Did you look for CFR 21 Part 11 or for ICH E6 Guideline for good clinical practice? That has the following section.
5.5. Trial management, data handling, and record keeping
5.5.1. The sponsor should utilize appropriately qualified individuals to supervise the overall conduct of the trial, to handle the data, to verify the data, to conduct the statistical analyses, and to prepare the trial reports.
5.5.2. The sponsor may consider establishing an independent data-monitoring committee (IDMC) to assess the progress of a clinical trial, including the safety data and the critical efficacy endpoints at intervals, and to recommend to the sponsor whether to continue, modify, or stop a trial. The IDMC should have written operating procedures and maintain written records of all its meetings.
5.5.3. When using electronic trial data handling and/or remote electronic trial data systems, the sponsor should:
a)Ensure and document that the electronic data processing system(s) conforms to the sponsor'sestablished requirements for completeness, accuracy, reliability, and consistent intendedperformance (i.e. validation).
The sponsor should base their approach to validation of such systems on a risk assessment that takes into consideration the intended use of the system and the potential of the system to affect human subject protection and reliability of trial results.
b)Maintains SOPs for using these systems.
The SOPs should cover system setup, installation, and use. The SOPs should describe system validation and functionality testing, data collection and handling, system maintenance, system security measures, change control, data backup, recovery, contingency planning, and decommissioning. The responsibilities of the sponsor, investigator, and other parties with respect to the use of these computerized systems should be clear, and the users should be provided with training in their use.
c) Ensure that the systems are designed to permit data changes in such a way that the data changes are documented and that there is no deletion of entered data (i.e. maintain an audit trail, data trail, edit trail).
d) Maintain a security system that prevents unauthorized access to the data.
e) Maintain a list of the individuals who are authorized to make data changes (see 4.1.5 and 4.9.3).
f) Maintain adequate backup of the data.
g) Safeguard the blinding, if any (e.g. maintain the blinding during data entry and processing).
h) Ensure the integrity of the data including any data that describe the context, content, and structure. This is particularly important when making changes to the computerized systems, such as software upgrades or migration of data.
5.5.4. If data are transformed during processing, it should always be possible to compare the original data and observations with the processed data.
5.5.5. The sponsor should use an unambiguous subject identification code (see 1.58) that allows identification of all the data reported for each subject.
5.5.6. The sponsor, or other owners of the data, should retain all of the sponsor- specific essential documents pertaining to the trial (see 8. Essential Documents for the Conduct of a Clinical Trial).
5.5.7. The sponsor should retain all sponsor-specific essential documents in conformance with the applicable regulatory requirement(s) of the country(ies) where the product is approved, and/or where the sponsor intends to apply for approval(s).
5.5.8. If the sponsor discontinues the clinical development of an investigational product (i.e. for any or all indications, routes of administration, or dosage forms), the sponsor should maintain all sponsor-specific essential documents for at least 2 years after formal discontinuation or in conformance with the applicable regulatory requirement(s).
5.5.9. If the sponsor discontinues the clinical development of an investigational product, the sponsor should notify all the trial investigators/institutions and all the regulatory authorities.
5.5.10. Any transfer of ownership of the data should be reported to the appropriate authority(ies), as required by the applicable regulatory requirement(s).
5.5.11. The sponsor specific essential documents should be retained until at least 2 years after the last approval of a marketing application in an ICH region and until there are no pending or contemplated marketing applications in an ICH region or at least 2 years have elapsed since the formal discontinuation of clinical development of the investigational product. These documents should be retained for a longer period however if required by the applicable regulatory requirement(s) or if needed by the sponsor.
5.5.12. The sponsor should inform the investigator(s)/institution(s) in writing of the need for record retention and should notify the investigator(s)/institution(s) in writing when the trial related records are no longer needed.
------------------------------
Reinhard Vonthein
------------------------------
Original Message:
Sent: 07-05-2022 23:07
From: Michiko Wolcott
Subject: "Regulatory/Research-Grade" Database in Clinical Fields
Chris, thanks for your comments. However, your response aligns with what I find on the internet: they address data *quality* rather than data *management* (e.g., retention/purge, change data capture, ETL process, metadata, other infrastructure, governance and accountability, etc.). This is where I'm getting a bit stuck. I'm looking for data management requirements, if there are any.
