process has consistently performed as expected

-Variation is managed empirically, but underlying causes are not well understood-Some understanding of scaling issues-Minor departures from expected results that were investigated and satisfactorily explained

-Variation has been observed, but has not been successfully managed-Impact of scale changes has not been explored-Unexplainedfailure has been experienced

Monitoring capability & detectability

-Ability of monitoring tools & methods to detect variation

-Attributes measured in real time at a sensitivity where performance variability is likely to be observed

-Attributes measuredoff-line (after batch completion) at a sensitivity where performance is likely to be observed

-Attribute measurement accuracy is inadequate

© PharmOut 2014

Stage 2


Strategy


Risk



Stage 1 ActivitiesAssessments of Product Knowledge and Process Understanding




© PharmOut 2014

Step 3: Determine overall residual risk

The residual risk level reflects the confidence in performance of the commercial process:

Residual Risk Level

Description

Severe (5)

Multiple factors have high risk ratings

High (4)

Few factors have high risk ratings or all have medium risk rating

Moderate (3)

Medium risk level for multiple factors or high risk level for one factor

Low (2)

Medium risk level for a few factors, the others are low risk

Minimal (1)

Low risk level for all factors

© PharmOut 2014



Strategy


Risk



Stage 1Assess




© PharmOut 2014

Step 4: Translate overall residual risk into the number of PV Batches

1. Based on rationales and experience

2. Target Process Confidence and Target Process Capability

• Statistical-includes measures of variability & confidence level

3. Expected Coverage

• Statistical-includes measure of probability of batch success rate

Note: Other approaches may be appropriate

© PharmOut 2014

How many PV batches?

Approach 1:Rationales and

experience

Approach 2:Target process confidence &

target process capability

Step 4:Translate Overall

Residual Risk into # of

PPQ Batches

2 Approaches to Translate Overall Residual Risk into # of PV Batches

© PharmOut 2014

Approach 1: Rationales and Experience

ResidualRisk Level

Number of Batches

Rationale

Severe (5)

Not Ready for PV

Encourage additional development to reduce risk level

High (4)

10 High # of consecutive successful batches unlikely if controls are not adequate

Moderate (3)

5 Increased residual risk addressed by preparing 2 additional PV batches to provide further demonstration of process consistency

Low (2)

3 Knowledge & Control Strategy regarded as sufficient. 3 PPQ batches has historically been appropriate for demonstrating process consistency for many low-risk processes

Minimal (1)

1-2 Minimal residual risk with less than 3 PPQ batches required, e.g. for verifying specific controls associated with a well-understood change to a process

© PharmOut 2014

Approach 2: Target process confidence & target process capability

• Process Capability (CpK) is used as a measure of the capability of the process to consistently meet the quality requirements

• Assumption: CpK ≥1 as a starting point for assessing the capability of a process undergoing validation

© PharmOut 2014


• Used as a measure for level of confidence needed in the CpK and thereby as a degree of assurance

• High level of confidence in the CpK can be built only with time and experience (during Stage 3)

• Residual Risk Level used to define the confidence needed at completion of Stage 2.

© PharmOut 2014


ResidualRisk Level

TargetConfidence

Comments

Severe (5) N/A Major gaps in knowledge & understanding.Additional effort on product/process/control strategy development may be necessary. High confidence level needed to provide high degree of assurance.

High (4) 97%

Moderate (3)

95% Target confidence levels designed to provide reasonable assurance of process capability. Higher confidence levels would be achieved during Stage 3.Low (2) 90%

Minimal (1) N/A High “confidence” based on existing understanding and capability of control strategy. Does not require additional assurance during PV beyond demonstration that commercial systems and procedures are appropriate.

© PharmOut 2014


Residual Risk Level

Min # of batches

Target Confidence for CpK 1.0

Acceptance Criteria

Readily Pass Calculated

CpK

Marginally Pass Calculated CpK

Fail Calculated CpK

Severe (5) Not Ready for PPQ

N/A

High (4) 11 97%

≥ 1.6≥ 1.0and

< 1.6< 1.0

Moderate (3)

8 95%

Low (2) 5 90%

Minimal (1) 1-3 N/A

• Based on a Target CpK of 1.0 and an actual CpK of 1.6. • May include clinical manufacture, demonstration, or other at-scale lots.

