By Glenn Restivo
Life Sciences Industry Marketing Manager
Pharmaceutical manufacturers are facing some of the most challenging market conditions ever. Better and improved technologies are available, but companies find themselves under increased pressure to bolster drug pipelines, accelerate the production process and meet increasingly higher earnings expectations. Adding to this challenge are the social pressures to contain costs, while still conducting extensive research to discover breakthrough drugs.
While drug development and time-to-market remain vital to business success, manufacturing efficiency has become equally critical and a key competitive advantage. This intense environment of change is forcing companies to focus on core competencies and to address business-level issues throughout the complete product lifecycle. More importantly, however, it has created an unprecedented need for a new pharmaceutical enterprise business model. That may help explain the growing enthusiasm in the industry for the many potential gains offered by process analytical technology (PAT), a new U.S. Food and Drug Administration (FDA) initiative that aims to foster improvements in manufacturing efficiency and product quality while creating a harmonization of regulatory expectations. This scientific, risk-based approach is intended to help manufacturers develop and implement new efficient tools for use during pharmaceutical development, manufacturing and quality assurance.
The PAT framework has two components: the first is a set of scientific principles and tools supporting innovation; the second is a strategy for regulatory implementation that will accommodate innovation. The goal of PAT is to encourage the industry to adopt innovative technologies to increase quality without concern that a new approach will lead to validation risks and production delays.
With an emphasis on process understanding, the PAT approach is designed to allow companies to determine what variables are most critical to the final desired product; where controls should be inserted into the process; and what factors control sample degradation. In this context, process understanding refers to ensuring that sources of variability are identified and explained — that is, variability is managed by the process and product quality can be predicted. This knowledge base can be helpful to support and justify flexible regulatory paths for innovations in manufacturing and post-approval changes.
A key driver of PAT comes from the regulatory side, where the FDA recognized that its traditional approvals procedures were actually hindering manufacturing innovation. With increased guidance and assurance from the FDA, PAT is expected to encourage innovation and to reassure manufacturers that moving toward PAT-based manufacturing is in their best interest. While the benefits are clear, the hesitation toward adopting PAT is understandable.
Of specific concern is the fear of FDA reprisals should companies implement PAT on existing processes only to find problems in the system that wouldn’t have been discovered in normal process monitoring. The FDA recognizes this concern and is working to alleviate manufacturers’ fears, as noted in the FDA’s draft guidance document for PAT: “FDA does not intend to inspect research data collected on an existing product for the purpose of evaluating the suitability of an experimental process analyzer or other PAT tool. FDA’s routine inspection of a firm’s manufacturing process that incorporates a PAT tool for research purposes will be based on current regulatory standards (e.g., test results from currently approved or acceptable regulatory methods).”
The underlying premise of PAT is that quality cannot be tested into products; instead it should be built-in or should be by design. By encouraging the application of advanced analytical technologies and improvements in manufacturing efficiency, companies hope to parlay this strategy into higher quality products, less rework, increased profits and a distinct competitive advantage.
Applying a New StrategyThe traditional approach to regulating quality in pharmaceutical manufacturing involved a laboratory analysis to verify quality after manufacturing the finished product. Many of these inefficiencies are based on traditions, cost considerations and a general reluctance to change. The disadvantages of this approach are continual process optimization, high levels of rejected product and limited adoption of new technologies.
The key to the success of PAT is applying the process monitoring tools needed to analyze each of the critical product attributes. Equally important is having the process controls in place to make production adjustments based on the analysis. Detecting errors or process deviations and correcting them, while the product is being made is more cost-efficient, and can help justify flexible regulatory paths for innovations in manufacturing and post-approval changes.
The pharmaceutical industry has historically been lab-centric – with minimal closed-loop, real-time control and limited enterprise-wide data availability. A key to optimizing manufacturing in the future will be to make data visible in the context it is needed. Similarly, the ability to cost-efficiently manage data with connectivity to the point-of-use will be important both within the company and with the FDA as part of the approval process.
