Data integrity

Ensuring data integrity at the pharmaceutical business is an important task. Data integrity is the sum total of arrangements which ensuring that data, irrespective of the process, format or technology in which it is generated, recorded, processed, retained, retrieved and used will ensure a complete, consistent and accurate record throughout the data lifecycle.

The pharmaceutical business needs to take responsibility for the systems used and the data they generate. The organizational culture should ensure data is complete, consistent and accurate in all its forms, i.e. paper and electronic. Arrangements within an organization with respect to people, systems and facilities should be designed, operated and, where appropriate, adapted to support a suitable working environment, i.e. creating the right environment to enable data integrity controls to be effective. The influence of organizational culture, the behavior is driven by objectives based on KPI and senior management behavior on the success of data governance measures should not be underestimated.

Data integrity systems should be integrated into the pharmaceutical quality system. It should be related to data ownership throughout the lifecycle, and take into consideration 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, and deletion of information.

The data integrity system should provide controls over data lifecycle which are commensurate with the principles of quality risk management. These controls might be:

• Organisational
  • SOPs, e.g. completion of records and retention of completed paper records;
  • training of personnel and documented authorization for data generation and approval;
  • data governance system design, covering how data is created, recorded, processed, retained and used;
  • routine data verification;
  • periodic surveillance, e.g. self-inspection processes seek to verify the effectiveness of the data governance policy.
• Technical
  • computerized system control,
  • automation

The first step to meet data integrity compliance can be GMP audit focused on data integrity. During this audit, all business processes will be analyzed to define data integrity risks and gaps will be identified and discussed. After a discussion, we will find a few ways how noncompliance will be corrected.