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Validation Testing in Pharmacovigilance: IQ, OQ, PQ and User Acceptance Testing

Learn how validation testing provides objective evidence that pharmacovigilance computerised systems are fit for their intended use through risk-based qualification and testing strategies.

Validation Testing in Pharmacovigilance: IQ, OQ, PQ and User Acceptance Testing

Introduction

Validation testing provides the objective evidence that connects documentation with operational reality. User Requirements Specifications, Functional Specifications and Design Specifications describe what a computerised system should achieve and how it has been implemented. Validation testing demonstrates that these expectations have been fulfilled under controlled conditions.

Within pharmacovigilance, validation testing is not performed simply to satisfy regulatory requirements. It provides confidence that computerised systems responsible for processing safety information, supporting regulatory reporting, managing safety signals and maintaining regulated records perform consistently, reliably and in accordance with their intended use.

Modern validation approaches emphasise scientifically justified, risk-based testing that focuses on patient safety, data integrity and regulatory compliance. Rather than attempting to test every possible software function, organisations should generate objective evidence that critical business processes perform reliably throughout the operational lifecycle of the system.

This article explains the principles of validation testing, the purpose of Installation Qualification (IQ), Operational Qualification (OQ), Performance Qualification (PQ) and User Acceptance Testing (UAT), and how experienced validation professionals develop efficient, risk-based testing programmes for pharmacovigilance systems.

Learning Objectives

After reading this article, you should be able to:

Why Validation Testing Exists

Validation testing is the process of generating objective evidence that a computerised system performs according to its approved requirements and is suitable for its intended use.

Unlike software debugging, which aims to identify and correct defects during development, validation testing seeks to demonstrate that an implemented system consistently supports regulated business processes while protecting patient safety, maintaining data integrity and complying with applicable regulatory requirements.

Validation testing therefore represents one of the most important sources of evidence within the Computerised System Validation lifecycle.

Validation Is Evidence, Not Assumption

Approval of a User Requirements Specification, Functional Specification or Design Specification does not demonstrate that the implemented system behaves as expected.

Similarly, successful software installation does not prove that critical pharmacovigilance processes operate correctly.

Validation testing provides objective evidence that:

Without objective evidence, confidence in the validated state cannot be justified.

Supporting Patient Safety

Every pharmacovigilance computerised system ultimately supports activities intended to protect patients.

Validation testing therefore extends beyond software functionality.

Testing provides confidence that the system supports activities such as:

Failure of these functions may delay identification of important safety information or compromise regulatory decision-making.

Accordingly, testing should focus on the business processes that are most important for patient safety.

Protecting Data Integrity

Reliable pharmacovigilance depends upon trustworthy data.

Validation testing should therefore verify that the computerised system maintains:

Testing should also demonstrate that data remain protected during routine operation, system failures and recovery activities where applicable.

Demonstrating Fitness for Intended Use

Validation testing is fundamentally concerned with demonstrating fitness for intended use.

Testing should therefore answer questions such as:

The objective is not to prove that software is perfect.

Instead, it is to generate sufficient evidence that the implemented system can be relied upon within its regulated operating environment.

Validation Testing Is Risk Based

Modern validation programmes do not attempt to test every possible software function with equal intensity.

Instead, testing effort should reflect:

Critical pharmacovigilance functions should receive greater testing attention than administrative or low-risk functionality.

This approach aligns with both GAMP 5 Second Edition and the FDA Computer Software Assurance (CSA) guidance.

Validation Testing Continues Throughout the Lifecycle

Validation testing does not end after initial system implementation.

Additional testing may be required following:

Ongoing testing supports maintenance of the validated state and provides continued confidence that the system remains fit for its intended use.

Scientific Foundation

Validation testing does not attempt to prove that software is free from defects. It generates objective evidence that the implemented computerised system consistently supports regulated pharmacovigilance activities while protecting patient safety, preserving data integrity and maintaining regulatory compliance throughout its operational lifecycle.

Fundamental Principles of Validation Testing

Effective validation testing is founded upon scientific principles rather than administrative procedures. Regardless of the software platform or regulatory environment, validation testing should generate reliable, reproducible and objective evidence that a computerised system is capable of supporting its intended use.

These principles apply equally to Installation Qualification (IQ), Operational Qualification (OQ), Performance Qualification (PQ), User Acceptance Testing (UAT) and ongoing regression testing throughout the operational lifecycle of the system.

Understanding these principles enables organisations to develop testing programmes that provide meaningful assurance while avoiding unnecessary testing activities.

Objective Evidence

Validation conclusions should always be supported by objective evidence.

Objective evidence consists of documented observations demonstrating that a predefined requirement has been satisfied.

Examples include:

Evidence should be sufficient to allow an independent reviewer to understand what was tested, how testing was performed and whether acceptance criteria were achieved.

Testing Should Be Planned

Validation testing should follow an approved testing strategy.

