Reason for Data Integrity in pharma industry

We know the available elements of ALCOA. We will discuss latter on the ALCOA topic. But currently we want to emphasis on the issue why we are getting this issues? Data integrity no only the problem of a specific organization, reflects how country are acting on the integrity issue. It will give very bad impact on the overall pharmaceutical industry in India and it will reduce the confidence level in different regulatory bodies. 

Once again we need to work together to remove this issues from our country. If we classify why this type of problems then we will get following points,

• Shop floor people Awareness: It can be resolve by providing training
• Doing mistake by mistake (unknowingly): Repeated training and awareness program  
• Doing mistake knowingly: It’s will be consider as a criminal offense.
• Lack of resources: This also a contributory factor for data integrity. e.g. man power also consider as resource which is a critical factor for integrity. 
• Pressure of productivity on Quality: This is the management polity, manage need to be think on that strategy. Quality should have definite freedom to take flexible decision/action on any deviations.   

Counseling required of all shop floor people those who are directly in touch with process, operation and testing.  Because human drive through emotions not automation. So, probability is very high for doing mistake. So, if we analysis in terms of risk assessment then we will find following,

 Severity: Severity is always high because it will impact your product quality directly.

Probability: As the human are driven through emotions then chance of doing mistake is more.

Detectably: Detection can be increase by introducing automation. Like incorporating eBPR and eBMR which will give better control.  

The element of ALCOA is follows,

• A - Attributable to the person generating the data
• L- Legible and permanent
• C - Contemporaneous
• O - Original record (or ‘true copy’)
• A – Accurate

Attributable:

The identity of the person completing a record should be unambiguous. The use of aliases or abridged names should only be permitted where this is consistently used, and attributable to an individual. The same alias or IT system log-in which cannot differentiate between different individuals should not be used.

Legible (permanent):

It should not be possible to modify or recreate data without an audit trail which preserves the original record. It is important not to forget paper records in this context. Blank forms for manual recording of data should also be controlled in a manner which prevents unauthorized re-creation.

A pile of papers and folders - cropped for blog small. It is important not to forget paper records

Exceptionally, there may be a valid reason to re-create a record, e.g where it has been damaged beyond use, or where an error does not enable a GMP compliant correction of the original. This must be managed through the quality system, either by making a ‘true copy’ (verified as being a true replicate of the original), or by re-writing a new copy and retaining the original as evidence. In all cases, this must be approved through the quality system, with QA oversight and justification for the action.

It is generally accepted that correction fluid is not acceptable in GMP areas. However, companies may be unaware that their computerized systems often have ‘data annotation tools’ enabled. These permit changes to data which can alter the appearance of reports, and may not have a visible audit trail. From a practical perspective, this is ‘electronic correction fluid’, and should not be permitted.

Contemporaneous:

System design has significant impact upon contemporaneous record keeping. The availability of records in the right place at the right time removes the need for staff to use loose scraps of paper, or their memory, to retain information for retrospective completion in the official record.

When inspecting packaging operations, I still find it a common approach for manufacturers to use a single batch packaging record (BPR) for blistering and cartoning of a solid dosage form. However, if the BPR is located in the secondary packing area, it is impossible for staff in the primary packing area to make contemporaneous records, and vice versa. The BPR may also require periodic checks, such as equipment performance. Specifying exact time intervals (e.g ‘every 60 minutes’) may result in an incentive for staff to ‘back date’ the time of the check if they were occupied at the exact time the activity was required. The system is encouraging staff to falsify the record, particularly if there is concern that missing an exact time point might lead to disciplinary measures.

This can be addressed by 2 simple changes. Specifying an acceptable window for completion of the activity (e.g. every 60 ±5 minutes’), and splitting the BPR into 2 parts (primary and secondary) encourages the correct behavior, and removes both opportunity and incentive to falsify the record.

Original:

Original records must preserve data accuracy, completeness, content and meaning. Metadata (data about data) is vital in this aim by enabling reconstruction of an activity – who did what, where and when. There are certain limitations in relation to file formats which may not maintain the full metadata record; so-called ‘flat files’ such as .pdf, .doc etc. We may know who created the file, and when, but there may be no information on how, when or by whom the data presented in that document was created, processed or amended. There is therefore an inherently greater data integrity risk with flat files, as they are easier to manipulate and delete as a single record with limited opportunity for detection.

Accurate:

Automated data capture, with the required IT controls, provides greater control over the accuracy of a record. Where automation is not possible or feasible, real-time second operator verification of quality-critical observed values may be necessary.

Data review must include a review of raw data in its original form. If access to electronic raw data is not possible remotely, this is a good opportunity for the reviewer to escape the confines of their office. Reviewing paper copies or flat file reports of electronic data, even from a validated secure system, is unlikely to enable detection of anomalies. This is because the preparation of reports still requires operator intervention, which can influence what data is reported, and how it is presented.

The final post in this series will look at the recurring problem of ‘trial analysis’, and ways in which organizations within the supply chain can take steps to build confidence and reliance on each other’s data.

I believe personally that we should encourage number of deviation logged in our system. As human are not equivalent to machine, even it is not possible to build error free human being. So, we should appreciate all people in our system those who are can able to identify any error or deviation. All deviation should to be documented and impact on product quality should evaluated. Meanwhile proper corrective and preventive action should to be in place to reduce future occurrence.