PAT – A Risk-Based Approach
Examining a risk-based approach within the FDA’s initiative
By: Bonnie Haferkamp, Life Sciences, Rockwell Automation
It can seem impossible for life sciences companies to simultaneously tackle cost, product quality and regulatory compliance pressures with the well-established inverse relationship between them. Add a program to improve product variability to the mix, and costs go up. At the end of the day, you might end up with a project designed to reduce costs that can stall with the additional regulatory compliance factors that must be addressed.
One of the bright spots to emerge is the potential advantages offered by process analytical technology (PAT). Here, you’ll find the U.S. FDA’s continued recognition of this dilemma and resolve to allow the pharmaceutical industry to become competitive in manufacturing by producing a paradigm in which cost, quality and compliance are in harmony through a risk-based approach.
In an article in the September 2006 issue, we characterized the scope of process analytical technology (PAT) based on the U.S. FDA’s four principles that form the pillars of a PAT strategy:
Regulatory strategy to accommodate innovation
This article will examine the role of a risk-based approach within a PAT strategy. The FDA has promoted a risk-based approach as a major initiative for 21st century current good manufacturing processes (cGMPs) with PAT as one guidance document generated out of the overall initiative. Within the PAT framework, the risk-based approach recognizes:
The level of scientific understanding of how formulation and manufacturing process factors affect product quality and performance.
The capability of process control strategies to prevent or mitigate the risk of producing a poor quality product.
As we will see, a risk-based approach based on process understanding can not only help you mitigate risk, but also quantify benefits to your process, production area, facility and company.
Value of a Risk-Based Approach
Risk exists at many levels. Process issues can cause product defects and increase waste. Regulatory issues can result in warning letters and consent decrees. Ultimately, inadequately addressed risk can jeopardize the health of patients as well as damage a manufacturer’s brand image and finances. Fines for consent decrees and resulting lost sales can each reach hundreds of millions of dollars.
A science-based approach to manufacturing based on in-depth process understanding can help reduce risk. That’s because knowing why a process behaves a particular way, can help identify what could potentially go wrong, how often it is likely to occur, and its potential impact on product quality. With a risk-based approach, high frequency and high severity events can be proactively and more consistently managed to mitigate negative impacts. In some cases the frequency can be significantly reduced or eliminated. The result is higher efficiency, more consistent quality, and a positive impact on a company’s bottom line.
Tackling a Risk-Based Approach
While the four principles of a PAT strategy (process understanding, risk-based approach, regulatory strategy, real-time release) are important individually, they are very much dependent on one another. A risk-based approach must begin with process understanding as its foundation. With a scientific understanding of the process, critical process parameters (CPP) with the most influence on critical quality attributes (CQA) can be identified. With control of the process, product quality attribute (PQA) targets can be achieved, resulting in consistent and predictable product quality against specifications.A three-step sequence breaks down a risk-based approach into a manageable process.
Step 1: Understand your process. The first step is to first develop the principles models of your process, so they can be used to determine the relationships between CPPs, CQAs and PQAs. Often, the information needed to create a first principles model of a process is incomplete or not available at all, depending on the complexity of the system. In this case, an in-depth analysis of historical process data can help discern relationships between raw material inputs, process conditions and product quality to develop logical rules or scientific models of the process. Hybrid models also can be used to augment incomplete first principles models with heuristic or empirical models.
Step 2: Analyze your risk. Once the CPP, CQA and PQA relationships have been analyzed, the impact of adverse events can be more accurately assessed. By quantifying the frequency of adverse events and the impact on PQAs, risk severity can be estimated and adverse events in production can be more easily detected.
Step 3: Mitigate your risk. Create scenarios and model your “as is” versus “what if” potential for identifying and acting upon risk in real-time in your manufacturing environment. Simulation models are an ideal tool for this task. By evaluating different scenarios, you can help quantify the value of your risk mitigation strategy and develop a return on investment model for implementing risk reduction controls. You also should determine whether your production environment is capable of analyzing and identifying adverse events on a continuous basis. If adverse events can’t be easily detected in time to mitigate negative impacts, it may be time to invest in either online production monitoring systems that can continuously monitor your process and provide alerts or closed-loop control systems that can minimize production disruptions or product quality issues.
A multitude of tools and technologies exist to support process and risk analysis. Many tools help identify process parameters that have the greatest impact on process variability and product quality. Other tools can be used to help teams brainstorm the range of risks in a structured hierarchy to help assess adverse events and outcomes with priorities. Advanced process control, enforced workflows through electronic batch records, integrated information visualization and a host of other technologies and solutions can provide on-line, real-time risk mitigation.
What Other Companies Have Achieved with a Risk-Based Approach
A risk-based approach can drive real results. One pharmaceutical company, for example, had difficulty keeping critical process parameters in control, resulting in lower operating efficiencies. The problems were exacerbated by a lack of tools to analyze the problems and non-standard practices in place across multiple plants. Audits and risk assessments were performed on three production lines to correlate PQAs to CPPs, identify the sources of variability on the lines and improve understanding for control requirements. To better understand the problem, a failure modes and effect analysis was performed on all CPPs. By implementing proper procedures to correct the problems identified in the analysis, the manufacturer was able to reduce risk of producing out-of-spec product, improve line performance and enhance its corrective and preventative actions (CAPA) program.
Great examples of what can be achieved by applying PAT principles are found in other industries where product quality and public safety are paramount, such as the food industry. Although there is perhaps more freedom within the food industry to implement manufacturing improvement programs, common margins, FDA regulations and a demanding customer base dictate that regulations, quality and cost must be simultaneously addressed. Case in point is a dairy products manufacturer with unacceptable quality variability downstream of a batch pasteurizer. By developing a dynamic heat and mass balance around the pasteurizer and downstream operations with closed loop control around temperature, moisture, ingredient additions and processing speeds, this manufacturer reduced cycle time 15 percent and variability 40 percent, with return on investment in less than a year.
Taking the Next Steps
By using the three-step process, you can better quantify the benefits that a risk-based approach can bring to your process, production area, facility and company. While process understanding is fundamental to this analysis, don’t stop there. Evaluate different scenarios for mitigating risks and quantify the return on investment. Sometimes it’s hard to put numbers on risk mitigation, so don’t lose sight of the hard benefits that process understanding and risk mitigation can produce –such as increased manufacturing efficiency, increased right-first-time manufacturing, fewer deviations and shorter release cycles. Take a look at your company’s key performance indicators and ways they can be impacted when you close the loop with a risk-based approach.
Next time: Regulatory strategy to accommodate innovation.