Before testing begins, organisations should define:

Planning ensures that testing remains systematic, repeatable and aligned with the approved intended use of the system.

Positive and Negative Testing

Validation should demonstrate both that the system performs correctly under expected conditions and that it responds appropriately when errors occur.

Positive testing confirms that expected workflows function successfully.

Examples include:

Negative testing evaluates system behaviour when invalid or unexpected conditions occur.

Examples include:

Together, positive and negative testing provide greater confidence in system reliability.

Challenge Testing

Critical system controls should be challenged rather than assumed to operate correctly.

Challenge testing deliberately attempts to verify that controls function as intended.

Examples include:

Successful challenge testing demonstrates that system controls continue to protect patient safety, data integrity and regulatory compliance.

Repeatability and Reproducibility

Validation testing should generate results that can be reproduced consistently.

Independent reviewers performing the same test under equivalent conditions should obtain comparable outcomes.

Repeatability increases confidence that observed results reflect genuine system behaviour rather than random variation or operator error.

This principle is particularly important when testing critical pharmacovigilance workflows.

Acceptance Criteria

Every validation test should define objective acceptance criteria before execution begins.

Acceptance criteria establish the conditions that determine whether testing has been successful.

Effective acceptance criteria are:

Clearly defined acceptance criteria reduce subjective interpretation and improve consistency between reviewers.

Risk-Based Testing

Not every function requires identical testing effort.

Validation resources should be concentrated on functions that have the greatest potential impact on:

Risk-based testing enables organisations to generate meaningful assurance while avoiding unnecessary testing of low-risk functionality.

This principle is consistent with both GAMP 5 Second Edition and the FDA Computer Software Assurance (CSA) guidance.

Good Documentation Practices

Validation evidence should comply with Good Documentation Practices.

Testing records should be:

Poor documentation may reduce confidence in otherwise well-executed validation activities.

Deviations Should Be Investigated

Unexpected testing outcomes should not simply be ignored or repeated until a successful result is obtained.

Instead, organisations should:

Transparent management of deviations strengthens confidence in the overall validation programme.

Scientific Foundation

Validation testing is a disciplined process of generating objective, reproducible and scientifically justified evidence. The strength of a validation programme depends not on the number of tests performed, but on the quality of the evidence demonstrating that critical pharmacovigilance functions remain fit for their intended use.

Installation Qualification (IQ)

Installation Qualification (IQ) provides documented evidence that the computerised system and its supporting environment have been installed correctly and are suitable for their intended operational use.

Traditionally, Installation Qualification focused on verifying that hardware, operating systems, databases and application software had been installed according to approved specifications before operational testing began.

Although this principle remains valid, modern pharmacovigilance systems increasingly operate within cloud-hosted or Software-as-a-Service (SaaS) environments where responsibility for infrastructure installation rests largely with the software supplier.

Consequently, the scope of Installation Qualification has evolved while its underlying objective remains unchanged.

Purpose of Installation Qualification

The primary purpose of Installation Qualification is to establish confidence that the implemented environment provides an appropriate foundation for subsequent validation activities.

Installation Qualification seeks to demonstrate that:

Successful completion of Installation Qualification provides confidence that Operational Qualification can proceed under controlled conditions.

Typical Installation Qualification Activities

Depending upon the implementation model, Installation Qualification may include verification of:

The scope should always be proportionate to system complexity and regulatory risk.

Installation Qualification for Pharmacovigilance Systems

Examples of Installation Qualification activities within pharmacovigilance include:

These activities establish that the technical environment is ready for functional testing.

Installation Qualification for Commercial Off-the-Shelf Systems

Many pharmacovigilance applications are implemented using Commercial Off-the-Shelf software.

In these situations, substantial Installation Qualification evidence may already exist within supplier documentation.

Organisations may leverage this evidence where appropriate, while documenting local installation activities that remain under their own responsibility.

Examples include:

The objective is not to repeat supplier testing but to demonstrate that the implemented environment supports the organisation's intended use.

Installation Qualification in Cloud and SaaS Environments

Cloud-hosted pharmacovigilance platforms require a different perspective.

Infrastructure installation is frequently performed and maintained by the service provider rather than by the Marketing Authorisation Holder.

Accordingly, Installation Qualification often relies upon a combination of:

The regulated organisation should evaluate whether this evidence provides sufficient assurance that the hosted environment remains suitable for its intended use.

Installation Qualification Is Not Operational Testing

Installation Qualification should not be confused with Operational Qualification.

Installation Qualification confirms that the environment has been established correctly.

It does not demonstrate that business workflows, regulatory reporting, calculations or user processes function correctly.

Those activities belong within subsequent qualification stages.

Maintaining this distinction improves traceability and simplifies lifecycle management.

Common Installation Qualification Deficiencies

Common deficiencies identified during audits and inspections include:

These deficiencies may reduce confidence that subsequent validation activities were performed within an appropriately controlled environment.