One possibility is that people are saying "regulatory-grade database" when they really mean "regulatory-grade data(set)." If it is the database that is regulatory-grade, then in the context it would mean (to me and the rest of the tech-y world) the infrastructure itself rather than the contents of the infrastructure. So, then, the question becomes: is it "regulatory-grade data" or "regulatory-grade database"?
------------------------------
Michiko Wolcott
Principal Consultant
Original Message:
Sent: 07-05-2022 22:27
From: Chris Barker
Subject: "Regulatory/Research-Grade" Database in Clinical Fields
Dear Michiko,
great question. And, in large part because of the "21st century cures act", Pharma can use what I presume the client means as regulatory grade by "GMPx" quality data or say, insurance claims or registry or other non-GMPx data.
GMPx abbreviates Good Manufacturing Practice for the "x" which is one of laboratory, clinical, manufacturing etc. that satisfies. regulatory agency criteria , FDA, EMA etc.
Quoting Laurie Burke,from FDA when I met her after her lecture the data meets the "evidentiary standard" approximately translating to "will hold up under cross examination by an unfriendly attorney in court". Hospital chart data,and registry data, and its cousin "insurance claims" is far from that evidentiary standard. Insurance claims data are sufficient for reimbursement by an insurance company or say, Medicare. I've worked with insurance claims in my health economics work (in the past). "out of the gate" those databases can be in the millions or hundreds of millions of covered lives. That data is not routinely checked for consistency. and it can take 10's of minutes or longer simply to process that data. . ONe of my favorite examples is a hospital length of stay of approximately avogadro's number 6.02 * 10^23 - which upon examination turned out to be an error in the bit representatation of a number. Claims data is rarely or never GMPx grade. FDA because of the Cures act ( under Obama) requires sponsor to demonstrate that the claims data meets the evidentiary standard. . The evidentiary standard is defined in the 1938 Food drug and cosmetic act (FD&C).
Pharma and FDA refer to claims data as "real world" and nearly every pharma company has a plan to use real world, such as claims or registry data. a company called flatiron has often led the way in real world data. Further complicating the matter, there is RWE (real world evidence) and RWD (real world data), which some statisticians distinguish.
When any project I work on involves databases that may use say, 100 million records, I keep in mind that even SAS can take 20 or so minutes simply to open the datasets. Some health economics projects I work on like to use all available insurance data. Sometimes only say 10,000 records (rows) of data are used, If you need 100 million, then ask for a dedicated UNIX leverl machine , exclusively used for the project and run the projects overnight. or Take a 1 or 10% random sample, develop and test code on the sample then run production on the 100Million records,
And you are absolutely guaranteed to find errors in claims data, and you may not have an option to "return to the source", determine the correct data, and revise your dataset.
to your question - google for RWE and RWD, and as the old consultant saying goes, double your hourly rate and add 1. :)
last but not least, have fun :)
------------------------------
Chris Barker, Ph.D.
2022 Statistical Consulting Section
Chair-elect
Consultant and
Adjunct Associate Professor of Biostatistics
www.barkerstats.com
---
"In composition you have all the time you want to decide what to say in 15 seconds, in improvisation you have 15 seconds."
-Steve Lacy
Original Message:
Sent: 07-05-2022 21:45
From: Michiko Wolcott
Subject: "Regulatory/Research-Grade" Database in Clinical Fields
Hi everyone,
Need a little direction. I have a data engagement that involves healthcare/pharma, in which there have been mentions of a "research-grade" or "regulatory-grade" database for (pragmatic) clinical trials.
I'm pretty well-versed in the field/discipline of data management and familiar with the cross-industry data management language, but I am finding that healthcare has its own language when it comes to data management, which is adding another layer of confusion. My trusty Google skills are failing me this time, yielding only results that just mention data quality in a more general sense rather than the requirements for a data store, which is what I'm after. I could just apply the same best practices used elsewhere, but I get the feeling that there is a specific standard out there.
If someone can point me to a resource that spells out what makes a database "regulatory-grade" or "research-grade," I would very much appreciate it. Links to regs, audit standards, or some other official language would be great. Thanks in advance.
Michiko
------------------------------
Michiko Wolcott
Principal Consultant
------------------------------