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Sep 15, 2007 (Vol. 27, No. 16)

Moving Biotechnology Forward with PAT

Being Proactive Instead of Passive Is the Cornerstone of Process Analytical Technology

  • Interest in the application of process analytical technology (PAT) to pharma and biotech stems from the introduction of a CDER (Center for Drug Evaluation and Research) initiative on this theme in 2004. According to CDER, the goal of PAT is to understand and control the manufacturing process, building or designing in product quality.

    PAT is a system for designing, analyzing, and controlling manufacturing through appropriate measurement of quality and performance with a range of technologies, both old and new. An Informa Conference entitled “PAT—Quality by Design and Process Improvement,” held earlier this year in Amsterdam, provided a forum for those involved in PAT to share various aspects of this new approach.

  • Biopharma Production

    Bo Kara, Ph.D., head, expression and cell sciences, at Avecia Biologics (www.avecia.com), discussed the application of PAT to biopharmaceutical production. “Adopting PAT is particularly appropriate for biopharmaceuticals. With small molecules, testing the product is easier because the structure is known and there are a lot of analytical tools. With biopharmaceuticals, testing is more complex, and you cannot test for everything. PAT is more about understanding your process and how you actually operate.”

    Quality by Design (QbD) is a key element of PAT, which Dr. Kara defined as a process that ensures you achieve quality by careful, methodical scrutiny of all the attributes that go into the product and the process.

    The PAT approach gives the biotech industry freedom to think more about analytical tools for process development and manufacturing, leading to more information about the product. It gives more assurance and more real-time data. It can involve technologies that lead to a greater knowledge of a protein’s properties such as its secondary structure and glycosylation patterns. It can also be about technologies that make measurements during, rather than at the end of, a process to get more information about the process and whether it is being carried out correctly.

    Dr. Kara reported that at Avecia, they have been looking at the use of advanced chemometric tools, in collaboration with an academic group, within the PAT framework as well as at more conventional technologies, applying these to both products and raw materials. “The heart of PAT is to design a robust and reproducible process that works every time,” he explained.

    According to Dr. Kara, PAT could have a big impact if the data it produces is used to correct for deviations. “At present, you have an operating window and you have to decide whether to carry on or not if there is a deviation, but PAT may allow for it to be corrected, which you can’t do now because of process validation. We are a long way from this at the moment though.”

    PAT has great potential for helping the biotech and pharma industries improve key metrics such as On Time in Full (OTIF, a measure of the capability of the process to produce product when required), Right First Time (RFT, relating variability in product to specification limits), and CpK (a measure of process capability). A recent study reports that today’s pharma has an average of 60–80% for OTIF, 85–95% for RFT, and 1–2 for CpK, with biotech being on the low side of these figures and pharma plants somewhat higher. PAT could lead to near 100% for OTIF and RFT and around 3.2 on CpK, the study surmises.

    Another measure that is much discussed in terms of PAT is Sigma level, which is a measure of failure rate and has been related to the cost of poor quality to an industry. Currently, a range of Sigma levels is found throughout industry—in semiconductors it is at level 8, with a vanishingly small failure rate; in the aircraft and automotive industries, it is at level 6 with a failure rate of around three per million (also expressed as a yield of 99.9997%); average pharma today is at 3 Sigma but aspires to 6 Sigma.

    Research by IBM has highlighted the gains to be made through improving two different aspects of Sigma, which Dr. Kara noted, could be important for biotech manufacturing.

    Process Sigma (PS) is derived from internal failure rates and is a measure of process robustness and understanding. Quality Sigma (QS) is derived from the ability of a quality system to prevent internal failures created by the production process “escaping” into the environment. According to an IBM analysis, pharma has far more to gain by investing in improving PS than QS. In other words, a focus on process understanding rather than improving QC is the way forward.

    “PAT is not as new as people may think. Elements of PAT have already been applied in biotech, where the process is always the product,” concluded Dr. Kara. “PAT is not about one-off fixes, it is far more of a systems approach. There will be new tools, but PAT needs QbD and chemometrics and must be built into the whole system, from process development to manufacturing.”

  • Aseptic Processing

    Nicole Denkinger of biopharma operations, manufacturing science, Boehringer Ingelheim Pharma (www.boehringer-ingelheim.com), discussed the role of PAT in aseptic processing, where both old and new approaches are available for comparison. The benefit of PAT is to help introduce well-designed and well-understood processes into manufacturing, which allows product quality to move toward the 6 Sigma aspiration, she said. This will reduce problems like failed batches, recalls, complaints, and out-of-specification results.

    Aseptic filling involves various operations where process knowledge and process control are important such as sterile filtration, filling, lyophilization, capping, visual inspection, and storage.

    In filtration, for instance, PAT can play a role in gaining process knowledge or as an assessment tool, with respect to protein adsorption, protein degradation, and filtration yield. As a process-control tool, PAT can be used to monitor filtration pressure and flow rate. Denkinger went on to describe some of the PAT methods that can be used in aseptic filling and how they compare.

    In the filling operation, the target is to optimize fill accuracy. To achieve this, the process knowledge needed is filling speed, filling yield, filling duration, and the product temperature—the latter measurement being done by wireless temperature measurement.

    Process control in filling requires a fill-weight check, which is done by balance and nuclear magnetic resonance (NMR). The pros and cons of these two approaches to filling, of light-barrier technology in monitoring vial-stopper position, and mass spectrometry (MS) for checking flow rate in lyophilization, and other PAT methods used in aseptic filling operations, were looked at in terms of set up costs, influence of packaging material, level of process knowledge needed, and other factors.

    After the evaluation, it was noted that the balance and NMR both reduces the risk of having to discard part of a batch, while use of the light barrier for checking the stopper resulted in fewer rejects. In addition, pressure-rise testing or MS for mass flow in lyophilization and near infrared spectroscopy for measuring residual water in lyophilization all resulted in better control of critical parameters. Finally, residual-seal-force measurements in capping led to fewer rejects, and wireless temperature measurements gave useful process data in cases of deviations.

  • Design Space

    René Labatut, Ph.D., associate vp of global manufacturing technology at sanofi pasteur (www.sanofipasteur.com), put forward the view that the PAT concept is evolving into the broader idea of design space, of which QbD is an important element and is especially important for vaccine manufacturing where, as in other sectors of biotech, the process is the product.

    Sanofi pasteur has been using PAT/design-space approaches for data management and process control to gain a deeper understanding of data generated by a process. “Process analytical technology should be used to catch and look after appropriate data,” Dr. Labatut said. “A lot of data has no real value and will have no influence on the economic value of the product. Maybe process analytical technology can be used to help us clean our data of this noise. Further, having a design-space mindset helps to define exactly how a process works.”

    PAT has been gradually introduced at sanofi pasteur over the last five to six years at different levels of application. The company is going for more and more online and real-time analytical data, rather than off-line data that can take days, if not months, to process. “We are getting as close to real time as possible in our processes,” Dr. Labatut explained.

    In some processes, sanofi pasteur is introducing new analytical technologies such as near infrared spectroscopy for measuring moisture content with the aim of obtaining a precise fingerprint characterization of products like influenza vaccines.

    “Process analytical technology is about becoming more proactive, rather than passive. We are controlling our output by managing the process better rather than analyzing it later,” said Dr Labatut. “This new mindset should be engaged early on, right at the process-development stage, so you can have a view of your process space—knowing where you can’t go and where you can navigate.”



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