Modern Perspective

Experienced validation professionals no longer regard Installation Qualification as a standard checklist applied identically to every computerised system.

Instead, they determine the appropriate scope of Installation Qualification based upon:

This approach aligns with modern lifecycle thinking promoted by GAMP 5 Second Edition and the FDA Computer Software Assurance initiative.

Scientific Foundation

Installation Qualification provides documented evidence that the technical environment supporting a pharmacovigilance system is suitable for validation and operational use. The scope of Installation Qualification should reflect the implementation model, supplier responsibilities and the risks associated with the intended use of the system rather than following a fixed documentation template.

Operational Qualification (OQ)

Operational Qualification (OQ) provides documented evidence that the computerised system operates according to its approved functional and design specifications under controlled conditions.

Where Installation Qualification demonstrates that the technical environment has been established correctly, Operational Qualification demonstrates that the implemented functionality performs as intended.

For most pharmacovigilance systems, Operational Qualification represents the largest and most important phase of validation testing because it evaluates the behaviour of the configured application before routine operational use.

Purpose of Operational Qualification

The primary objective of Operational Qualification is to verify that configured system functionality consistently supports approved business requirements.

Operational Qualification should demonstrate that:

Successful Operational Qualification provides confidence that the configured application behaves as expected before representative users begin routine operation.

Relationship with Previous Validation Documents

Operational Qualification is directly traceable to earlier validation activities.

Testing should demonstrate that approved User Requirements have been translated into implemented functionality through the Functional Specification, Design Specification and Configuration Specification.

Typical traceability follows this sequence:

Business Requirement

↓

User Requirement

↓

Functional Specification

↓

Configuration or Design Specification

↓

Operational Qualification Test

↓

Objective Evidence

This relationship demonstrates that approved business requirements have been implemented and verified systematically.

Typical Operational Qualification Activities

Depending upon the system, Operational Qualification commonly includes testing of:

Testing should reflect the intended use of the implemented system rather than attempting to exercise every possible software function.

Operational Qualification in Pharmacovigilance

Operational Qualification for pharmacovigilance systems frequently includes scenarios such as:

These scenarios should represent the regulated activities performed by the organisation rather than generic software demonstrations.

Positive and Negative Operational Testing

Operational Qualification should include both expected and unexpected operating conditions.

Positive testing confirms that valid business processes operate successfully.

Negative testing evaluates how the system responds when incorrect or unexpected situations occur.

Examples include:

Testing both normal and abnormal conditions increases confidence that the system can protect patient safety and maintain data integrity.

Challenge Testing

Critical controls should be actively challenged during Operational Qualification.

Examples include:

Challenge testing demonstrates that implemented controls continue to function under conditions that could reasonably occur during routine operation.

Operational Qualification and Risk-Based Testing

Modern validation programmes recognise that not every system function requires identical testing effort.

Operational Qualification should therefore focus primarily on functions that influence:

Administrative functions with limited regulatory significance generally require proportionately less validation effort than critical pharmacovigilance processes.

This approach aligns with the principles of GAMP 5 Second Edition and FDA Computer Software Assurance.

Common Operational Qualification Deficiencies

Deficiencies identified during audits and inspections frequently include:

Many of these deficiencies reduce confidence that the validated system will perform reliably under routine operational conditions.

Operational Qualification as Evidence

Operational Qualification should not be viewed simply as a collection of completed test scripts.

Collectively, the testing programme should provide convincing objective evidence that the configured pharmacovigilance system performs consistently, reliably and in accordance with its approved intended use.

The emphasis should remain on demonstrating confidence rather than documenting activity.

Scientific Foundation

Operational Qualification provides objective evidence that the configured pharmacovigilance system performs according to its approved requirements under controlled conditions. By evaluating workflows, business rules, security controls, interfaces and exception handling using a risk-based approach, Operational Qualification establishes confidence that the system is suitable for regulated operational use.

Performance Qualification (PQ)

Performance Qualification (PQ) provides documented evidence that the validated computerised system performs effectively within its intended operational environment using representative business processes, representative users and realistic operational conditions.

Where Operational Qualification demonstrates that configured functionality operates correctly under controlled test conditions, Performance Qualification demonstrates that the complete business process functions successfully during routine organisational use.

Performance Qualification therefore evaluates the interaction between technology, people, procedures and operational workflows.

Purpose of Performance Qualification

The primary objective of Performance Qualification is to demonstrate that the implemented system supports the organisation's regulated pharmacovigilance activities when used as intended.

Performance Qualification seeks to provide confidence that:

This stage bridges technical validation and day-to-day pharmacovigilance operations.

Performance Qualification Is Business Process Validation

Unlike Installation Qualification and Operational Qualification, Performance Qualification evaluates complete business processes rather than isolated system functions.

Testing should therefore reflect how the system is actually used within the organisation.

