SOP on Data Integrity


Data integrity verification is performed as the data/record/report being generated electronically and is than further analyzed /calculated as per respective test procedure / calculation sheet to verify and then result linkages are established between respective equipments software, log book and records calculation sheet as per respective test procedure and specification.  

  1. SCOPE : 

Electronically generated data/record /report and manually linked records and calculation sheets for all quality control equipments and tools as under the scope of procedure in quality control departments. 

    1. Head QC :

             To perform detailed investigation on the basis of daily monitoring of data after analysis.   Confidential record shall be maintained by the QC head for further discussion.  

  1. Head QA: Review the daily monitoring record and inform to Superior of respective functional head with reporting.
  2. CQA: CQA is responsible for the implementation of system and procedures to minimize the potential risk to data integrity and for identifying the residual risk, using the principle of ICH Q9.
  1. General procedure: integration /audit trial cautionsDo’sDon’ts

Additional runTo take print out the sequence before run injections and confirm with reviewer for verificationsWithout obtaining confirmation from reviewer, don’t add any injection in pre defined sequence.

Change/modification To be processed batch with same integration parameters and inform to reviewer.Without obtaining confirmation from reviewer, don’t modify.
  3.Timing mismatch in log book with respect to log of system ( HPLC)Restricted these start time in log book at the time of login system, and entered end time in log book after Completion of sequence.Do not allow the entry in logbook of both start and end time after completion of sequence.
  4.Modification in version of Pre-evaluation Sequence.Inform to reviewer about the SST criteria not match with specification.Don’t modify the sequence without inform to reviewer.
 5.Data analysis /integration not perform at the time of analysisTo analysis the chromatograms after completion of sequence immediately integrate the chromatograms.Don’t delay the long period without any cause.
 6.Date of audit trial is before then analysis dateTo analyzed the chromatograms after completion of sequence to prevent mismatch in date.Don’t delay the long period without any cause.
 7.Missing VialsPerform physical verification of the vial in system w.r.t sequence before starting the run injectionsWithout any confirmation of vials in system according the sequence, don’t start the run.
  1. Systems to assure data quality and integritysystems should be designed in a way that encourages compliance with the principles of data integrity for examples include :-
    1. Access to clocks for recording timed events.
    2. Accessibility of batch record at location where activities take place so that ad hoc data recording and later transcription to official records is not necessary.
    3. Control over blank paper templates for data recording.
    4. User access rights which prevent (or audit trail) data amendments.
    5. Automated data capture or printers attached to equipments such as balances.
    6. Proximity of printers to relevant activities.
    7. Access to raw data for staff performing data checking activities.
  1. Activity is performed by an operator, but witnessed and recorded by a reviewer or executive. However the supervisory recording must be contemporaneous with the task being performed, and must identify both the person performing the observed task and the person completing the record. The person performing the observed task should countersign the record wherever possible, although it is accepted that this countersigning step will be retrospective.
  1. All raw data for e.g. analytical report  must be:  

A – Attributable to the person generating the data.

L – Legible, permanent and accessible throughout the data lifecycle.

C – Contemporaneous

           O – Original record (or ‘true copy’)

           A – Accurate.

  1. Original records and documentation, retained in the format in which they were originally generated (i.e. paper or electronic), or as a ‘true copy. Raw data must be contemporaneously and accurately recorded by permanent means. In the case of basic electronic equipment which does not store electronic data, or provides only a printed data output (e.g. balance or pH meter), the printout constitutes the raw data.
  2. Metadata is data that describe the attributes of other data, and provide context and meaning. Typically, these are data that describe the structure, data elements, inter-relationships and other characteristics of data. It also permits data to be attributable to an individual. 
  3. Data integrity arrangements must ensure that the accuracy, completeness, content and meaning of data is retained throughout the data lifecycle. 
  1. Data governance should address data ownership throughout the lifecycle, and consider the design, operation and monitoring of processes / systems in order to comply with the principles of data integrity including control over intentional and unintentional changes to information. 
  1. Archival arrangements should be in place for long term retention (in some cases, periods up to 06 years) for records such as batch documents, marketing authorization application data, traceability data for human-derived starting materials. 
  1. The ‘primary record’ attribute should be defined in the quality system, and should not be changed on a case by case basis.
  1. All data should be considered when performing a risk based investigation into data anomalies (e.g. out of specification results).
  1. Original records and true copies must preserve the integrity (accuracy, completeness, content and meaning) of the record. Exact (true) copies of original records may be retained in place of the original record (e.g. scan of a paper record), provided that a documented system is in place to verify and record the integrity of the copy.
  1. Data retention process must be shown to include verified copies of all raw data, result files, specific to each analytical run, and all data processing runs (including methods and Program) necessary for reconstruction of a given raw data sheet.

Examples of ‘units of work’

  1. Weighing of individual materials 
  2. Entry of process critical manufacturing / analytical parameters

4.13.3 Verification of the identity of each component or material that will be used in a batch Verification of the addition of each individual raw material to a batch.

  1. Audit trail review should be part of the routine data review / approval process, usually performed by the operational area which has generated the data (e.g. laboratory). There should be evidence available to confirm that review of the relevant audit trails have taken place. When designing a system for review of audit trails, this may be limited to those with GMP relevance (e.g. relating to data creation, processing, modification and deletion etc). 
  1. QA should also review a sample of relevant audit trails, raw data and metadata as part of self inspection to ensure on-going compliance with the data governance policy / procedures.
  1. Computerized system user access controls to ensure that people have access only to functionality that is appropriate for their job role, and that actions are attributable to a specific individual. This must be able to demonstrate the access levels granted to individual staff members and ensure that historical information regarding user access level should be available. 
  1. System Administrator rights (permitting activities such as data deletion, database amendment or system configuration changes) should not be assigned to individuals with a direct interest in the data (data generation, data review or approval). Where this is unavoidable in the organizational structure, a similar level of control may be achieved by the use of dual user accounts with different privileges. All changes performed under system administrator access must be visible to, and approved within, the quality system. 
  1. Raw data generated in paper format may be retained for example by scanning, provided that there is a process in place to ensure that the copy is verified to ensure its completeness.
  2. Archive records should be locked such that they cannot be altered or

Deleted without detection and audit trail. The archive arrangements must be designed to permit recovery and readability of the data and metadata throughout the required retention period.

  1. File structure has a significant impact on the inherent data integrity risks. The ability to manipulate or delete flat files requires a higher level of logical and procedural control over data generation, review and storage. 

Trainer:   Head – Quality Control

Trainees:  Quality Control Chemist/Sectional Heads


Controlled Copy No. 1 :  Head of Department – Quality Assurance

Controlled Copy No. 2 :  Head of Department – Quality Control 

Original Copy                       : Head Quality Assurance

       7.0      ANNEXURE:


8.0      REFERENCES:



Sr. No.Revision No.Change Control No.Details of RevisionReason(s) for Revision
0100———New SOP New SOP

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