Top 7 ways to reduce Data Integrity issues in Life Sciences Industry
As we know that Life sciences companies such as pharmaceutical, biotech and API manufacturers need to meet minimum standards which are called GMPs in its product development and execution phase to get their product or process accepted. These standards include hygienic practices, work environment, record keeping, specification, testing procedures of finished products. Data integrity has a very important role in all of these areas for a GMP compliant environment.
Sound and meaningful data is the requirement of life sciences industries for manufacturing high-quality products. This data must be reliable demonstrating integrity, validation, safety, quality, identity, strength, reproducibility and more. Data must be carefully chosen considering the risk to patient, process and product. Based on recent findings from the regulatory agencies, companies struggle to meet data integrity requirements which led to regulatory actions.
Data integrity is one of the important aspects of the FDA’s evaluation and assessment process of a drug application submission. For Careful evaluation of data to check its relevance and authenticity with the drug application, the FDA relies on sponsor’s data. With the above insights, we can say that data integrity plays a crucial role in the process of bringing products to the market by the life sciences industries. Failing to maintain sound data integrity and robust GMPs, companies will have to bear the additional cost to get the approval from FDA.
The capability of Data integrity and GMP compliance can be greatly improved by carefully designed and developed SOPs, validation of equipment and other systems and continuous employee training. Organizations must take care of data standards by assigning the responsibility of Recording data to a specific person, letting data entry flexible with name and date stamps but not at fixed intervals which may not reflect the actual data. Only Original data must be collected which is known as primary source data or the data which has been recorded initially. Such data must be maintained without any error.
All the data collected now becomes the part of GMP records and must be recorded and saved to be evaluated for compliance with FDA 21 CFR requirements of the life sciences industry.
7 ways to maintain Data Integrity
1. Limited User Access
Unique login credentials must be assigned to the person responsible for data recording in accordance with CGMP requirements in parts 21 CFR 211 and 212. user accounts which have only read and view access which does not allow you to modify data or settings are acceptable. But, accounts which have added or edit options must have a unique user login.
2. Reliable data capture
Data must be recorded using technically reliable laboratory controls. Recording the data on temporary notepads or on any other places with the intention of transcribing it to the permanent notebook is not acceptable. Storage of electronic records in a way which allows to edit or manipulate data is also not acceptable.
3. Data verification
All the data must be preserved in its true form throughout the retention period. This includes the data regarding the tests performed and the results obtained from those tests. Such data must be reviewed for its accuracy, completeness and compliance with the required standards. This second verification will ensure the reliability and authenticity of the data.
FDA prohibits the use of testing and sampling methods to achieve a specific outcome or to avoid some acceptable results. Moreover, when any process or product is invalidated, it must be documented scientifically and with clear justification. This justification provided will validate the legitimacy of the invalidation. Complete GMP batch records must be maintained along with investigation report which justifies the invalidated result.
4. Validation process
Validation of process and equipment must replicate the intended use of that process or equipment. The depth of this validation can be decided based on the risk associated with the system which indicates that careful validation is required for critical processes. Controls must be designed appropriately to address hardware, software, personnel and documentation issues. FDA always recommends maintaining limited access as much as possible to change or edit testing settings or data. This is the most reliable way of preventing data corruption.
5. Development of corrective actions
A global corrective action plan has to be developed to address the non-conformance issues which is to be documented and executed. Introducing, third party consultants will be very beneficial in some cases to address these issues as they show commitment to improving the overall quality. Lapses can be quickly removed from the places where they are imp Sometimes, even though the processes are aligned in the best possible way, it is not possible to get the required results. In such cases, we have to make corrections. FDA encourages to conduct in-depth root cause analysis of the problem with an efficient risk assessment process, predicting the potential impact on the accuracy of data used to Support Submissions to FDA.
They can also help to create advanced computer systems and processes to prevent the reoccurrence of these data integrity issues.
6. Data storage
Storage of data plays a crucial role in maintaining the integrity of data and overall GMP program. Besides keeping the original and unaltered data as a backup, any risk of unintentional data deletion and deterioration should also be eliminated.
7. Updating the GMP standards
As the processes evolve and develop, new testing procedures will also be required. All aspects of GMP compliance must be updated to reflect the change in businesses. GMP updates should be informed to each and every employee of the impact area due to the change. There are no fixed GMP requirements for all the companies, they have to develop their own protocols suitable to them. Again, in case of any confusion, third party consultants can help you to update your GMP standards according to the latest requirements.
Finally, Data Integrity has a crucial role to play in quality management for the life sciences industries such as pharmaceutical, biotech and API manufacturers which can make or break companies compliance which leads to regulatory action.
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