Examples include:

These workflows frequently involve multiple users, multiple system functions and several organisational procedures.

Representative Users

Performance Qualification should involve users who routinely perform the regulated activities being evaluated.

Depending on the system, participants may include:

Using representative users provides confidence that validated functionality can be applied successfully during routine operations.

Representative Data

Performance Qualification should use realistic test data that reflects normal operational activities.

Examples include:

Representative data improves confidence that operational workflows perform reliably under realistic conditions.

End-to-End Pharmacovigilance Workflows

Performance Qualification should evaluate complete workflows rather than isolated transactions.

Typical end-to-end scenarios include:

Evaluating complete workflows demonstrates that individual validated functions operate successfully as an integrated business process.

Partner MAH and Vendor Scenarios

Many pharmacovigilance activities involve collaboration between Marketing Authorisation Holders, licensing partners, distributors, contract research organisations and pharmacovigilance service providers.

Performance Qualification should therefore include representative scenarios such as:

Testing these scenarios demonstrates that organisational responsibilities and contractual processes function correctly in addition to the computerised system itself.

Procedures and Training

Performance Qualification evaluates more than software functionality.

Successful execution also depends upon:

A technically correct system cannot achieve its intended use if supporting operational controls are ineffective.

Performance Qualification and Risk-Based Validation

Performance Qualification should focus on business processes that are most important for:

Lower-risk administrative activities generally require less extensive operational evaluation than critical pharmacovigilance processes.

This approach is consistent with modern quality risk management principles.

Common Performance Qualification Deficiencies

Common observations identified during audits and inspections include:

These deficiencies may reduce confidence that the validated system will perform reliably within routine pharmacovigilance operations.

Performance Qualification Demonstrates Operational Readiness

Successful Performance Qualification demonstrates that the implemented computerised system, together with trained personnel, approved procedures and supporting organisational controls, is capable of supporting routine pharmacovigilance activities safely, consistently and in accordance with applicable regulatory requirements.

It therefore provides an important bridge between technical validation and operational deployment.

Scientific Foundation

Performance Qualification demonstrates that validated technology, trained users, approved procedures and organisational governance function together as an integrated pharmacovigilance system. Its objective is to provide objective evidence that the complete operational process—not merely individual software functions—is fit for its intended use.

User Acceptance Testing (UAT)

User Acceptance Testing (UAT) is the process through which business users confirm that the implemented computerised system satisfies approved business requirements and is acceptable for routine operational use.

Unlike Installation Qualification, Operational Qualification and Performance Qualification, which primarily generate validation evidence, User Acceptance Testing represents the formal confirmation by business process owners that the implemented solution meets operational expectations.

Successful completion of User Acceptance Testing provides confidence that the system can be adopted into routine pharmacovigilance operations.

Purpose of User Acceptance Testing

The principal objective of User Acceptance Testing is to demonstrate that the implemented solution supports the organisation's intended business processes from the perspective of those who will use the system.

User Acceptance Testing seeks to confirm that:

The emphasis is therefore placed upon business suitability rather than technical implementation.

Business Ownership

User Acceptance Testing should be led by the business rather than the software supplier.

Typical participants include:

Validation specialists may coordinate testing activities, but acceptance should ultimately remain a business decision.

Relationship Between UAT and Previous Qualification Activities

User Acceptance Testing builds upon evidence generated during Installation Qualification, Operational Qualification and Performance Qualification.

By the time UAT begins:

User Acceptance Testing should therefore confirm business acceptance rather than repeat earlier qualification activities.

Typical User Acceptance Testing Scenarios

User Acceptance Testing should reflect routine pharmacovigilance activities performed by the organisation.

Representative scenarios may include:

These scenarios should be representative of routine operational practice.

Acceptance Criteria

Each User Acceptance Test should have predefined acceptance criteria agreed before testing begins.

Acceptance criteria should be:

Where acceptance criteria are not achieved, organisations should investigate the underlying cause and determine whether corrective actions or additional validation activities are necessary before approving the system for production use.

Managing User Acceptance Testing Findings

User Acceptance Testing may identify observations ranging from minor usability issues to significant defects affecting regulated business processes.

Each finding should be:

Business acceptance should be based upon documented evidence rather than informal agreement.

Common User Acceptance Testing Deficiencies

Deficiencies commonly identified during audits and inspections include:

Such deficiencies may reduce confidence that the organisation has adequately evaluated the suitability of the system for routine use.

User Acceptance Testing and Production Release

Completion of User Acceptance Testing represents an important milestone but should not automatically trigger production deployment.

Before release, organisations should confirm that:

Production release should therefore be based upon the combined results of validation, business acceptance and organisational readiness.

Distinguishing User Acceptance Testing from Performance Qualification

Although User Acceptance Testing and Performance Qualification frequently involve similar users and realistic business scenarios, their objectives differ.

