In medical packaging, failures rarely look mysterious. A seal leaks. A pouch tears. A device arrives compromised. The explanation follows quickly—material issue, sealing problem, shipping damage, maybe even user error. A fix is implemented, the issue is closed, and the team moves on.
Then it happens again.
Same failure mode. Same general explanation. Same type of fix. At that point, the issue isn’t bad luck—it’s that the wrong problem is being solved.
What’s missing in many of these investigations isn’t effort or technical capability. It’s perspective. Packaging failures are typically treated as isolated events, when in reality they are the result of interactions across an entire system. Until that shift happens, failures don’t go away—they just reappear.
The Trap: Solving What’s Visible
Most investigations start with what can be seen. A leak points to the seal. A crack points to the material. Damage in transit points to distribution. These conclusions feel logical—and often they’re directionally correct.
But they’re also incomplete.
They describe where the failure shows up, not what caused it. And once a label is applied, the investigation tends to stop. Adjustments are made to match the label, validation passes, and the issue is considered resolved.
Underlying all of this is a quiet assumption: if the package passed testing, it should perform in the real world. When it doesn’t, the failure is treated as an exception rather than a signal that the system wasn’t fully understood.
A Real Example: The Seal That Wouldn’t Stay Fixed
A medical device manufacturer began seeing intermittent seal failures—small leaks detected during post-sterilization testing. The immediate conclusion was a sealing issue. Process parameters were tightened. Equipment was recalibrated. Validation was repeated.
The failures went away…for a while.
Within months, the same issue returned. This time, more aggressively. Again, the seal was adjusted—temperature increased, dwell time extended. Again, it passed and again, it came back.
At this point, the investigation expanded beyond the sealing process.
What changed?
- Pre-sterilization performance was consistently acceptable
- Failures only appeared after EO sterilization
- Failure locations were not random—they clustered near formed geometry transitions
That pattern shifted the focus upstream.
Further analysis showed that the forming process was introducing localized stresses into the material—particularly at transitions in geometry. These stresses were stable enough to pass initial testing, but during sterilization, temperature and humidity redistributed those stresses, concentrating them at the seal interface. The seal wasn’t failing because it was weak. It was failing because it was being loaded.
Once that interaction was understood, the solution changed completely. Instead of continuing to adjust sealing parameters, the team modified forming geometry and process conditions to reduce stress concentration. The failures stopped—and stayed stopped.
Packaging Is a Lifecycle System
In practice, ISO 11135 requires a much broader evaluation.
Beyond sterility testing, manufacturers must also consider:
- Residuals testing to ensure safe levels of sterilant byproducts
- Packaging integrity to confirm sterile barrier performance
- Physical parameter equivalence to document that process conditions are consistent and controlled
- Comprehensive documentation supporting the release decision
Full Validation: The Long-Term Standard
That example is not unusual. It illustrates a broader reality: packaging does not fail in a single step, It evolves across a lifecycle:
Design → Manufacturing → Sterilization → Distribution → Clinical Use
Each stage introduces different stresses—mechanical, thermal, environmental, and human. These stresses don’t act independently. They interact, accumulate, and gradually consume the margin built into the system. By the time a failure appears, it may look like it came from one step. But in most cases, it’s the result of everything that came before it.
The “Usual Suspects”—and What They’re Actually Telling You
When failures occur, the same explanations tend to surface. They’re not wrong—but they’re often incomplete.
- Sterilization rarely causes failures outright. It changes material behavior and redistributes stress, exposing weaknesses that were already present.
- Distribution doesn’t just apply load—it introduces interacting stresses (compression, vibration, abrasion) that reveal reduced system margin.
- Clinical use doesn’t create variability—it introduces real-world conditions (gloves, moisture, speed) that testing often fails to capture.
- Material doesn’t act alone—its performance depends on processing, environment, and loading.
- The seal isn’t always the source—it’s where the system finally gives way.
Each of these is a signal. But if the investigation stops at the label, the mechanism remains hidden—and the failure returns.
What a Better Investigation Actually Looks Like
Most teams understand the idea of “looking deeper.” The challenge is translating that into practice. A mechanism-based investigation is not just more analysis—it’s a different structure of thinking.
- Make the Interaction Visible
Instead of treating conditions like sterilization or distribution as single variables, break them down.
- Separate thermal, moisture, and radiation effects in sterilization
- Use indicators (dye, film, powder) to reveal contact and motion
- Record real-world use—video often captures what inspection misses
The goal is to move from assumptions to observable behavior.
- Isolate the Drivers
Failures are rarely caused by one factor. But they can be understood one factor at a time.
- Vary a single condition (e.g., load, humidity, geometry) while holding others constant
- Compare pre- vs post-processing behavior
- Run the same material under different process conditions
If performance changes, you’ve identified a driver—not just a correlation.
- Follow the Stress, Not the Label
Where the failure occurs is a clue.
- Does it always happen in the same location?
- Does it move when you change process parameters?
- Does it correlate with geometry, contact points, or handling?
Failures follow stress. If the location is consistent, the underlying stress is consistent—and traceable.
- Prove It Through Repeatability
A true root cause can be reproduced.
- Same conditions → same failure mode
- Same location → same mechanism
- Same inputs → same outcome
If the result can’t be repeated, the cause hasn’t been confirmed.
The Cost of Getting This Wrong
When failures are treated as isolated events, the impact extends beyond a single issue.
- Recurring complaints erode customer confidence
- Repeated validations consume time and resources
- Late-stage fixes increase cost and complexity
- Regulatory risk increases when root cause is not fully understood
More importantly, teams get trapped in a cycle—responding to failures instead of preventing them.
The Upside of Getting It Right
When investigations shift to mechanism-based thinking, the outcome changes:
- Failures are resolved at their source—not masked
- Design and process decisions become more robust
- Testing becomes more predictive of real-world performance
- Organizations move faster because they stop revisiting the same problems
It’s not just better troubleshooting—it’s better system design. It starts with asking a different set of questions.
- Not What failed? → What changed?
- Not Where did it break? → Where was robustness lost?
- Not What fixed it? → Why did that work?
These questions force the investigation past symptoms and into system behavior.
Final Thought
Packaging failures are rarely caused by material, shipping, sterilization, or user behavior alone. They are driven by interactions across the lifecycle that were never fully examined and that has real consequences. When those interactions go unrecognized, teams don’t just miss the root cause—they inherit it. It shows up again in the next product, the next validation, the next complaint. More time spent investigating. More resources spent retesting. More risk carried forward into the field. At that point, the cost isn’t just technical—it’s operational. But the inverse is also true. When teams start identifying and understanding these interactions early—during development, not after failure—the entire system changes. Testing becomes more predictive. Designs become more robust. Investigations get shorter, not longer. And failures stop repeating.
That shift doesn’t require more testing or more data. It requires asking better questions—and being willing to follow the answers across the full lifecycle. Because the goal isn’t just to fix failures, it’s to stop designing systems where they can happen in the first place.