From FY2017 to FY2021, 21 CFR 211.192 - Production record review was the second most commonly cited regulation appearing in FDA Warning Letters (as analyzed by FDA's publically-available dataset.)
"21 CFR 211.192 — Investigations of discrepancies" appeared a total of 523 times in Warning Letters throughout that time.
We gathered and analyzed inspection data from the FDA Data Dashboard to identify the top four trending drug and device cGMP issues cited in inspectional observations from 2016 to 2019.
Then, with the help of Neal Siegel, PhD, a Quality/Regulatory consultant who’s spent over 25 years seeing and solving quality management issues in organizations large and small, we identified some of the firsthand observations into how these issues typically arise in production facilities and labs—with tips for detecting, fixing, and avoiding them. This guide explores 21 CFR 211.192 in particular.
We cover:
- What 21 CFR 211.192 says
- Common compliance problems observed in the field
- Common signals of a larger quality system problem
- A few instructive Warning Letter excerpts
- How to access expert compliance assistance
If you find Neal’s advice helpful, you can watch his free presentation on this subject, and many other trending problem areas in our free recorded webinar you can watch here. You may also want to grab his guide to remote auditing, which you find here.
Need expert assistance acting on any of the advice this guide presents? Contact us to connect with the consultant, contractor, or candidate you need to get the job done right while freeing you to focus on revenue-generating projects.
What is 21 CFR 211.192?
First, let's put the regulation in front of us right from the US Code of Federal Regulations Title 21 Section 211.22 (via fda.gov):
A few common examples of specific observations appearing in Warning Letters include lines like:
A Few Common Problems Observed in the Field
1. Unclear or misused definitions prevent investigations from reaching genuine root causes.
"I sometimes see teams operating without precise, trained-on definitions that enable people to clearly know whether, say, a deviation they’re raising is in fact a nonconformance, a deviation from the procedure, or something else entirely. Incorrectly categorizing a discrepancy can—and often does—steer the investigation in the wrong direction, sending busy people searching for root causes in all the wrong places. All the while, the real root cause goes undetected.”
— Neil Siegel, Industry Consultant, The FDA Group
Here's a quick reference to those definitions:
- Deviation (ICHQ7): Departure from an approved instruction or established standard.
- Discrepancy: Datum or result outside of the expected range; an unfulfilled requirement; may be called nonconformity, defect, deviation, out-of-specification, out-of-limit, out-of-trend.
- Nonconformity (21 CFR 820(q)): The nonfulfillment of a specified requirement.
- Nonconformance: A deficiency in a characteristic, product specification, process parameter, record, or procedure that renders the quality of a product unacceptable, indeterminate, or not according to specified requirements.
- Incident (GAMP®): Operational event which is not part of standard operation.
2. A lack of robust root cause analysis methods.
"This is where I see investigations break down most often. There’s either no model for root cause analysis or the models that are in use are not being used properly. As a result, the stated root cause isn’t sufficiently addressing the actual root of the problem. An investigation that found that a technician ‘used the wrong buffer,’ for example, isn’t finished. Was the buffer mislabeled? If so, why? What’s causing or motivating errors to occur?”
— Neil Siegel, Industry Consultant, The FDA Group
A brief overview of root cause analysis methodologies
There are a number of reliable methodologies for analyzing root causes, however, not all are equally effective in every scenario. Applying the same methodology to every investigation can fail to go far or wide enough into the problem, undermining the effort.
While each methodology deserves to be thoroughly understood by those putting them to use, we’ve summarized the key takeaways for three of the most common models to help you choose the right one for a given scenario.
Fault Tree Analysis (FTA)
This is a deductive procedure used to determine the various combinations of hardware and software failures and human errors that could cause undesired events (referred to as top events) at the system level.
- Advantages: FTA values the judgment of experts from many disciplines and provides a common perspective on a given problem.
- Disadvantages: FTA relies on multiple expert opinions and judgments at various stages, making it prone to inaccuracy. For larger systems, a quantitative analysis might be so complex, it requires computer algorithms to accomplish.
- A few recommended applications:
- Analyzing and forecasting system reliability, maintainability, and safety
- Understanding the logic leading to a “top event” or undesired state
- Demonstrating compliance with system safety and reliability requirements
- Prioritizing multiple contributors which led to a top event or undesired state
Fishbone Diagram
Also called a “cause and effect” or “Ishikawa” diagram (among other terms), a fishbone diagram is a visual tool for looking at cause and effect. A problem or effect is displayed at the “head” or “mouth” of the fish and possible contributing factors are listed on the “bones” under various cause categories. These models work best when the “head” of the fish contains a very detailed problem statement. This helps eliminate scope creep of the team’s discussions. What happened? When? Where? These can help narrow the focus to solve the problem.
- Advantages: Fishbone diagrams are particularly useful for organizing potential causes, helping teams think through causes they might otherwise miss, and providing a living document that shows the status of all potential causes and whether they have been proved, disproved, or acted upon.
- Disadvantages: Fishbone diagrams are by nature a divergent approach to problem-solving, so they make it possible for teams to expend a lot of energy speculating about a potential cause that may have no effect on the problem.
- A few recommended applications:
- Directing a team to focus on identifying all possible categories and considering alternative causes
- Refocusing a team on the causes of a problem rather than the symptoms
- Improving product design
- Preventing quality defects
- Identifying potential factors causing an overall effect
5 Whys
The 5 Whys is arguably the simplest technique for root cause analysis. It can be very effective when answers come from people who have hands-on experience in the process being examined. It is remarkably simple: when a problem occurs, you drill down to its root cause by asking “why?” five (or more) times. Then, when a countermeasure becomes apparent, you follow it through to prevent the issue from recurring.
