What is it? Why is it important?

A Computer System Validation (CSV) is a documented validation-process, verifying that a computer-based system does exactly what it is designed to do (e.g. consistent, reproducible, accurate)

 

In studies, the aim is to demonstrate that the study data is correctly handled from collection/storage (CDMS) to analysis (e.g. statistical software).

 

Problems must be identified and controlled, as it may compromise data:

Completeness: a complete dataset contains:

  • All relevant information for a given purpose
  • No missing, duplicated or irrelevant data

Accuracy: requires trained users of software systems, the implementation of data checks (e.g. source data verification), and query management (e.g. data monitoring)

Reliability: requires that data is reproducible:

  • Upon double entry same datasets are produced
  • Upon repeated statistical analysis same study results are produced
  • Data records are retained as originally stored

Integrity: data is neither distorted nor lost due to;

  • Changes to the software (e.g. software updates)
  • Data being migrated/processed/transferred

What do I need to do?

As SP-INV, prepare the following documents:

    • User Requirement (USR): describe stakeholder and CDMS expectations.
    • Functional Specifications (FS) describe what end-users want the system to do (i.e. system capabilities, appearance and interactions with users)
    • Design Specification (DS) describe how FSs are translated in software modules (i.e. collection of building blocks configured and adapted for different user requirements)

 

Document URS in a traceability matrix, and relate every USR to one or more FS, and link every FS to a given software module.

 

Describe software validation steps:

    • Installation Qualification (IQ) describe how software modules are installed, connected to each other, and tested step by step
    • Operational Qualification (OQ) describe tests related to any implemented FS of the CDMS itself as a unique system
    • Performance Qualification (PQ) describe the implementation of a clinical trial with the described system (e.g. through screenshots of the developed form)

More

Describe in an SOP(s) the data-life-cycle or data-flow from data source (e.g. patient file, lab results), through CDMS, to the statistical software

 

The PQ is the only document that should be prepared ex-novo for every clinical trial, as it represents the data collection specificity of every study. In the event of study modification (e.g. protocol amendment), changes must be validated.

Where can I get help?

Your local CTU can support you with experienced staff regarding this topic

External Links

ECRIN – see in particular

  • Services/Data Centre Certification

GCDMP – see in particular

  • Chapter “Database Validation, Programming and Standards”

FDA – General Principles of Software Validation 

Swiss Law

ICH GCP E6(R2) – see in particular guidelines

  • 5.5 Trial Management, data handling, and record-keeping
Abbreviations
  • CDMS – Clinical Data Management System
  • CTU – Clinical Trials Unit
  • CSV – Computer System Validation
  • ECRIN – European Clinical Research Infrastructure Network
  • FDA – Food and Drug Administration
  • GCDMP – Good Clinical Data Management Practices
  • SOP – Standard Operating Procedures
  • SP-INV – Sponsor Investigator
Concept ↦ Data Management ↦ Clinical Data Mgmt. System ↦ Computer System Validation
Study
Basic

Provides some background knowledge and basic definitions

Basic Monitoring
Basic Drug or Device
Concept

Starts with a study idea

Ends after having assessed and evaluated study feasibility

Concept Statistic Methodology
Concept Drug or Device
Development

Starts with confidence that the study is feasible

Ends after having received ethics and regulatory approval

Development Drug or Device
Set-Up

Starts with ethics and regulatory approval

Ends after successful study initiation

Set-Up Ethics and Laws
Set-Up Statistic Methodology
Set-Up Quality and Risk
Set-Up Drug or Device
Conduct

Starts with participant recruitment

Ends after the last participant has completed the last study visit

Conduct Statistic Methodology
Conduct Drug or Device
Completion

Starts with last study visit completed

Ends after study publication and archiving

Completion Statistic Methodology
Completion Drug or Device
Current Path (click to copy): Concept ↦ Data Management ↦ Clinical Data Mgmt. System ↦ Computer System Validation

Please note: the Easy-GCS tool is currently under construction.