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Optimize time and cost of product development by managing risk.
The issuance of the FDA's guidance in 2004 advocating a risk-based approach to current good manufacturing practices (cGMPs) has changed the basic paradigm for quality in the biopharmaceutical industry. This guidance advocates using scientific inquiry as a foundation for developing quality initiatives that will ensure ongoing product quality. Managing risk in the product development lifecycle presents the industry with an opportunity to optimize the time, resources, and cost of developing a drug product. This same opportunity extends to the establishment of our quality argument and all of its related systems.
The challenge in embracing this new approach to quality is shifting from the traditional mindset based on blanket inspection and testing to one driven by control and monitoring. We must change our approach and quality standards for troubleshooting and prevention if we are to realize the agency's vision of quality and business synergy. In an industry where the ratio of quality to operations personnel can reach 3:1, as is often seen in large biopharmaceutical operations, the concept that quality can operate synergistically with the needs of the business is a radical departure from what we have experienced for the last 50 years.
With this shift in philosophy by both industry and the regulatory bodies, we find ourselves reinventing our approach and expectations to fundamental quality activities, such as root cause analysis (RCA). RCA is an approach to problem solving aimed at identifying the basic drivers or causes for problems or events. The philosophy behind RCA is predicated on the belief that problems are best solved by attempting to correct or eliminate root causes, as opposed to merely addressing the immediately obvious symptoms.
In investigating a problem or event, there are three basic components we need to understand. We have the symptom, which is the failure observed against the expected performance; the mechanism that drove the failure; the contributing state or events that may have supported the failure; and the actual root cause of the failure. Separating these components is the key to an effective root cause analysis. The relationship among these components is shown in Figure 1.
Figure 1. Relationship among the components of root cause analysis.
By directing corrective measures at root causes, it is hoped that the likelihood of problem recurrence will be minimized. However, we recognize that complete prevention of recurrence by a single intervention is not always possible. To be effective, RCA is often a highly iterative process, and is frequently viewed as a tool for continuous improvement.
There is no single approach to RCA: it is an amalgam of different tools, processes, and analyses applied appropriately to identify the source of the problem or event. Even so, RCA exercises have not always been completely objective. We have all seen the corrective action and preventative action (CAPA) documents which have been closed, with the recommended root cause and corrective action being operator retraining. In such cases, the problems invariably reappear later because the corrective action was off the mark. An effective corrective action based on an effective RCA should eliminate the problem or event from happening again. In the absence of this reality, the RCA was not effective.
The lack of a disciplined approach to RCA has undermined the effectiveness of CAPA programs and often leads to recurring issues with products. As a result, the focus of many FDA inspections has been the quality and defensibility of RCAs, which are often used to close out a CAPA. Nevertheless, the emphasis in the biopharmaceutical industry on moving toward a more process-centric rather than a product-centric philosophy for quality assurance has laid the groundwork for a more effective RCA exercise. The emergence of operational excellence initiatives has rekindled interest in structured problem solving techniques such as Kepner-Tregoe that methodically drive the analysis toward an objectively defensible final conclusion. But the one thing we have learned as an industry is that there is no magic bullet, no one-size-fits-all solution that we can just buy and implement to meet this shift in quality philosophy. However, a common framework defines all good investigative processes. This article describes and illustrates the application of one approach that is very effective in integrating the basic tenets of Quality by Design and risk management as purported by ICH Q10 as a methodology for an effective RCA.
The RCA roadmap borrows heavily from best practice methodologies for process development and characterization. It consists of eight steps designed to identify the metrics for success, the sources of variation in the process, and their success remediation steps, as follows:
1. Establish a project charter.
2. Understand the project scope.
3. Understand the process and product.
4. Understand the measurements.
5. Understand the performance.
6. Address the corrective action.
7. Monitor process stability.
8. Summarize the results.
The purpose of defining the project charter is to clearly establish the metrics for success for the project. We are often simply told we have a failure or a problem and to fix it. Defining the specifics of the issue is essential to setting the scope and direction of the investigation. Any structure may be used for this exercise, but the establishment of the charter should be objective and include definitive metrics for the current process and the future desired metrics that would represent a successful RCA exercise. If a product is failing or trending out of specification on stability, then a summary of the historical performance of the product should be a starting point for comparison. The charter also should establish the priority for resolving the RCA exercise. If there are regulatory, safety, or business implications driving the RCA, then a sponsor for the exercise will be essential to gain the right organizational support for the investigation. Clearly identifying this individual and gaining his or her buy-in for the effort is critical to a successful RCA. The project charter also focuses the team on the primary goals and scope of the project and milestones for completion. Another measure of value may be to analyze the cost of poor quality, both internal and external to the company. Understanding the cost exposure of dealing with deviations, failures, and recalls contributes to the urgency and priority that should be assigned to the RCA in the organization.