Assumes process will be under statistical control & data will show normal distribution.

© PharmOut 2014


PPQ Outcome Pass / Fail Other Considerations

Impact on Initial CPV Sampling Approach*

Readily Pass calculated CpK

Pass N/A Supports Stage 3 routine sampling

Marginally Pass calculated CpK

Pass All input/output parameters within range

Consider enhanced monitoring for CQA’s not meeting “Readily Pass”

Fail calculated CpK

Investigate -Parameter values-Intra-lot CpK-Probability of detection-Process improvement options

Consider enhanced monitoring; May include some testing beyond PPQ.

*PPQ outcome is one consideration in establishing CPV Plan

© PharmOut 2014

This session

Using Risk to determine no of batches

Risk vs criticality

© PharmOut 2014

FMEA - recap

• Study the Failure Mode and Effect Analysis

• It involves reviewing as many components, assemblies, and subsystems as possible to identify failure modes, and their causes and effects.

© PharmOut 2014

Ishikawa – Cause and Effect Diagram

© PharmOut 2014

Quality Risk Management (QRM)

• This session will take a step back and look at the basics

• We will ponder some topics:

• Is the “Criticality Assessment” a “Variability Assessment” when discussing CQAs/CPPs for Qualification & Validation activities?

• Do we throw out our innate understanding of the hazard because we are “FMEA” driven?

FMEA does not help identify sources of variation

© PharmOut 2014

ICH Q9 Quality Risk Management (& Annex 20 of PIC/S PE 009-8)

• ICH Q9 explains the “What” of QRM [10 pages]

• Annex I of ICH Q9 provides concepts and ideas on the “How to”-formal and informal [4 pages]

• Annex II of ICH Q9 details the potential “Where” of QRM [5 pages]

• A “roadmap” is presented to us within the document, but do we follow it for Qualification & Validation activities?

• For example, do we make use of QRM tools other than FMEA (or FMECA) effectively?

© PharmOut 2014


• Risk is defined as the combination of the probability of occurrenceof harm and the severityof that harm

• Harm: Damage to health, including the damage that can occur from loss of product quality or availability.

• Severity: A measure of the possible consequences of a hazard.

Begin the QRM Process

Risk Identification

Risk Analysis

Risk Evaluation

Risk Reduction

Risk Acceptance

Risk Assessment

Risk Control

Output of the QRM Process

Review Events

Risk Review

QRMTools

Risk C

om

mu

nicatio

n

© PharmOut 2014


Wet Floor (Hazard: The potential source of harm)

Broken Leg(Harm: Damage to health, including the damage that can occur from loss of product quality or availability)

Severity: A measure of the possible consequences of a hazard.

Risk is defined as the combination of the probability of occurrence of harmand the severity of that harm

© PharmOut 2014

Deductive vs Inductive Reasoning

Destroyed my car.How did this happen?

Intoxicated?What will happen if I

drive?

Inductive (forward logic)Deductive

?

FMEAPHA

FTA STA C&E Analysis

© PharmOut 2014

Inductive Reasoning

Outcome

Hypothesis

Observation

Confirmation

Risk Identification

Risk Analysis

Risk Evaluation

Risk Reduction

Risk Acceptance

“Top-down" “Think up” Failures!

More Proactive?

© PharmOut 2014

Deductive Reasoning

Theory

Tentative Hypothesis

Pattern

ObservationRisk

Identification

Risk Analysis

Risk Evaluation

Risk Reduction

Risk Acceptance

“Bottom-up" “Narrow down”

Failure!More Reactive?

