Was betrifft es? Warum ist das wichtig?

A Computerised 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 (e.g. research question, safety)
  • No missing, duplicated or irrelevant data (i.e. adds no value to the analysis)

 

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 first saved by entry operator.

 

Integrity: data is neither distorted nor lost due to;

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

Was muss ich befolgen?

As SP-INV, prepare the following documents:

    • User Requirement (USR): describe stakeholder (study team) 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 the URS in a traceability matrix, ensuring each USR item is mapped to one or more FS , and that every FS is linked to the corresponding software function.

 

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)

Mehr

Describe in the SOP(s) the data-flow or data-life-cycle from the data source (e.g. patient file, laboratory 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.

Wo kann ich Hilfe anfordern?

Your local Research Support Centre can assist you with experienced staff regarding this topic

  • Basel, Departement Klinische Forschung (DKF), dkf.unibas.ch

  • Lugano, Clinical Trials Unit (CTU-EOC), ctueoc.ch

  • Bern, Department of Clinical Research (DCR), dcr.unibe.ch

  • Geneva, Clinical Research Center (CRC), crc.hug.ch

  • Lausanne, Clinical Research Center (CRC), chuv.ch

  • St. Gallen, Clinical Trials Unit (CTU), h-och.ch

  • Zürich, Clinical Trials Center (CTC), usz.ch

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 

References

ICH GCP E6(R3) – see in particular principles and guidelines

  • Principle 6: Quality should be built into the scientific and operational design and conduct of clinical trials.
  • Principle 9. Clinical trials should generate reliable results
  • Glossary: Definition of computerised systems validation
  • 4.3 Computerised Systems
  • 4.3.4 Validation
Abkürzungen
  • CDMS – Clinical Data Management System
  • CTU – Clinical Trials Unit
  • CSV – Computerised System Validation
  • ECRIN – European Clinical Research Infrastructure Network
  • FDA – Food and Drug Administration
  • FS – Functional Specifications
  • GCDMP – Good Clinical Data Management Practices
  • ICH GCP – International Council for Harmonisation - Good Clinical Practice
  • SOP – Standard Operating Procedures
  • SP-INV – Sponsor Investigator
  • USR – User Requirement Spcifications
Concept ↦ Data Management ↦ Clinical Data Mgmt. System ↦ Computerised System Validation
Study
Basic

Provides some background knowledge and basic definitions

Basic Monitoring
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 Drug or Device
Current Path (click to copy): Concept ↦ Data Management ↦ Clinical Data Mgmt. System ↦ Computerised System Validation