Data Integrity – General consideration and current understanding of the Pharmaceutical industry

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Introduction 

Data integrity is an important and current top issue for many regulatory authorities these days as many pharmaceutical industries found multiple problems due to poor practices followed during the development and commercialization of products for the patients. In the current scenario, the data integrity has been extended throughout the life cycle of products with the expectation that all the data should be complete, consistent, and accurate. Many regulatory authorities like USFDA, MHRA, WHO, and TGA, etc. have been recommended the use of the ALCOA+ principle for the data integrity practices of pharmaceutical industries.

Data Integrity is a fundamental requirement in the pharmaceutical quality system which ensures that pharmaceutical products manufactured should be of desired quality to patients. Failing to follow data integrity practices in industry and vulnerabilities weaken the quality of records and evidence, and may ultimately the quality of medicinal products goes down. Data integrity applies to all elements of the Quality Management System and in principles the data integrity is applied equally to data generated by electronic and paper-based systems throughout the product life cycle.

Data Governance System

This system includes all the measures of data integrity by a pharmaceutical organization which helps in assuring data integrity for all the data captured electronically or manually. Data governance systems help in maintaining the data, irrespective of the procedure, plan, or technology in which it is being generated, processing, reviewing, analyzing, reporting, transferring, storing, retrieving, monitoring, and retiring and ensures a complete, consistent, and accurate record throughout the data lifecycle.

ALCOA+ Principle                

  1. Attributable

Attributable means who has performed the action or who has acquired the data and entered every piece of data or evidence into the record and must be capable of being traced back. The data recording is mainly collected in the electronic version or paper version. Electronic versions require the use of secure and unique user logins and electronic signatures. Unique user logins permit and control the individual’s rights for the creation, modification, or deletion of data within the record. The electronic system should demonstrate that who has performed the actions, are trained and qualified personnel as per procedures. All the changes should be recorded and justified related to corrections, deletions, changes, etc.

  • Legible

All the information recorded by a human must be legible and readable. The information must be readable for it to be of any use. The records should be permanent and using suitable ink that cannot be erased so that the data is readable and preserve throughout the data lifecycle.

3. Contemporaneous

This means that the recording of data should be carried out in a real-time or same time when the actions are being performed. The document should serve the information of who has performed when it is performed. Backdating, pre-completion of the document are strictly prohibited while in electronic records the data must be saved immediately with the required justification for same.

4. Original

The original data generally referred to as the first capture of information or data which can be in paper (static) or electronic (usually dynamic) form. Information or actions that are originally recorded in a dynamic state should always remain available in the same state. The data could be stored in a centralized database in an approved protocol or related forms, or dedicated laboratory notebooks. It is always important that the data should be preserved with the same content and meaning.

5. Accurate

The documented or recorded data or results should be correct, truthful, complete, valid, consistent, free from any errors, and reflective of the observation. The data or results may be related to equipment like qualification, calibration, maintenance or computer system validation or standard operating procedures, deviation management, records of trained and qualified personals. 

Also of the above principle, the data is expected to be complete, consistent, enduring, and easily available on demand. Good documentation practices should be followed throughout any process, without exception, including all the changes and deviation occurred during the process.

Conclusions

In the pharmaceutical industry, data integrity plays an important role to maintain the quality of a final product because the poor practice can allow the substandard product to reach patients, so it’s necessary for an existing system to ensure data integrity, data traceability, and reliability. On a quality basis, data integrity is a critical component of a Quality System. Quality data provides the basis for the confidence of the company to utilize correct data to operate by regulatory requirements.

References:

1. Good practices for data management and integrity in regulated GMP/GDP environments (Draft guidance) by Pharmaceutical inspection convention pharmaceutical inspection co-operation scheme

2. Data integrity and compliance with CGMP – Guidance for industry (draft guidance) by USFDA

3. https://www.pda.org/docs/default-source/website-document-library

4. https://www.who.int/medicines/news/emp-data-integrity-guide/en/

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