Maintaining the integrity of data in pharmaceutical industry.
What is data integrity How to Maintain data integrity in Pharmaceutical Industry
Integrity is a principle of being truthful and honest towards the work and data generated through work by inculcating and practicing strong moral and ethical principles while doing work in an organization or as an individual.
When it comes to data generated, gathered while manufacturing a medicine in a pharmaceutical company, it is expected that all data generated are honoring above principle, generated data is authentic, and reliable, and in event of challenged by any inspection authority it must prove its truthfulness and reliability.
Why its required that integrity of data is maintained.
During FDA inspections in the Pharma Industry in the past it was found by FDA inspectors that data presented to them during inspection was not authentic, due to which US FDA had to issue warning letters to such companies, also some companies were asked to stop the supply to US market from their manufacturing facility. Following is the number of warning letters issued to pharma companies across the world.
This impacts directly on the financial status of the company and affects the people as well, due to which actions are taken on people who were responsible for violation of integrity of data.
How to maintain the data integrity?
In order to maintain the integrity of data the basic statement of Data integrity must be understood and followed apart from those principles which are outlined in the pharmaceutical industry as data integrity.
“Integrity is a principle of being truthful and honest towards the work and data generated through work by inculcating and practicing strong moral and ethical principles while doing work in an organization or as individual”
When data does not have a problem of data integrity.
When a data is generated by flowing below principles it can be said that there is no data integrity violation. These are written as ALCOA, initial letters of the principles there is more principles of data integrity beyond ALCOA , Complete, Consitant, Enduring, and Available, which are explained in brief below.
1) Attributable (A): The name of the person who generated the data, and the data must be complete, from the beginning of the process till the final completion.
For this computerised system must have password protection, and data generated with a computerized system should be generated from the ID of a person who is responsible for the work and data. Doer and person generating record or writing record should be the same.
For this one should not share login ID and password to others.One should do his, her work and do reporting and signe off the documents, on should not sign on documents when he or she has not done the work described in the documents unless he or she is reviewer of the documents they can sign after complete review of the documents.Same things apply for Computer system.
In addition to personnel practices computer system must have audit trials for verification of the changes done on every edit, computer system must have password protection so that only the person who is allowed to work can log in with log in ID and password.
2) Legible (L) : Easily readable, one should understand the meaning of the written things.
To achieve this the documents should be free from any overwritten data, if any error occur during writing word should be striked of with single line without smudging the word the striked off word should be identifiable, afterwords one should write the correct data beside that cut word. Such corrections must be signed writing date of correction. As far as possible all signature done should also mention date on which documents are signed.
3) Contemporaneous: Means the data generated is simultaneous to the process, as and when the process occurs the entries are done in real time, data is not generated after completion of the process.
One must not do entries of work happened in past. Data entered must be concurrent with the process.
4) Original (O): Data generated should be original, original copy should be there as and when the data is generated.
5) Accurate (A): Data should be accurate, there should not be any error in the data.
6) Complete : Data should be complete in all respects, from the beginning to end of the process.
7) Consistent: Since Validation of Process and Product expect that the product manufactured must meet consistently the desired quality and standard, the data too should consistently have been generated with honouring the principles of integrity.
8) Enduring: The data generated must be preservable and must last as per the guidelines issued for the inspections of records, it should not get damaged during storage.
9) Available: Data must be made available as and when it is requested, without any justifiable delay.
In event of violation of any of the above mentioned requirements the violation should be treated as an incidence, a proper investigation should be done for and the root cause of the incidence should be identified. If the root cause is not related to training then the Corrective and preventive action should be taken to eliminate any future possibilities of such incidence.
If the indiance is due to lac of understanding or training training is required to be provided to the individual.
In event of the individual is involved in critical operation he can be provided with on job training assisting him to learn and understand better and perform accordingly.
Explanation of data integrity violations and methods to prevent Data Integrity violations.
Following are the examples of Violations of DATA INTEGRITY
1) A chemist in a laboratory does testing of a drug and records the observations in a raw data book, and at the end of his shift he has to submit the report, he asks his friend to make the report and sign it and submit. Such scenarios are violation of data integrity
2) Someone finds an error in writing over the document and makes a correction by cutting it with a single cut with pen drawing a single line over the wrongly written words and does correct entry and signs with date.
This is also a violation of data integrity, since the actual doer who is entirely responsible for the data he should do corrections, other person doing correction is violation of principle of data integrity (Attributable)
3) Scribbling over a word to hide the incorrectly written word is conceded as manipulation of data therefore it attracts actions by FDA inspectors. Therefore, one must not do overwriting over the incorrect word to correct the same.
4) The printouts and paper or the written data should be readable, properly printed, any document with fading of ink is also considered as a violation of Data Integrity.
5) Sharing one’s password with another and asking another person to complete his work, too is considered a serious violation of data integrity.
Therefore, pharmaceutical manufacturing companies must allot login IDS and password to every individual who is responsible for the entry of data..
6) Principle of data integrity C in the ALCOA called as Contemporaneous documentation of activity is requirement of Good Manufacturing Practices Guidelines issued by US FDA 21 CFR part 211.100(b), it is mandatory to write the documents or update the records of activity contemporaneous with the activity, means along with manufacturing process the data should be recorded. Violation of this is termed as deviation from the guidelines, and should be handled as an unplanned deviation or Incidence.
7) Anyone using a Xerox copy of original documents or documenting the activity in an unauthorized format is considered a data integrity violation.
Issuing copies of authorized formats in duplication or in unauthorized manner too is considered as violation of data integrity. A log book for all formats which are part of SOPs are required to be issued by Quality Assurance should be maintained, the forms issued should be traceable, if any form is damaged or reissued the justification reason for reissue must be written in log book, and with proper reissue documentation approved from QA head.
8) Writing wrong data or writing falls data is a serious violation of GMP guidelines and data integrity, one should not do this even on demand of their superiors. One should stay honest, refuse to do such work, and not write any fake results, by doing this the root cause of the discrepancies will be taken care of and in the long run it will be beneficial.
9) Management of a pharmaceutical company should inculcate a culture of truthfulness and honesty in their staff by regular training.
What to do if any Data Integrity observation is found?
Any of the violations observed of data integrity should be considered as violations and incidence and it should be reported in the format of Deviation (Unplanned) it will be logged as unplanned deviation.
Methodology of handling of unplanned deviation should be adapted and root cause should be identified, on arriving at root cause a corrective action to eliminate the violation is required to log, as preventive actions company is required to provide training to identified individuals