Performance Qualification demonstrates that the validated system performs effectively within the operational environment.

User Acceptance Testing confirms that business users consider the implemented solution suitable for routine operational use.

Both activities contribute to confidence in the implemented system, but they answer different questions and provide different forms of evidence.

Scientific Foundation

User Acceptance Testing is the formal confirmation by business users that the validated computerised system satisfies approved business requirements and is suitable for routine pharmacovigilance operations. It complements technical qualification activities by providing documented evidence of business acceptance rather than technical verification.

Risk-Based Testing and Computer Software Assurance (CSA)

Modern Computerised System Validation no longer assumes that every function within a computerised system requires the same level of testing. Contemporary guidance encourages organisations to direct validation activities towards functions that are most important for patient safety, data integrity and regulatory compliance.

This philosophy underpins both ISPE GAMP 5 Second Edition and the FDA Computer Software Assurance (CSA) guidance.

Rather than measuring validation quality by the number of executed test scripts, modern validation programmes focus on generating meaningful evidence that critical business processes operate reliably throughout the system lifecycle.

The Principles of Risk-Based Testing

Risk-based testing allocates validation effort according to the significance of the function being evaluated.

Factors commonly considered include:

Functions presenting greater potential risk should receive proportionately greater validation attention.

Identifying Critical Functions

Not every feature within a pharmacovigilance system contributes equally to regulatory compliance.

Examples of functions that frequently require extensive validation include:

Conversely, administrative functions with minimal impact on regulated activities generally require less extensive testing.

Computer Software Assurance

The FDA's Computer Software Assurance initiative encourages organisations to focus validation on activities that provide meaningful confidence rather than simply increasing documentation.

Within CSA, organisations should consider:

The emphasis is therefore placed on scientific judgement rather than mechanical compliance.

Choosing the Appropriate Testing Approach

Different testing approaches may be appropriate depending on the function being evaluated.

Examples include:

The testing approach should always be justified by the risks associated with the intended use of the function.

Leveraging Supplier Evidence

For Commercial Off-the-Shelf pharmacovigilance applications, organisations should make appropriate use of supplier evidence where justified.

Examples include:

However, supplier evidence should not replace testing of:

The Marketing Authorisation Holder remains responsible for demonstrating that its own implementation is fit for its intended use.

Regression Testing

Validated systems continue to evolve throughout their operational lifecycle.

Regression testing provides assurance that existing validated functionality continues to operate correctly after changes such as:

Regression testing should be proportionate to the potential impact of the implemented change.

Risk-Based Testing in Pharmacovigilance

Examples of risk-based validation decisions include:

Such decisions demonstrate the application of quality risk management to validation activities.

Avoiding Over-Testing

Risk-based validation should not be interpreted as performing less testing regardless of circumstances.

Instead, organisations should avoid testing activities that provide little additional assurance.

Repeating supplier testing without scientific justification or generating excessive documentation for low-risk functionality consumes resources without improving confidence in the validated state.

Validation effort should therefore remain proportionate to the significance of the business process and the risks associated with system failure.

Scientific Foundation

Risk-based validation focuses testing on functions that are most important for patient safety, data integrity and regulatory compliance. Computer Software Assurance strengthens this approach by encouraging organisations to generate meaningful evidence that supports confidence in the validated system rather than producing documentation that adds little regulatory or operational value.

Writing Effective Validation Test Scripts

Validation test scripts translate approved requirements into objective evidence. Each test script should demonstrate that a defined requirement has been implemented correctly and that the resulting behaviour is suitable for its intended use.

A well-designed test script enables different testers to perform the same activity under comparable conditions and obtain consistent results. Test scripts should therefore be clear, repeatable and directly traceable to approved validation documentation.

The objective is not simply to execute software functions but to generate reliable evidence supporting confidence in the validated state.

Traceability to Approved Requirements

Every validation test should be traceable to one or more approved requirements.

Depending upon the validation approach, traceability may link the test script to:

This relationship demonstrates why the test exists and what requirement it verifies.

Testing activities that cannot be traced to an approved requirement should be critically reviewed to determine whether they provide meaningful validation evidence.

Essential Components of a Test Script

Although organisations use different templates, effective validation test scripts generally include:

Using a consistent structure improves repeatability and simplifies inspection review.

Preconditions

Each test should clearly describe the conditions that must exist before execution begins.

Examples include:

Clearly documented preconditions reduce variability and improve reproducibility.

Test Data

Validation should use controlled and representative test data.

Examples include:

Representative data increases confidence that testing reflects routine operational use.

Writing Test Steps

Test steps should describe observable user actions rather than broad objectives.

Each step should be:

For example, instead of writing:

"Verify case processing."

a more effective instruction would describe each activity required to create, review, medically assess and complete the case.

Clear instructions reduce variability between testers and improve consistency of execution.

Expected Results

Every test step should define the expected outcome before testing begins.