Setting the project scope is a critical activity during the chartering process. RCA exercises too often get derailed by issues that are not related to the fundamental problem or event. For example, if a tablet is failing potency on stability because of the presence of escalating degradation products, do not worry about the content uniformity or tablet breakage issues that production may be struggling with. Although there could be a relationship between these characteristics, it is better to let the investigation and the data drive the conclusion rather than pursue all paths simultaneously.
Before any RCA exercise can begin, the investigating individual or team must have a baseline understanding of the process or product and the steps and variables involved in the process. Although there is no absolute set of tools to use for this exercise, a successful sequence for establishing process understanding is shown in Table 1.
Table 1. A successful sequence for establishing process understanding
Based on these analyses, a clear list of what we do and do not know should now be apparent. This should drive activity to address the missing information. A fundamental truth for RCA activities is that we cannot effectively implement a corrective action if we do not understand the drivers of variation in the process.
Before delving too far into the failure mode data analysis, it is important to establish that the measurement systems used to steer and measure process or product performance are capable of distinguishing a good process or product from a bad process. Most analytical methods in our industry go through a rigorous method development and qualification. However, saying a method is validated is not good enough to ensure the level of resolution necessary to identify the root cause of the problem. Depending on the test or the company's quality policy, method errors of 5–7% are often deemed acceptable. This could be a problem when looking for subtle changes in a process or problem that can be driving the observed failure mode. Understanding the variation that is native to the method, the sampling technique, and the raw materials is crucial to deciphering what is really happening with the process. Studying variation in a process is the quest to differentiate between common cause variation that is native to a controlled process and special cause variation that is driving the failure mode.
Look at the error allocation between the equipment, process, method, and operators. This is often confirmed by a simple gauge repeatability and reproducibility study that will determine whether the measurement method is capable of distinguishing good from bad product. If the method is deemed unsuitable, then an alternate measurement scheme will be required by the team. When conducting an analysis of your measurement system, consider the following four questions:
1. Is the measurement system stable?
2. Are you able to measure differences in the process? This is needed to be able to drive process improvement.
3. Are you able to measure differences to distinguish good results from bad? This is needed for quality control of a nonconforming product.
4. If you can't measure the differences, then what can you do to improve the measurement system?
The abovementioned tools will have clearly categorized what key process variables drive performance and which measurement tools you can trust to steer your process. If the conclusion from the previous steps does not answer these questions, then studies will have to be performed to gather the required information. Before moving forward, it is important to understand the regulatory landscape for the project. What commitments have been made and what are the requirements for demonstrating that the product is behaving as originally intended? In this step, any studies should consider statistical sampling plans and all process variable investigations must be statistically unbiased, i.e., orthogonal. Understanding the difference between attribute testing and continuous variable testing will help steer the group to the correct sample size and conclusions in terms of root cause identification.
A good rule of thumb at this step is to assume that if you can turn the failure mode on and off then you will have identified the root cause for the problem. Integrating this sensibility, actually trying to cause a failure is a key component to establishing a standard for defensible RCAs.
Implementing the corrective action should move the process back to where it was behaving predictably. Establishing a baseline for key performance metrics and establishing alert and action limits for these variables will ensure the process failure does not reappear unexpectedly.
The final step in the process is to capture the previous seven steps in a comprehensive document that clearly illustrates the rationale and criteria used for the decision and the conclusions made during this investigation. The final report should definitively establish that the root cause has been identified and be able to use the RCA methodology and final data to defend this conclusion. All eight steps are illustrated in Figure 2.
Figure 2. The root cause analysis roadmap consists of eight steps to identify the metrics of success.
Establishing an objective, data-driven methodology is a critical component to an effective RCA exercise. You may leverage established quality and risk management tools as part of the process to help focus the investigation on the key elements that are critical to the observed failure mode. Maintaining the remediated process through focused monitoring of the key parameters, which drive process stability and performance, will ensure that the conclusion drawn from the RCA investigation and the remediation implemented will maintain processability and predictability and drive down or eliminate the compliance risk associated with substandard or incomplete RCA investigations.
Bikash Chatterjee is president and chief technology officer and Wai Wong is director, both at Pharmatech Associates, Hayward, CA, 510.760.2456, firstname.lastname@example.org