Why OOS/OOT investigations fail
After years of reviewing and coaching teams through OOS/OOT cases, I have come to believe that many investigations fail not because of a lack of technical competence, but because of systemic misconceptions about the nature and purpose of root cause analysis, and a persistent belief that OOS/OOT issues are primarily laboratory events.
In pharma, we have lots of clear guidance from the MHRA, FDA and European Compliance Academy (ECA), with the expectation of scientifically sound, thorough and unbiased investigations. However, we still see the root cause of 'analyst error' time and time again.
Why is this? As usual, there is more than one reason, and I have tried to describe some of the most common culprits below:
😕Cultural Misunderstanding: “OOS Investigations Are Different”
Many organisations—implicitly or explicitly—treat OOS investigations as something separate from the wider root cause analysis (RCA) framework used for deviations, complaints, CAPAs and process failures.
This belief is incorrect, and directly at odds with the expectations described in the regulatory guidelines where the requirements for fact-based analysis are clearly described.
When organisations treat OOS/OOT as if they are “not really RCAs,” the result is predictable:
Narrow laboratory focus
Weak problem statements
Assumptions instead of data
CAPAs that address symptoms rather than causes
Regulators routinely highlight this as a deficiency. The underlying cause is not poor documentation—it is a cultural separation of OOS from genuine problem-solving.
🔬Laboratory focused model
A major misconception is the belief that every OOS/OOT originates in the lab. It is true that:
Analytical error must always be excluded first
Laboratory investigations are the initial stage of regulatory guidance
But too many organisations interpret this as “the lab is the default root cause unless proven otherwise.”
This leads to:
Overuse of “analyst error” with insufficient evidence
Re-testing that resembles confirmation rather than investigation (testing into compliance)
Delayed or absent escalation to manufacturing
Little appreciation of process variation, equipment issues, raw material variability, or environmental factors
The FDA is particularly clear: laboratory error must be conclusively demonstrated—not assumed. Yet many investigations reverse the burden of proof, leading teams to stop at the first plausible lab issue rather than look holistically at:
Upstream processing
Sampling method
Equipment calibration
Material attributes
Batch history and trends
Human factors
The root cause therefore remains hidden, only to re-emerge in future batches.
📊Misuse of Hypothesis Testing: Bias > Science
The most damaging misconception is the idea that hypothesis testing means proving the investigator’s preferred explanation. In reality, hypothesis testing requires:
Generating multiple plausible causes
Designing tests that have the power to disprove hypotheses
Remaining neutral until data is collected
Recognising confirmation bias
Yet, in many OOS/OOT investigations:
The hypothesis is selected before data review
Testing is designed to support the preferred explanation
Hypotheses rarely include non-laboratory causes
Challenges to the initial theory are dismissed as “unlikely”
Negative results are interpreted as inconclusive
This is not hypothesis-driven investigation—it is bias confirmation.
The ECA describes OOS investigations as requiring “critical thinking, open questioning, and disconfirmation of assumptions.”
However, most organisations fail to train analysts and supervisors in cognitive bias, scientific reasoning, or experimental design.
As a result, investigations become procedural exercises, not scientific ones.
⚙️Missing the “Process Story”: Data Without Context
Many OOS/OOT reports lack what the MHRA calls the “process narrative”—the ability to describe:
How the batch was manufactured
What actually happened
What variables were present
Whether trends existed
Whether similar events occurred previously
Without this understanding, analytical results (even correct ones) float without context. This leads to “probable root causes” that cannot be validated and CAPAs that cannot prevent recurrence.
Great investigators ask:
“What is the process telling us?”
“What else changed?”
“Where does this fit in the long-term trend?”
“What does the data not show?”
They think like scientists, not document completers.
🪟What needs to change?
Quality Needs Better Thinking, Not More Forms
Pharmaceutical OOS and OOT investigations often fail not because guidance is unclear, but because organisations misunderstand the scientific nature of investigations. When teams treat OOS as “just another laboratory issue,” or when they use hypothesis testing to confirm biases rather than challenge them, the real root cause is never found. The laboratory personnel and the Qualified Person should understand the requirements and implementation of the guidance and should work together to ensure that the appropriate steps are taken to return the 'true value' of any testing.
This will ensure that a good product is provided to patients who need it, and a bad product is prevented from reaching patients and potentially causing harm.
Regulators expect—and patients deserve—true scientific inquiry, grounded in structured RCA, free from assumptions, and driven by evidence.
To achieve this, we must evolve mindsets, not just SOPs.
Alex Hall.