Expected results should be:

Examples include confirmation that mandatory fields are enforced, regulatory reports are generated successfully or audit trail entries are created correctly.

Expected results should never be modified after execution has begun.

Recording Actual Results

Actual results should accurately describe what occurred during testing.

Where appropriate, supporting evidence may include:

Actual results should reflect observed system behaviour rather than assumptions or conclusions.

Objective Evidence

Validation conclusions should be supported by objective evidence.

Evidence should be attributable, legible, contemporaneous, original and accurate, consistent with Good Documentation Practices and the principles of ALCOA+.

Evidence should allow an independent reviewer to understand:

Determining Pass or Fail

Each completed test should conclude with a documented assessment.

A test should be considered successful only when:

Any unexpected outcome should be documented and assessed through the deviation management process rather than informally disregarded.

Pharmacovigilance Examples

Validation test scripts for pharmacovigilance systems commonly evaluate activities such as:

These scenarios should reflect the organisation's actual pharmacovigilance processes rather than generic software demonstrations.

Common Test Script Deficiencies

Recurring deficiencies identified during audits and inspections include:

Many of these deficiencies reduce confidence in the validity of the testing rather than in the software itself.

Scientific Foundation

Effective validation test scripts provide objective, repeatable and traceable evidence that approved requirements have been implemented correctly. Their purpose is not merely to document test execution but to generate scientifically defensible evidence supporting confidence that the pharmacovigilance system remains fit for its intended use.

Managing Deviations During Validation

Validation testing does not always proceed exactly as planned. Unexpected results may occur because of software defects, configuration errors, incorrect test scripts, unsuitable test data, environmental problems or deficiencies within the validation process itself.

The existence of a failed test does not necessarily indicate that validation has failed. Rather, it indicates that the observed outcome differs from the predefined expectation and requires systematic evaluation.

An effective deviation management process demonstrates that unexpected results are investigated objectively, their impact is understood and appropriate actions are taken before the computerised system is approved for operational use.

What Is a Validation Deviation?

A validation deviation is any departure from the approved validation protocol, predefined acceptance criteria or expected test result.

Examples include:

Every deviation should be documented, evaluated and resolved using a controlled process.

Sources of Validation Deviations

Not every deviation originates from the computerised system itself.

Common causes include:

Identifying the true source of the deviation is essential before corrective actions are implemented.

Classification of Deviations

Many organisations classify validation deviations according to their potential impact on patient safety, data integrity and regulatory compliance.

Although terminology differs between organisations, deviations are commonly categorised as:

Classification should be based upon documented risk assessment rather than subjective judgement.

Factors commonly considered include:

Root Cause Analysis

Corrective actions should address the underlying cause of the deviation rather than its immediate symptom.

Root cause investigations should seek to determine:

Structured investigation techniques may be used where appropriate to support consistent and objective analysis.

Corrective and Preventive Actions

Once the underlying cause has been identified, appropriate Corrective and Preventive Actions (CAPAs) should be implemented.

Examples include:

CAPAs should be proportionate to the significance of the identified deficiency.

Retesting

Where corrections affect validated functionality, retesting is generally required.

Retesting should demonstrate that:

Depending upon the nature of the change, regression testing may also be necessary to demonstrate that existing validated functionality remains unaffected.

Residual Risk Assessment

Following implementation of corrective actions, organisations should evaluate any remaining residual risk.

Questions commonly considered include:

Residual risk should be documented and formally approved before validation activities are concluded.

Pharmacovigilance Examples

Examples of validation deviations within pharmacovigilance include:

Each deviation should be evaluated according to its potential effect on regulated pharmacovigilance activities rather than solely on technical complexity.

Common Deficiencies in Deviation Management

Inspection findings frequently relate not to the existence of deviations but to weaknesses in how they are managed.

Examples include:

These weaknesses may reduce confidence in the overall validation programme.

Deviations Demonstrate the Effectiveness of the Validation Process

An effective validation programme is not characterised by the absence of deviations.

Instead, it is characterised by the systematic identification, investigation, correction and documentation of unexpected findings.

A transparent deviation management process demonstrates that the organisation understands its computerised system, applies scientific judgement and maintains effective quality oversight throughout the validation lifecycle.

Scientific Foundation

Validation deviations are an expected component of a controlled validation programme. Confidence in the validated state is established not by avoiding deviations, but by ensuring that they are identified, investigated, risk assessed, corrected and documented using a systematic and scientifically justified process before the system is approved for operational use.

Common Mistakes in Validation Testing

Many deficiencies identified during Computerised System Validation do not arise because testing was omitted entirely. Instead, they occur because testing was poorly planned, inadequately documented or failed to provide meaningful evidence that the computerised system was fit for its intended use.

Modern validation programmes should focus on generating scientifically justified evidence rather than simply completing predefined test scripts.