© PharmOut 2014

Inductive vs Deductive QRM

QRM Tool Inductive Deductive “Complexity”

FMEA Yes No Medium

FMECA Yes No Medium

FTA No Yes High

HACCP Yes Yes Low

HAZOP Yes No Medium

PHA Yes No Low

Risk Ranking and Filtering

Yes Yes Low

Supporting Statistical Tools

Yes Yes Low

© PharmOut 2014

Appendix I: Risk Management Methods & Tools

• General overview-references some primary tools

“It is important to note that no one tool or set of tools is applicable to every situation in which a QRM procedure

is used”

FMEA FMECA FTA HACCP

HAZOP PHARisk Ranking & Filtering

Supporting Stats Tools

© PharmOut 2014

Appendix I: Risk Management Methods & ToolsQRM Tools Input Process Output

FMEA Relies on product & process understanding. Manageable process steps.

Once potential failure modes are established, risk reduction can be used to eliminate, contain, reduce or control the potential failures.

Summarises modes of failure, factors causing these failures and the likely effects of these failures.

FMECA Relies on product & process understanding. Manageable process steps.

Once potential failure modes are established, risk reduction can be used to eliminate, contain, reduce or control the potential failures.

The output of an FMECA is a relative risk “score” for each failure mode, which is used to rank the modes on a relative risk basis.

FTA System (or sub-system) failures

Evaluates system (or sub-system) failures one at a time but can combine multiple causes of failure by identifying causal chains.

The output of an FTA includes a visual representation of failure modes.

© PharmOut 2014

Failure Mode Effects Analysis (FMEA)

Item or process

Step

Potential Failure Mode

Potential Effect(s) of Failure

Se

ve

rity

Potential Cause(s)

Occu

rren

ce

Current Controls

De

tectio

n

RP

N

Recommended Action

Responsibility & Target Date

Action Taken

Se

ve

rity

Occu

rren

ce

De

tectio

n

RP

N

FMECA: Extended to incorporate an investigation of the degree of severity of the consequences, their respective probabilities of occurrence and their detectability

© PharmOut 2014


HACCP Product and process understanding.

It is a structured approach that applies technical & scientific principles to analyze, evaluate, prevent, and control the risk or adverse consequence(s) of hazard(s)

Risk management information that facilitates monitoring of critical points not only in the manufacturing process but also in other life cycle phases.

HAZOP All processes & safety hazards.

It is a systematic brainstorming technique for identifying hazards using so-called “guide-words”.

As is the case with HACCP, the output of a HAZOP analysis is a list of critical operations for risk management.

PHA Product, process and facility design information

1) Identification, 2) Evaluation 3) Ranking, and 4) Remediation

Typically, hazards identified in the PHA are further assessed with other risk management tools such as those in this section.

© PharmOut 2014

Preliminary Hazard Analysis (PHA)

• Early in the development: little information on design details or operating procedures will often be a precursor to further studies

• For product, process and facility design

• Further assessed with other risk management toolsHazards Arising from Product Design

Hazard Investigation/ Controls

Severity (S)

Frequency (F)

Impact (SxF)

© PharmOut 2014



Risk ranking and filtering can be used to prioritize manufacturing sites for inspection/audit by regulators or industry.

Forms a single relative risk score that can then be used for ranking risks. “Filters,” in the form of weighting factors or cut-offs for risk scores, can be used to scale or fit the risk ranking to management or policy objectives.

Risk ranking methods are particularly helpful in situations in which the portfolio of risks and the underlying consequences to be managed are diverse and difficult to compare using a single tool.

Supporting Statistical Tools

Statistical data They can enable effective data assessment, aid in determining the significance of the data set(s), and facilitate more reliable decision making.

Control Charts, Design of Experiments (DOE), Histograms, Pareto Charts, Process Capability Analysis

© PharmOut 2014

Appendix II: Potential Applications for QRM

In II.1: Integrated Quality Management

• To interpret monitoring data (e.g., to support an assessment of the appropriateness of revalidation or changes in sampling).

• To determine appropriate actions preceding the implementation of a change, e.g., additional testing, (re)qualification, (re)validation or communication with regulators.

© PharmOut 2014


In II.4: Facilities, Systems & Equipment

• To determine the scope and extent of qualification of facilities, buildings, and production equipment and/or laboratory instruments (including proper calibration methods).