Program ImplementationThe successful application of PAT requires a shift in organizational structure, including the development of in-house expertise and training, changes to existing inspection and validation methodologies, and reliance on specialized PAT support teams. The implementation of a PAT program requires identifying the relevant technologies that can be applied and the creation of an integrated data management infrastructure capable of handling the volume of data to be recorded. It also requires advanced automation, visualization and analysis tools to manage the continuous identification and prediction stages in the process.
For the majority of manufacturers, the transition to a PAT strategy is too monumental to be made in a single effort. Instead, they should look to implement a PAT program in phases, starting with a specific project or production line and then gradually expanding to other areas. The first step is to conduct a productivity improvement appraisal (PIA) to analyze existing product lines and determine which may benefit most from PAT.
A PIA report identifies possible productivity improvement opportunities such as:
• identification of best practices
• identification of acquired critical operating data (COD)
• reusable engineering components
• cost reduction
• overall equipment effectiveness (OEE) data, and
• other key performance indicators (KPIs)
Potential costs and benefits can then be generated, which will help create a list of financially viable projects. By carefully analyzing likely opportunities and implementing PAT projects in phases, companies can more accurately assess the potential impact of process changes and better manage investment costs. Defining the business drivers and potential benefits from a PAT initiative are essential for a successful project.
Equally critical are continuous learning and efficient information management. Specifically, it will be important for manufacturers to understand the significance of each data point and how best to use this information to justify proposals for post-approval process changes. Likewise, the assembly and dissemination of this information will be important both within the company and with the FDA as part of the approval process.
Once a specific project is identified, the next step involves re-evaluating work practices, process chemistry, manufacturing techniques, and inspection and validation methods. In the analysis phase, engineers perform a thorough and systematic review of product filings, exception history, manufacturing and quality data and other sources for each product to verify if the original critical process parameters (CPPs) are still valid, or whether other parameters not originally identified are now more critical. The emphasis is on CPPs that affect in-process product quality rather than quantitative measurements.
The results of the analysis provide the basis for determining which manufacturing technologies and quality assurance tools will comprise the PAT solution. This might include: data acquisition and analysis technology; modern process analyzers or process analytical chemistry tools; knowledge management systems; and process and endpoint tools for real-time or near-real time monitoring and control of all critical attributes. It’s important that the risk and impact assessments be completed on the basis of data and not on opinions or theories.
Design strategies should address:
• the attributes of input materials;
• the ability and reliability of process analyzers or other instrumentation like Near Infrared (NIR) sensors to measure critical attributes; and
• the achievement of pre-established process endpoints to ensure consistent quality of the output materials and the final product.
Keep in mind that improperly developed processes, poorly trained operators, or equipment that has not been properly qualified will hinder any PAT efforts. The key to long-term success in applying PAT is oversight after installation by a specialized, dedicated PAT support team. To that end, it’s critical that companies obtain and retain employees with education, training, and experience in multiple disciplines, including process control engineering, process analytical chemistry, instrumentation and metrology.
Showing Return on InvestmentAlso key to successful implementation, is the ability of project managers to make a solid business case for adopting PAT. A good first step is to educate management on the value of PAT, which requires effectively articulating – in management terms – what the initiative is intended to accomplish and how this relates to the underlying business goals.
By making carefully planned investments in equipment and resources, project managers can show measurable results. With tangible benefits in hand, they’re in better position to justify larger investments and expand the program on an incremental basis. The reality is that good manufacturing practices will always reduce a plant’s total cost to produce.
Gains in quality safety and/or efficiency will vary depending on the product and are likely to come from:
• Reducing production cycle times by using on- in- and/or at-line measurements and controls
• Improving efficiency by managing product variability
• Reducing rejects, scrap, and re-processing
• Considering the possibility of real-time release
• Increasing automation to improve operator safety and reduce human errors
•Facilitating continuous quality enhancements that yield positive relationships with regulatory agencies
In today’s lean manufacturing environment, it’s critical for companies of all sizes to focus on optimizing their production processes. By adopting the PAT framework and building in quality on the front end, pharmaceutical manufacturers can more effectively maximize their production assets and will be better positioned to adapt quickly to market changes. Moreover, since the initiative has the support of FDA, a successful PAT program can lead to regulatory incentives. After all, it’s better to be ahead of the curve than behind it.