Understanding common validation mistakes helps organisations develop testing programmes that are efficient, risk based and inspection ready.

Testing Without Traceability

One of the most significant weaknesses is executing validation tests that cannot be traced to approved requirements.

Every validation activity should demonstrate why the test exists and which requirement it verifies.

Testing that cannot be linked to approved User Requirements, Functional Specifications, Design Specifications or identified risks provides little objective evidence supporting validation.

Complete traceability should be maintained throughout the validation lifecycle.

Treating Every Function Equally

Some validation programmes apply identical testing effort to every software function regardless of its importance.

This approach frequently results in:

Validation effort should instead be directed towards activities that have the greatest potential impact on patient safety, data integrity and regulatory compliance.

Copying Supplier Test Scripts Without Assessment

Commercial software suppliers frequently provide standard validation documentation and test scripts.

Although these materials provide valuable evidence, organisations should not adopt them without critical review.

Supplier documentation rarely reflects:

Local implementation should therefore be validated using organisation-specific scenarios in addition to supplier evidence.

Inadequate End-to-End Testing

Testing isolated software functions does not necessarily demonstrate that complete pharmacovigilance processes operate successfully.

Examples of incomplete validation include:

Validation should include representative end-to-end business processes whenever these support regulated activities.

Inadequate Partner and Vendor Scenarios

Modern pharmacovigilance frequently involves collaboration between Marketing Authorisation Holders, licensing partners, distributors and outsourced service providers.

Validation programmes sometimes overlook these operational interfaces.

Representative testing should include scenarios such as:

Testing only internal workflows may fail to identify important operational risks.

Insufficient Challenge Testing

Validation should demonstrate not only that the system performs correctly under expected conditions but also that important controls function when challenged.

Examples of insufficient challenge testing include failure to evaluate:

Challenge testing provides confidence that system controls continue to protect patient safety and data integrity.

Weak Objective Evidence

Successful execution of a test is not sufficient unless supported by objective evidence.

Common documentation deficiencies include:

Inspection readiness depends upon the quality of recorded evidence rather than the number of completed test scripts.

Poor Deviation Management

Unexpected test results should never be ignored or repeated until a successful outcome is obtained.

Weak practices include:

A robust deviation management process strengthens confidence in the validation programme.

Treating Validation as a Documentation Exercise

Perhaps the most important mistake is viewing validation primarily as the production of documents.

The objective of validation is not to complete protocols or generate signatures.

Its purpose is to provide objective evidence that the computerised system consistently supports regulated pharmacovigilance activities while protecting patient safety, maintaining data integrity and complying with regulatory requirements.

Documentation supports this objective but should never replace critical scientific judgement.

Professional Insight

Strong validation programmes are distinguished not by the volume of testing performed but by the quality, relevance and traceability of the evidence produced. Every validation activity should answer a single question: does this evidence increase confidence that the pharmacovigilance system is fit for its intended use?

Inspection Perspective

Regulatory inspectors rarely assess validation testing by counting completed protocols or executed test scripts. Instead, they evaluate whether the overall validation programme provides objective, scientifically justified evidence that the computerised system is fit for its intended use and remains capable of supporting regulated pharmacovigilance activities.

Inspection findings relating to validation testing are therefore frequently associated with weaknesses in planning, traceability, governance or lifecycle management rather than isolated testing failures.

The central question for inspectors is whether the organisation can demonstrate continued confidence in the validated state.

What Inspectors Evaluate

During inspections, validation testing is commonly evaluated together with the broader Computerised System Validation programme.

Inspectors typically assess whether:

These questions are considered collectively rather than as isolated documentation checks.

Traceability Throughout the Validation Lifecycle

Inspectors frequently examine whether testing can be traced directly to approved business requirements.

For critical pharmacovigilance functions, organisations should be able to demonstrate clear relationships between:

Incomplete traceability may indicate that important business requirements have not been adequately verified.

Evaluating Risk-Based Testing

Modern inspections increasingly evaluate whether validation effort has been allocated appropriately according to risk.

Inspectors may ask why certain functions received extensive testing while others received less detailed evaluation.

Organisations should therefore be able to justify their testing strategy using documented consideration of:

A scientifically justified testing strategy is generally viewed more favourably than uniform testing applied without consideration of risk.

Reviewing End-to-End Business Processes

Validation of isolated software functions alone is rarely sufficient.

Inspectors commonly seek evidence that complete pharmacovigilance processes have been evaluated.

Examples include:

End-to-end testing demonstrates that validated functions operate effectively within real business processes.

Configuration and Local Implementation

For Commercial Off-the-Shelf pharmacovigilance systems, inspectors generally focus less on supplier-developed software and more on how the organisation has implemented the application.

Typical areas of review include:

Validation evidence should therefore demonstrate that local configuration has been appropriately verified.

Reviewing Validation Deviations

Inspectors recognise that deviations may occur during validation.