• To determine acceptable (specified) cleaning validation limits.

© PharmOut 2014


In II.4: Facilities, Systems & Equipment

To select the design of computer hardware and software (e.g., modular, structured, fault tolerance);

To determine the extent of validation, e.g.,

• identification of critical performance parameters; selection of the requirements and design;

• code review;

• the extent of testing and test methods;

• reliability of electronic records and signatures.

© PharmOut 2014


II.6 Production

• To identify the scope and extent of verification, qualification and validation activities (e.g., analytical methods, processes, equipment and cleaning methods;

• To determine the extent for follow-up activities (e.g., sampling, monitoring and re-validation);

• To distinguish between critical and non-criticalprocess steps to facilitate design of a validationstudy.

© PharmOut 2014

Uses in Qualification & Validation

QRM ToolsTools

Uses in Q&V

FMEA All Q&V Stages-prioritize potential risks and monitor the effectiveness of risk control activities.

FMECA All Stages-Prioritize potential risks and monitor the effectiveness of risk control activities. Understand the impact of detectability

FTA Establish the pathway to the root cause of the failure during Q&V. Is useful both for risk assessment and in developing monitoring programs as an output of Q&V.

HACCP Used to identify and manage risks associated with physical, chemical and biological hazards (including microbiological contamination).

HAZOP This facilitates regular monitoring of critical points in the manufacturing process. Used early in the design stage. Q&V input.

PHA Used early in the development of a project when there is little information on design details or operating procedures; thus, it will often be a precursor to further studies. Useful “first cut” for Q&V.


Risk ranking is useful when management needs to evaluate both quantitatively-assessed and qualitatively-assessed risks within the same organizational framework.

Stats Tools They can enable effective data assessment throughout Q&V activities

© PharmOut 2014

QRM vs Impact Assessment Example

“Top Down”

Critical Quality Attributes

Critical Process Parameters

System

Subsystem

Component

End

End

Product carryover exceeds acceptance criteria

Cleaning Agent Concentration

CIP System

Chemical Addition

Chemical Feed Pump

“Bottom Up”

From ISPE GPG Applied Risk Management for C&Q

© PharmOut 2014

QRM vs Impact Assessment

Characteristics Impact Assessment (Baseline® Guide 5)

Formal Risk Assessment

“Top Down” or “Bottom Up” “Bottom Up” “Top Down”

Ability to identify specific process risks Low High

Ability to identify specific Critical Aspects

Low High

Ability to prioritise Qualification efforts Medium High

Cost in time and resources Medium High

Need for SMEs experienced in the tool to be used

Low High

Acceptability to regulators Medium High

Usefulness as “lifecycle” document in future

Low High

From ISPE GPG Applied Risk Management for C&Q

© PharmOut 2014

“Criticality” in Annex 15

• “It is a requirement of GMP that manufacturers identify what validation work is needed to prove control of the critical aspects of their particular operations.”

• “The protocol should specify critical steps and acceptance criteria.”

• “Evidence should be available to support and verify the operating parameters and limits for the critical variables of the operating equipment.”

• “Risk analysis: Method to assess and characterise the critical parameters in the functionality of an equipment or process.”

© PharmOut 2014

Going from QTPP to CQA

• We assume that during product development the clinicians and toxicologists have established that these parameters are high risk to the patient.

• So we are looking at reducing the variability of these attributes.

© PharmOut 2014

Connecting a CQA to a CPP

• The manufacturer during product development and based on prior product and process knowledge establishes that these process parameters have a high impact on variability.

• “Validation” looks at ways to provide confidence that the variability is controlled.

© PharmOut 2014

Activity 3: QRM

Please complete the Blue Sheets as a group and return them to us

Please assign a Speaker/Scribe at

each table

If there are any questions, please ask!

© PharmOut 2014

Thank you for your time.Questions?

Trevor Schoerie

[email protected]

Lead Consultant

www.pharmout.net

session 3 validation, risk and criticality · session 3 validation, risk and criticality presented...

Documents