Getting to the true root of lab quality problems

In the warning letter, FDA makes it clear that the concerned company must correct the problem and provide directions and a timeframe for the company to inform the FDA of their plans for correction. Failure to address the FDA’s concerns can lead to enforcement actions that have significant repercussions as well as product liability exposure. Therefore when a warning letter is received, company employees, especially senior management (who are already very busy), scramble to address it in the stipulated time frame.

It is estimated that a single warning letter leads to a loss of approx. 900 manhours across the hierarchy. This increases exponentially if there are multiple warning letters received simultaneously. It has to be noted that this will be at the cost of progress on their routine, ongoing tasks.

After this marathon, the remediation procedures that FDA expects companies to implement can be even more expensive than complying in the first place. Moreover, there are long-term repercussions in terms of loss of credibility with regulators - not just the FDA but also other global regulators, leading to increased scrutiny and more inspections. In case of repeat offenders, they often have to pay hefty fines and sign a consent decree of permanent injunction that will bind them to be compliant in perpetuity. All this can impact the company’s business/financial performance, affect company valuations, and reduce the overall reputation.

The problem

The major reasons for FDA warning letters are not unknown. About 50% of FDA warning letters pinpoint CAPA (corrective action and preventive action) failuresii. CAPA failures also show up year after year in these warning letters. Most of these CAPA failures are also clearly indicated by the FDA as a failure of root cause analysis.

What does not work well

So, over the years, pharma labs have been using multiple techniques to identify the root cause so that they can take the necessary actions to improve their quality performance. The popular techniques employed include 5-Whys, Fishbone diagrams, Pareto chart, Failure Mode and Effect Analysis (FMEA), decision trees, and brainstorming.

A significant chunk of the results of these analyses tends to point to human or analyst error (~40-55%). Therefore, some of the typical actions companies have taken are adopting digital systems for reducing documentation error, putting in next-generation analytical testing technology, automation of few of the quality processes, increasing the level of supervision in the lab, increase in the training of analysts and addition of resources to reduce the load on the system.

However, experience has shown many of these companies that these steps (always quite expensive in terms of time or money or both), while offering some improvement, do not help sustain high-quality standards consistently. After a while, any improvement that accrued stagnates or even more perplexingly, when something improves, something else seems to deteriorate. Moreover, FDA has increasingly been criticizing the finding of ‘human error’ as the conclusion of root cause analysis as limited or shallow and has been urging companies to take a deeper look.

The real root cause: Cognitive overload

A closer study of the testing environment in pharma companies will indicate that the analysts are often under a situation of significant ‘cognitive overload’. The analysts have the responsibility to

• conduct all activities of assigned tests as per the TDS (test data sheet) - i.e. collect glassware and documents, arrange for chemicals and reagents, ensure the validity of all solutions prepared till tests are complete, select appropriate equipment (e.g., column), manage instruments, etc.
• generate an audit trail for which they also have to record the equipment used.
• concurrently record various observations in TDS and maintain a separate checklist to ensure no steps are missed.

Skips and misses: All this the analysts have to manage in an eight-hour shift by switching between various stages of testing (instrument setting/monitoring, solution preparation, mobile phase, collecting glassware, checking/arranging resources, etc.) and by trying to take advantage of the natural waiting time in some of these stages. Unfortunately, the human brain finds such a balancing act and this level of multi-tasking very difficult to manage. Therefore, occurrences of inadvertent skips and misses became inevitable.

Systemic error masked as human error: In addition to such human errors, testing environments also tend to have systemic errors due to

• missing information in the SOPs set or because of inadequately documented SOPs.
• a process gap or due to a gap in the testing method

However, when faced with a melee of different kinds of problems cropping up daily, it is difficult for managers to correctly infer and assign real causality for these errors. So, in this confusion, even systemic errors are mistaken for human error. This inevitably leads to frequent-finger pointing, stress and inability to take timely corrective actions.

Direction of solution:

Based on these insights, it is obvious that the only option is to first address the cognitive overload in the system to bring down real manual errors to minimal levels. Then the systemic errors due to incorrect methods followed, unclear procedures, etc., will become visible, and actions can be taken to rectify them.

While this logic is unrefutably simple, implementing a system-wide, counterintuitive solution that can significantly bring down the cognitive load on analysts without loss of overall productivity is obviously a huge challenge. The key to this is to release capacity by identifying and eliminating significant wastages in the activities of the analysts. Research by Vector has shown that the level of analyst capacity wastage can be as high as 40% in a typical pharma lab.

The ‘flow’ focussed solutions that Vector implements for eliminating these wastages and for releasing capacity serve a dual purpose. On the one hand it enables the released capacity to be used for controlling the loading of analysts, and on the other, it will re-set the quality practices of the company to a much higher level of rigour. For instance, improving the STPs (Standard Testing Procedures) by detailing them more thoroughly to remove elements of subjectivity can ensure that a large number of systematic errors are eliminated.

A few pioneering companies have implemented this new approach. Within a few months, they could significantly reduce invalid OOS and bring down lab incidents! Some salient details of the results of the implementation achieved with a major multi-national pharma company’s labs in a year are as below:

If more companies address cognitive overload, which is the true root cause of their quality issues, it can bring down quality-related inconsistencies and keep companies ‘inspection ready’ at all times. With that, one is sure to see a dramatic dip in the warning letters FDA has to issue.