Their primary interest is not whether failures occurred but whether they were managed appropriately.

They typically evaluate whether:

A transparent deviation management process generally strengthens confidence in the validation programme.

Maintaining the Validated State

Validation testing is not viewed as a one-time implementation activity.

Inspectors expect organisations to maintain confidence in validated systems throughout their operational lifecycle.

Evidence may include:

These activities demonstrate that the validated state continues to be maintained after production deployment.

Inspection Readiness Is Continuous

Organisations that consistently maintain validation documentation, objective evidence and lifecycle controls are generally well prepared for inspection.

Attempting to reconstruct validation evidence immediately before an inspection rarely provides convincing assurance.

Inspection readiness should therefore be regarded as a continuous quality activity supported by effective governance, document control and ongoing validation management.

Inspection Insight

Inspectors are not attempting to determine whether every validation protocol passed on the first attempt. They are assessing whether the organisation can demonstrate, through objective and traceable evidence, that its pharmacovigilance computerised systems remain fit for their intended use and continue to operate within a controlled, validated state throughout their lifecycle.

How an Experienced CSV Lead Thinks About Validation Testing

Experienced Computerised System Validation professionals do not regard validation testing as a regulatory exercise or a collection of completed test scripts. Instead, they regard validation testing as the process of generating objective evidence that justifies confidence in the computerised system throughout its operational lifecycle.

Their primary objective is not to demonstrate that software functions correctly in isolation. It is to demonstrate that the implemented system consistently supports regulated pharmacovigilance activities while protecting patient safety, preserving data integrity and complying with regulatory obligations.

They Begin With Risk Rather Than Test Scripts

Experienced validation professionals rarely begin by asking:

"What tests should we execute?"

Instead, they ask:

Only after understanding these questions do they determine the most appropriate testing strategy.

Their testing programme is therefore driven by risk rather than by historical protocol templates.

They Think in Terms of Business Processes

Experienced CSV Leads recognise that pharmacovigilance systems exist to support regulated business activities rather than isolated software functions.

Consequently, they think in terms of complete operational workflows such as:

Their objective is to demonstrate that these business processes operate reliably from beginning to end.

They Challenge Critical Controls

Experienced professionals recognise that successful execution of expected workflows alone provides limited assurance.

They deliberately challenge critical controls by asking questions such as:

Testing that deliberately challenges important controls generally provides greater assurance than simply confirming expected behaviour.

They Value Objective Evidence

Experienced validation professionals understand that conclusions must always be supported by objective evidence.

Consequently, they expect validation documentation to demonstrate:

Well-supported evidence allows an independent reviewer to understand and reproduce the validation conclusions.

They Use Supplier Evidence Wisely

For Commercial Off-the-Shelf pharmacovigilance systems, experienced professionals do not repeat every supplier test simply because it exists.

Instead, they critically evaluate:

This approach reduces duplication while maintaining confidence in the implemented solution.

They View Failed Tests as Valuable Information

Experienced CSV Leads do not regard failed validation tests as evidence of unsuccessful validation.

Instead, they regard failures as opportunities to improve understanding of the system.

Their focus is on determining:

A transparent investigation strengthens confidence in the validation programme.

They Think Beyond Initial Implementation

Validation testing does not end when the system enters production.

Experienced professionals continuously consider how validation evidence will support:

Their objective is to maintain confidence in the validated state throughout the entire system lifecycle.

They Think Like Inspectors

Experienced validation professionals routinely review their own testing programme from an inspector's perspective.

Typical questions include:

This perspective encourages continuous inspection readiness rather than retrospective document preparation.

They Measure Success by Confidence

Experienced CSV Leads do not measure validation success by:

Instead, they ask a single question:

"Have we generated sufficient objective evidence to justify confidence that this pharmacovigilance system will continue to support safe, reliable and compliant operations?"

If the answer is yes, the validation programme has achieved its purpose.

Professional Reflection

Experienced Computerised System Validation professionals recognise that validation testing is fundamentally an exercise in scientific reasoning. Every test, every piece of evidence and every validation decision should contribute to one objective: demonstrating, through objective and traceable evidence, that the pharmacovigilance system remains fit for its intended use throughout its operational lifecycle.

Key Takeaways

Validation testing transforms approved requirements into objective evidence that a pharmacovigilance computerised system is fit for its intended use.

Installation Qualification confirms that the technical environment has been established appropriately. Operational Qualification demonstrates that configured functionality performs as intended. Performance Qualification confirms that complete pharmacovigilance business processes operate successfully under representative conditions. User Acceptance Testing provides formal business confirmation that the implemented solution is suitable for routine operational use.

Modern validation programmes apply quality risk management to focus testing on functions that are most important for patient safety, data integrity and regulatory compliance. Throughout the system lifecycle, validation testing, supported by effective change control and periodic review, provides continued confidence that the validated state has been maintained.

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Last reviewed: 2026-07-12