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Data integrity PIC S

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

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