Anyone familiar with Annex 11 of Eudralex Annex 4 won’t be surprised by the content, but frankly I expect a lot of folks who have primarily experience on the clinical side will be scratching their heads. The fact that the authors felt the need to have an entire paragraph dedicated to unique user names is telling.
This is a great resource for sponsors who need to figure out just what to evaluate at investigators sites, a requirement this guideline repeats multiple times.
I’ll be very curious how effective sponsors are in ensuring this requirement is met “The investigator should receive an introduction on how to navigate the audit trail of their own data in order to be able to review changes.”
In July 2022, the U.S. FDA issued a Warning Letterto the U.S. American company “Jost Chemical Co.” after having inspected its site in January 2022. The warning letter listedfour significant areas:
“Failure of your quality unit to ensure that quality-related complaints are investigated and resolved, and failure to extend investigations to other batches that may have been associated with a specific failure or deviation.”
“Failure to establish adequate written procedures for cleaning equipment and its release for use in manufacture of API.”
“Failure to ensure that all test procedures are scientifically sound and appropriate to ensure that your API conform to established standards of quality and purity, and failure to ensure laboratory data is complete and attributable.”
“Failure to exercise sufficient controls over computerized systems to prevent unauthorized access or changes to data, and failure to establish and follow written procedures for the operation and maintenance of your computerized systems.”
I offer them the above clip as a good mini-training. I recently watched the show, and my wife thought I was going to have several heart attacks.
In a serious nature, please do not short your efforts in data integrity.
Specialty Process Labs LLC is a specialty API manufacturer of natural desiccated thyroid. Which is, yes, what you might think it is. And as far I can tell, mostly ships direct to compounding pharmacies and patients. This month they got a warning letter.
The warning letter highlights:
Failure to validate the process
Failure to test to specification
Failure to exercise sufficient controls over computerized systems
All three of these observations make me rather glad my loved-ones take levothyroxine and I am deeply aware of all the difficulties in that drug supply.
Focusing more on the computer system, it is an unsurprising list of bad access controls, change controls not controlled, and failure to validate excel spreadsheets.
The last observation really stood out to me:
“Manufacturing master batch records held in electronic form on your company’s shared drive do not have restrictions on user access. Your quality unit personnel stated that there are no restrictions for any personnel with login credentials to access new and obsolete master records. Our investigator observed during the inspection multiple versions of batch records were utilized for API lot production.”
This is truly a failure in document access and record management. And it is one I see a lot of places. The core requirement here is really well stated in the PIC/S Data Integrity Guidance requirement 8.4 “Expectations for the generation, distribution and control of records.” Please read the whole section, but pay close attention to the following:
Documents should be stored in a manner which ensures appropriate version control.
Master documents should contain distinctive marking so to distinguish the master from a copy, e.g. use of coloured papers or inks so as to prevent inadvertent use.
Master documents (in electronic form) should be prevented from unauthorised or inadvertent changes.
Document issuance should be controlled by written procedures that include the following controls:
details of who issued the copies and when they were issued; clear means of differentiating approved copies of documents, e.g. by use of a secure stamp, or paper colour code not available in the working areas or another appropriate system;
ensuring that only the current approved version is available for use;
allocating a unique identifier to each blank document issued and recording the issue of each document in a register; – numbering every distributed copy (e.g.: copy 2 of 2) and sequential numbering of issued pages in bound books;
where the re-issue of additional copies of the blank template is necessary, a controlled process regarding re-issue should be followed with all distributed copies maintained and a justification and approval for the need of an extra copy recorded, e.g.: “the original template record was damaged”;
critical GMP/GDP blank forms (e.g.: worksheets, laboratory notebooks, batch records, control records) should be reconciled following use to ensure the accuracy and completeness of records; and
where copies of documents other than records, (e.g. procedures), are printed for reference only, reconciliation may not be required, providing the documents are time-stamped on generation, and their short-term validity marked on the document
There are incredibly clear guidelines for these activities that the agencies have provided. Just need to use them.
This week, the Pharmaceutical Inspection Co-operation Scheme (PIC/S) finally announced that its new guidance on good practices for data management and integrity for pharmaceutical manufacturers and distributors has come into effect.
This final version is of a draft document originally introduced in 2016 and re-issued as a draft in 2018. It’s been a long road to get final version. Final version here.
Attributable is part of ALCOA that tells us that it should be possible to identify the individual or computerized system that performed the recorded task. The need to document who performed the task / function, is in part to demonstrate that the function was performed by trained and qualified personnel. This applies to changes made to records as well: corrections, deletions, changes, etc.
This means that records should be signed and dated using a unique identifier that is attributable to the author. Where author means the individual who created or recorded the data.
Understanding what role the individual is playing in the task is critical. There are basically six: Executor, Preparer, Checker, Verifier, Reviewer and Approver.