Reducing Data Integrity Risk: 7 Must-Know Strategies

Data integrity is essential in a pharmaceutical quality system to make sure that the products are of the required quality. In fact, data integrity in pharma has become the most important aspect in pharmaceuticals due to FDA and other regulatory agencies.

What is Data Integrity?

Data integrity refers to the fact that data must be accurate and reliable over its entire lifecycle. Uncorrupted data is considered to be whole, and then stay unchanged relative to that complete state. Data that is reliable can meet the standards with which compliance is necessary.

The FDA has developed the acronym ALCOA to define integrity standards. Data is expected to be:

A: Attributable – Data has to demonstrate who handled it, what it is about, when was it used and operated.

L: Legible – Data should be simple and easy to understand, it should be stored permanently and the source should be preserved.

C: Contemporaneous – Data must be recorded as it was used or operated, and at the time it was executed.

O: Original – Source information must be accessible and protected in its original form.

A: Accurate – There should be no errors and data should comply with the set protocol.

 

How to Reduce Data Integrity Risk

Here are 7 strategies to reduce data integrity risk.

  • Implement Audit Trails

An audit trail must be an inerasable record of all data in a system. It is essential for learning what happened to the data throughout the different stages of its lifecycle. An audit trail records user identity, date and time of the activities performed on the system. It helps in ensuring the authenticity of the electronic records and their modification or deletion from the system.

  • Ensure Computer Systems are 21 CFR Part 11 Compliant

21 CFR Part 11 is an FDA regulation which applies to electronic records. ALCOA principles helpful implement the recommendations of 21 CFR. It is required to ensure that all the electronic records are reliable, trustworthy and equivalent to paper records.

  • Validate the Computer Systems

Since the computer software is responsible for the working of the computerized systems, all the software used must be validated. Software validation provides documented evidence that a specific process consistently produces a product that meets the predetermined specifications.

  • Implement Quality Control Measures

Quality control measures include specific processes and people that are put in place to verify that employees are working with data in accordance with security and data governance policies.

  • Follow Software Development Lifecycle

The software development lifecycle method helps in ensuring that the quality related tasks are performed to address the lifecycle phases. These include software development, testing, integration, installation and system maintenance. All the computer systems must be properly developed, qualified, tested and assessed on a regular basis.

  • Secure Data with Limited Access

All systems must have a two-way authentication log. Access to data must be provided only to authorized individuals to guarantee data integrity.

  • Have a Strategy for Backup and Recovery

You need to have a strategy for backup and recovery in case of unexpected data loss and application errors. The procedure must ensure that the data can be reconstructed through media recovery and restoration of physical and logical data. Having a backup strategy protects the integrity of all the database files.

  • Train Users

All users must be trained for record maintenance and data integrity. The training should be conducted periodically and documented properly.

If the quality of pharmaceutical products is compromised, it could risk the user’s life. Data integrity is an important practice that ensures that quality of every single product meets the required standards.

If you want to learn how to adopt data integrity in your organization, get in touch with us at RS Calibrations.

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