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Investing Time to Make Money: A PAT Implementation Perspective (continued)

Returns on team, time, and investment Recommendations from industry observers about how to implement PAT in the manufacturing environment have a common thread: Develop a common understanding among all PAT-affected parties. Avoid complex experiments, especially early in the program. Use valid process-capability metrics. Recognize that PAT sensing and monitoring tools are interdependent. Accept the onset of automation. Demonstrate periodic successes along the way. Keep PAT process research separate from PAT-implemented product methodology until you are completely ready. How long should this strategy take to achieve? Let's assume Fundamental Pharma plans to produce a solid dosage form product using PAT before 2010. Each year should carry its own task burden and, more importantly, its own benchmarked goals. Year one: 2005. If a PAT team is not already in place, one must be formed. Teamwork is critical to PAT's success. Check with human resources for guidance in working together. And, be very sure both the required personnel and time are available to complete the program. Be sure to include representatives from quality operations, manufacturing, product R&D, formulation, analytical services, and corporate finance. Heed the advice of experienced industry representatives and select a simple project. Establish stepwise goals and keep to a timeline. The team must win at intermediate levels before finalizing the project. Subcommittees can and should operate in parallel. By the end of the year, the team should test its plan on a simple, existing, relatively failure-free product under the CGMP environment. That test should include an evaluation of operations and the attendant sensors that will provide unit operation control. Though one must accomplish a large amount of work in the first year, a heavy task load is critical to success. The steps one fails to take now can cause unacceptable consequences down the road. Be sure to address the following planning elements: Begin a dialogue with FDA. Ask a financial team member to create a series of metrics (acceptable to the management team) to establish an ROI as the project matures. Become familiar with the language and structure of process operations, especially those that involve feedback and feed-forward control elements. Make sure the sensor vendors are qualified. Insist that they be capable of developmental qualification—the "DQ" in the DQ–IQ–OQ–PQ chain. Explore contract outsourcing for turnkey program elements. Year two: 2006. By now, the team will have a well-established leader, capable subcommittees, and a plan of action. This year, the team must test sensors with operating machinery, most likely at the pilot level. All testing should be conducted outside the validated operations area, but it does require dedicated equipment access. Clearly, this is an investment year. The team will have exhausted available public information by now, so further data will only come from deploying test equipment. The second year is the program's R&D period, so false starts and parallel evaluations will be the norm. The team will learn to assess manufacturing processes for optimization. Awareness of the industry's low manufacturing efficiency suggests that the team needs expertise in continuous process evaluation. By year's end, the planned process will be defined, sensors and monitors will be selected, and a fully documented transition to scaled-up operation will be ready. Year three: 2007. The manufacturer is ready to begin making product on a test-case basis. Because it is important that equipment not fail, parallel machinery should be fitted with sensors. Wireless transmission should be in place. Operation-monitoring software must be capable of indicating process refinements (e.g., dryness, particulate nature, blend completion, or lubricant condition) and, in short, anything that the team has determined to be critical to quality. The dialogue with process and manufacturing personnel during the first two years will pay off now. Analytical sensing will begin to merge with manufacturing and control systems such as human–machine interface, manufacturing execution system, enterprise resource planning, and materials requirements planning, among others. Test manufacturing will evolve from measurements with CGMP to PAT. All this effort is classified as "process R&D" and therefore is not subject to regulatory risk, per FDA's PAT guidance (1). Keep in mind that FDA has a vested interest in the industry's success with PAT, so manufacturers should continue to involve the agency in the implementation process. The Pharmaceutical Inspectorate has been trained in science-based testing and, by the time the program is ready, it will have amassed a record of its experience. If the inspectors are happy with plans in the R&D stage, another pitfall on the road to product release has been eliminated. By the end of the third year, the team should produce test product on multiple scale-up or pilot lines. Year four: 2008. In this year, one must prepare for full production. The manufacturer should know what makes the process tick and which data predict failure before it happens. The company has long since abandoned the "run three batches, store the results, and forget them" mentality. Work simplification is all that remains to be achieved, at least technically. This task calls for automation. The need for control will surface while the team evaluates sensors, checks monitors, and ensures wireless compatibility, feedback, and feed-forward. Even if the company didn't think about control, the vendor did. Why watch a trend chart and hover over machinery controls if a robust program can achieve it faster and more reliably? While the company sets production lines in motion, the document burden for product release is making headway. Time spent with FDA's Pharmaceutical Inspectorate during the third year is paying off now. Approval for a "go" should be merely formal recognition of an already well-understood process. Year five: 2009. During this year, one must make product; stay on top of well-established trends; collect operating data such as OOS and OOR records, time-to-market issues, and lack of recalls; and calculate actual process capability indices. One must remember: PAT is not measurement. It is control. "Making product" means that the manufacturer is exercising a well-understood, optimized operation that delivers a high-quality drug with consistency and timeliness. Year six: 2010. Fundamental Pharma has successfully marketed a drug product that meets all quality norms consistently. 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