- Advantages: This is essentially a simpler form of fault tree analysis, making it a straightforward process when investigating specific accidents instead of chronic problems.
- Disadvantages: Results can be non-reproducible and inconsistent. For instance, two teams analyzing the same issue may reach a different solution. It also leaves the door open to stopping short of reaching the true root cause.
- A few recommended applications:
- Resolving simple or moderately difficult problems
- Resolving issues involving human factors
- Resolving issues where statistical analysis is not needed or possible
3. "No or incomplete written record of investigation” often indicates that data aren’t recorded properly.
"This citation comes up when teams don't record their data properly. In many cases, investigations are often treated with less importance than they deserve. Investigations should be given the same attention and diligence as a batch record. When raising a deviation, I’ve witnessed some teams fail to be clear and concise about what they’re writing down. They fail to take good notes—leaving out potentially important points that have massive importance on the investigation.”
— Neil Siegel, Industry Consultant, The FDA Group
3. “Failure to investigate discrepancies, failures” often signals an inadequate—or completely absent—root cause investigation.
"A demonstrated unwillingness to investigate at the level required to determine a root cause is something I know firsthand the FDA sees with alarming frequency. Root causes are labeled ‘TBD’ or ‘No root cause found’—something to that effect.
Usually, this happens when teams regard a discrepancy as ‘rare,’ and therefore feel an investigation isn’t necessary. Simply put, if something breaks, there has to be a reason for it and that reason must be identified. Other times, when asked to explain the lack of a root cause for a discrepancy, teams will say, for example, ‘We didn’t see anything in the lab that jumped out to us. We ended the lab-level investigation by saying that one of our personnel needs to be re-trained. We feel the root cause is a training issue.’ The person is then put back through the SOP and a manager signs off on re-training.
The problem here is—and again, this comes up a lot—while training may be a convenient root cause, it’s not the actual root cause. If the investigation had looked at the material that person was handed, they’d have discovered the sampling cup was contaminated. The real root cause stretched back into manufacturing sampling and had nothing to do with the training of the lab technician.”
— Neil Siegel, Industry Consultant, The FDA Group
Common Signals of a Larger Quality System Problem
In addition to some of the acute red flags that we commonly observe in the field outlined above, there are a few things that can signal that there's a deeper quality system problem at the root:
- Root causes are not determined, or unclear
- Root causes are often identified as ”mistakes” or similarly shallow terms
- Root causes are unrelated to the observations (due to, perhaps, improper categorization)
- Indications that someone isn’t reading what they’re signing
- Improper use of statistics
A Few Instructive FDA Warning Letter Excerpts
“Your investigations were not thorough and did not fully address non-conforming products on the market. You failed to adequately investigate the stability of your [product] after complaints about product odors. You determined that the root cause of the atypical odors was a reaction of [substance] with improperly cured containers. However, the CAPA you implemented were inadequate: you concluded that the product was safe although it may not remain stable over its shelf-life. You failed to recall these products.”
“In your response, you said that the product owner performed a toxicological study of the defective product and found it did not pose risks. Your response was inadequate. You did not evaluate all product lots for stability in this reactive container-closure system to ensure it would meet all specifications over its shelf-life, including but not limited to assay and impurity profile.”
[Requests:]
- Data to show that your [product] is stable over the intended shelf-life, and an action plan to address any nonconforming products still in distribution, including potential recalls or market withdrawals.
- A comprehensive, independent assessment of your system for investigating deviations, atypical events, complaints, OOS results, and failures. Your CAPA plan should include, but not be limited to, improvements in investigations, root cause analysis, written procedures, and quality unit oversight. Also include your process for evaluating CAPA plan effectiveness
- A comprehensive, independent review of your material system to determine whether all containers, closures, and ingredients from each supplier are qualified and assigned appropriate expiration or retest dates. The review should also determine whether incoming material controls are adequate to prevent use of unsuitable containers, closures, and components.
Steering Clear of Compliance Issues Amid a Potential Increase in FDA Oversight and Enforcement
With pressure mounting on the FDA to address its pandemic-induced inspection backlog, oversight and enforcement activities will likely increase in the coming years. Companies should expect the FDA’s previous focus on trending issues, such as supply chain, data integrity, and cGMP compliance to continue—perhaps with even more force.
Zooming out to look at approaching regulatory compliance more broadly, it’s important to acknowledge that even the most frequently cited compliance issues rarely result from a willful refusal to adhere to, for example, cGMP.
Many if not most Form 483 inspectional observations are the result of something simply being overlooked—lost in the endless list of priorities competing for our finite time and attention. It’s a lab manager forgetting to review a maintenance record after a week off. It’s a production technician losing the newly-updated SOP and using an older copy at the workstation. It’s a rushed sign-off that didn’t follow from a rigorous review.
The flawed workflows, poor collaboration, and human errors that give rise to noncompliance issues can often be avoided through a robust, well-maintained QMS—the foundation of a truly quality-driven operation. Developing an outstanding QMS, however, can require a significant and ongoing heavy lift—not to mention routine objective assessments that reveal blindspots and unrealized opportunities for continual improvement.
Very often, Quality teams are simply stretched too thin to give their QMS the proactive attention it deserves. On top of this, the cyclical, non-constant nature of these projects may not be best suited to a traditional full-time employee or group.
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In addition to providing traditional consulting and FTE recruitment services, we also provide staff augmentation services as a convenient, flexible alternative that often better reflects the cyclical or project-based resource demand while infusing new skills and experiences into a team either on-site or remotely.
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Get in touch with us to learn more about our services and craft a resourcing solution fit for you and watch our free webinar to learn more about 21 CFR 211.192 compliance and other common problem areas.
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