"The definition of insanity is doing the same thing over and over and expecting different results."
Whether Albert Einstein actually said those words is debatable. What isn't debatable is how accurately they describe the way many organizations approach quality management in clinical research.
- A deviation occurs.
- A corrective action is opened.
- Staff members are retrained.
- The CAPA is closed.
🤔 Six months later, the same issue returns.
♻️ The cycle repeats.
For years, the clinical research industry has treated recurring quality issues as inevitable. Protocol deviations, informed consent deficiencies, documentation errors, investigational product accountability discrepancies, delayed safety reporting, and incomplete source records are often viewed as unfortunate (but expected) realities of conducting clinical trials. FDA Bioresearch Monitoring (BIMO) inspection trends tell a similar story. While individual observations vary from year to year, the underlying themes remain remarkably consistent: failures to follow the investigational plan, inadequate records, informed consent deficiencies, investigational product accountability issues, and insufficient sponsor oversight continue to appear across inspections. These are rarely isolated mistakes; they are indicators of systemic weaknesses that organizations have not fully addressed.
Perhaps that is why Brené Brown's research resonated so strongly with me.
In Dare to Lead, Brown describes interviewing hundreds of leaders from business, academia, and the military. Among the questions she asked was:
"What, if anything, about the way people are leading today needs to change in order for leaders to be successful in a complex, rapidly changing environment where they're faced with seemingly intractable challenges and insatiable demand for innovation?"
Among the ten most common responses, two stood out to me:
- Leaders become stuck and defined by setbacks, disappointments, and failures.
- Leaders rush into ineffective or unsustainable solutions rather than staying with problem identification and solving.
Although Brown wasn't discussing clinical research, she could have been describing many quality systems I have encountered throughout my consulting career.
When Problems Become "Normal"
One of the most dangerous phrases in quality management is: "It's always been this way."
Clinical sites accept recurring protocol deviations because "that's just what happens with this sponsor." Sponsors expect delayed data entry because "sites are always behind." Phase 1 units assume scheduling conflicts and source documentation corrections are simply part of conducting first-in-human studies. CROs accept monitoring findings that continue from study to study because "every trial has these issues."
Over time, recurring problems stop looking like risks. They become accepted operating conditions. This quiet acceptance creates something far more dangerous than the original issue: organizational resignation. When organizations stop believing problems can truly be eliminated, they stop looking for solutions capable of eliminating them. Instead, they learn to manage the symptoms.
The CAPA Trap
Unfortunately, this mindset often reveals itself during root cause investigations. Consider a common example.
A study participant undergoes a protocol-required procedure before signing the informed consent form. The deviation investigation concludes…
· Root Cause: Coordinator forgot to obtain consent.
· Corrective Action: Retrain study coordinator.
· CAPA Status: Closed.
Months later, another coordinator makes the same mistake, the cycle repeats, and nothing changesbecause the study team investigated the person, not the system.
Effective root cause analysis asks progressively more difficult questions.
- Why was the process dependent on memory?
- Were responsibilities clearly assigned?
- Was workload appropriate?
- Did the visit workflow include verification checkpoints?
- Were protocol procedures unnecessarily complex?
- Was competency ever verified beyond initial training?
- Have similar events occurred before or elsewhere?
This type of investigation often arrives somewhere uncomfortable. The problem isn't the coordinator. The problem is the process. Or the oversight. Or staffing. Or communication. Or leadership. Those are much harder conversations which many leaders prefer to avoid. But they are also the conversations where meaningful improvement begins.
Phase 1 Units: Speed Without Sacrificing Curiosity
Phase 1 units face unique operational pressures: enrollment windows are narrow, dose administrations follow minute-by-minute schedules, and safety assessments occur around the clock, to name a few. In these environments, operational efficiency is essential.
Ironically, these same pressures make organizations even more vulnerable to rushing toward immediate solutions. When every hour (and sometimes minute) matters, stopping to thoroughly investigate an issue can feel like a luxury one cannot afford. Yet Phase 1 studies generate some of the most critical safety and pharmacokinetic data in drug development. A poorly designed process can affect dosing accuracy, sample timing, source documentation, investigational product accountability, and ultimately the reliability of the data submitted to regulators.
Speed should never replace understanding. The fastest organizations are often those that spend the most time understanding problems before attempting to solve them. To "quote” Albert Einstein again…
“If I had an hour to solve a problem, I'd spend 55 minutes thinking about the problem and 5 minutes thinking about solutions.”
ICH E6 (R3) Demands a Different Mindset
One of the most significant shifts introduced by ICH E6 (R3) is its emphasis on proactive quality management. The revised guideline encourages sponsors and investigators to identify risks before they become findings, focus resources where they matter most, continuously evaluate quality throughout the study lifecycle, and implement risk-proportionate controls.
This is more than a regulatory update; it is a call for a change in leadership’s perspective. Risk assessments require organizations to challenge assumptions. Root cause analysis requires curiosity instead of blame. CAPA requires long-term thinking instead of quick closure. Continuous improvement requires the humility to acknowledge that today's processes may not be sufficient for tomorrow's challenges. None of those behaviors can be mandated through an SOP. They emerge from the organization’s culture that is primarily shaped by leadership behavior and decisions.
Curiosity Is a Competitive Advantage
Organizations frequently ask how they can reduce protocol deviations, improve inspection readiness, or strengthen data integrity. Those are important questions. But perhaps the better question is this: Are we solving today's problem, or are we preventing tomorrow's?
Organizations that merely close deviations become efficient at documentation; while those that pursue understanding become proficient at prevention. The difference is enormous. With this new mindset, companies see fewer recurring deviations, obtain more reliable data, reduce the need to repeat activities, avoid statistical surprises, achieve greater inspection readiness, lower operational costs, and accelerate their regulatory submission timelines. These outcomes aren't achieved because they completed more CAPAs, but rather because they solved the right problems.
Final Thoughts
Brené Brown's research reminds us that leadership is not about having immediate answers; it’s about having the courage to stay with difficult questions long enough to discover meaningful solutions.
That lesson is equally true for quality management. Every meaningful risk assessment begins with challenging assumptions; every effective CAPA begins with asking the difficult questions; every resilient quality system begins with leaders who refuse to accept recurring problems as inevitable.
Ultimately, risk management is not just a regulatory requirement under ICH E6 (R3). It is a leadership discipline. Organizations that embrace a leadership-driven quality culture will not simply pass inspections, they will build stronger systems, protect study participants more effectively, produce more reliable data, and accelerate the path from clinical development to patients who need new therapies.