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In fact, the FDA’s 2002 current Good Manufacturing Practices (cGMPs), on which its PAT guidance and quality-by-design (QbD) recommendations are based, reportedly give drugmakers more leeway to make process changes without traditional validation if they make those changes within a pre-defined “design space,” according to Brian Stephens, ABB’s PAT coordinator for North America. He adds that research indicates that using PAT can reduce cycle times from 25 days to 12 days on average.
“The heart PAT is understanding your process and then using that understanding to improve manufacturing operations,” adds Bart Reiter, GE Fanuc’s life-sciences global industry manager. “However, especially in pharmaceutical firms, this can require changes in organizational thinking, behavior and funding allocations. Many pharma companies have been manufacturing the same way for 100 years, so a sea change is needed to shift their focus from just making product and onto manufacturing. This is not a technical problem—it’s a cultural problem. For example, one of our service technicians was at a pharmaceutical operation that was still using a ladle in its sugar-coating pans, and I know a guy who reported seeing an operator using a canoe paddle and a stopwatch in a blending operation.”
To improve their process knowledge and understanding, some pharmaceutical firms are forming PAT teams and enlisting process control engineers and suppliers to help update their primary and secondary processes from offline sample testing to online or at-line principle component analysis (PCA) of multivariable processes and projection of latent structures (PLS) to begin to accurately predict that a given batch will meet its quality parameters.
“Instead of waiting for end-product test results, the FDA’s PAT guidelines say manufacturers can release product before testing if they can prove they have enough knowledge of their entire process and the multivariate analysis tools to accurately predict that they’ll meet required product quality parameters,” says Terry Blevins, Emerson’s principle process management technologist. For example, Emerson’s DeltaV Insight software identifies process dynamics with each loop and at each point of a batch, so users can diagnose, identify gains and make process changes as a batch progresses. He adds that Emerson recently helped Baxter Healthcare avoid $6 million in capital revalidation costs by implementing multi-loop process control to the distilling process at a new anesthetic production facility.
Unfortunately, these tasks aren’t made any easier by the fact that batch systems must deal with numerous different operating conditions during their cycles (Figure 2). For instance, feed-flow, oxygen and/or reagent demands can vary widely during a typical bioreactor cycle, which can make it hard for sensors and controls to adhere to parameters and maintain product quality, so PAT projects often need to implement continuous performance monitoring and control functions. Despite the upfront development and configuration costs, PAT can help users save time and improve quality by moving from manual feeding that can shock batches and increase variability to continuous feed that can improve consistency.
“The ability to sample and test every four hours, which Broadley-James’ bioreactor can do with Nova’s analyzer, expands our knowledge and allows more impact on the process,” adds Blevins. “However, these methods need to be designed into processes at the product development stage.”
Likewise, New York City-based Pfizer’s plant in Ireland recently installed near infrared (NIR) spectrometers to monitor moisture closer to real time when drying its Lipitor product. Drying the pills used to take two days, and then samples were analyzed offline. However, after jointly developing and installing ABB’s FTPA 2000 NIR analyzers and software, Pfizer discovered that it was able to dry the pills in one day, and saved about $10 million in one year, says Thomas Buijs, ABB’s produce line supervisor for AAS and remote sensing.
“Traditional pharmaceutical manufacturing wastes huge amounts of time waiting for lab results that come back too late to optimize its processes,” says Buijs. “The key factor is being able to measure closer to real time, which allows better optimization and reduces cycle time.”
Buijs adds that ABB also helped Novartis, based in Basel, Switzerland, add a small NIR device and battery-powered WiFi equipment to a three-powder blending application in a V-shaped arrangement of two drums to make sure the powders were blended homogeneously. Using NIR meant that waiting for lab results was no longer needed in this application.
“There are articles and training courses on PAT, but the change is also a mindset change on the factory floor. As long as pharmaceutical manufacturers think of quality in traditional terms, they’ll continue to fail to understand the need for PAT or how to apply it,” explains Mahboubian-Jones “Pharma has a huge amount to learn, but the biggest lesson is that it’s not unique, that others have similar problems and have developed solutions which make an excellent starting point. One way is to bring in expertise from outside the industry, which is very rare in pharmaceuticals.
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