Concept↦Data Management↦Clinical Data Mgmt. System↦Computer System Validation
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:
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- 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:
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- 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 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
Swiss Law
ICH GCP E6(R2) – see in particular guidelines
- 5.5 Trial Management, data handling, and record-keeping