Data integrity PIC S
good practices for data management and integrity in regulatory GMP/GDP environments
good practices for data management and integrity in regulatory GMP/GDP environments
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Staying continuously and actively involved in the operations of the
business,
Setting realistic expectations, considering the limitations that place
pressures on employees,
Allocating appropriate technical and personnel resources to meet
operational requirements and expectations,
Implementing fair and just consequences and rewards that promote good
cultural attitudes towards ensuring data integrity, and
Being aware of regulatory trends to apply “lessons learned” to the
organisation.
6.4 Modernising the Pharmaceutical Quality System
6.4.1 The application of modern quality risk management principles and good data
management practices to the current Pharmaceutical Quality System serves
to modernize the system to meet the challenges that come with the
generation of complex data.
6.4.2 The company’s Pharmaceutical Quality System should be able to prevent,
detect and correct weaknesses in the system or their processes that may
lead to data integrity lapses. The company should know their data life cycle
and integrate the appropriate controls and procedures such that the data
generated will be valid, complete and reliable. Specifically, such control and
procedural changes may be in the following areas:
Quality Risk Management,
Investigation programs,
Data review practices (section 9),
Computerised system validation,
IT infrastructure, services and security (physical and virtual),
Vendor/contractor management,
Training program to include company’s approach to data governance and
data governance SOPs,
Storage, processing, transfer and retrieval of completed records,
including decentralised/cloud-based data storage, processing and
transfer activities,
Appropriate oversight of the purchase of GMP/GDP critical equipment
and IT infrastructure that incorporate requirements designed to meet data
integrity expectations, e.g. User Requirement Specifications, (Refer
section 9.2)
Self-inspection program to include data quality and integrity, and
Performance indicators (quality metrics) and reporting to senior
management.
PI 041-1 13 of 63 1 July 2021