PAT gains traction

At IFPAC 2012, industry experts from the pharmaceutical and biopharmaceutical industries met with suppliers and partners to discuss the latest trends and development in PAT. During talks, it became evident that PAT implementation is gaining traction in the biopharmaceutical industry.

Although process analytical technology (PAT) has been implemented by other industries, biopharmaceutical companies have been slow to adopt it on an enterprise-wide scale. Historically, one of the limiting barriers to PAT implementation has been the FDA’s prescriptive regulations. But, during the past decade, the FDA has promulgated three separate guidelines - cGMPs for the 21st Century (2002), PAT (2004) and Process Validation (2011) - creating a regulatory environment that not only allows PAT implementation but strongly encourages it.

Under the framework of PAT, the use of real-time process analysers can be integrated into a control system, allowing manufacturers to understand their processes and, through this understanding, control them. Inextricably linked with PAT is the concept of built-in quality, or quality by design (QbD), which is the use of model-predictive methodologies to relate material properties and process parameters for finished product performance. The same analysis that allows manufacturers to apply QbD also tells them what they need to measure and what they need to control.

PAT Guidance has set off a few important trends in biopharmaceutical manufacturing: the gradual shift from scientists to process engineers driving manufacturing processes; the incorporation of information loops into the design of manufacturing processes; and the implementation of continuous manufacturing, first on a project-by-project basis for the most part, now moving towards enterprise-wide programs.

“The industry is striving to achieve ‘real-time release’ of finished products,” said Glenn Restivo, Industry Manager Pharma US, Siemens Industry. “And continuous manufacturing (with PAT as its heart) is the approach rapidly gaining acceptance to achieve this vision.”

The voices of process engineers become louder

One of the barriers to PAT adoption by the biopharmaceutical industry has been that the manufacturing process was heavily driven by the scientists who were responsible for product quality, rather than the process engineers responsible for the manufacturing process itself, according to Dr Sam Watts, Business Development & Commercial Officer, Stratophase, a company that provides biopharma with inline monitoring of glucose status.

“Over the last couple of years, the voice of the process engineers has become louder. They’re moving away from saying they must take absolute measurements,” Watts said. “There’s been a shift towards process engineers, who say, ‘If we can engineer a quality process, then we will have a quality product.’”

As the chemical industry, outside of pharmaceutical work, has been implementing PAT for some time now, there is transferable technology available. However, there isn’t a precedent for controlling biological processes, and in many cases, manufacturers are starting at square one with them - not in terms of available technology - but in terms of what they believe they can implement and the best way to do so.

“Given that biological processes are reactive, they do migrate. It’s important not only to do the upfront analyses, then lock the process down, but also to continue to verify the process through the course of its lifetime - and that’s where we get into process engineering. That’s where the industry hasn’t gotten that far,” said George Barringer, Consultant, Stratophase. “Biologicals need it perhaps more so than chemical. The small molecule process is less uncertain and higher yield. Biologicals are a very low-yield process, so we need to make every percentage point count.”

Using information loops in biopharmaceutical manufacturing

Ten years ago, biopharmaceutical manufacturers typically learned which manufacturing process designs worked well and which didn’t through one-at-a-time experiments, after which designs would be deemed successful or not. Failure was the driving force behind design changes, rather than the desire to acquire information about the process in order to optimise it.

“The biggest change in the pharma domain is that we are creating many situations where we’re using an information recycle loop. That was not the case 10 years ago,” said Fernando Muzzio, PhD, Director, Engineering Research Center for Structured Organic Particulate Systems, Rutgers University.

Information loops are intrinsic to QbD within a PAT framework. Muzzio described two situations where information recycle loops are in use: the control loop and the design loop. The control loop is in place when manufacturers implement a control process because they are measuring, analysing and then acting on the information. The design loop is in place when manufacturers do sequential design of experiments (DoE), meaning they do a DoE, take note of something and plan the next DoE accordingly. The design loop is also present when manufacturers are optimising their system.

“You develop a model, make predictions about what the process is going to do, implement those predictions and measure your outcomes. Your outcomes are never exactly like your predictions, so you refine your model, you make new predictions, and that’s the learning process,” Muzzio said.

Continuous manufacturing: moving from pilot projects to a strategic approach

It is widely anticipated that the use of QbD will become an expectation by the FDA - at least in the generic domain - sooner rather than later, perhaps in just a few years. It is also believed that the next iteration of PAT will be driven by different manufacturing methods and different product concepts. Muzzio said, “What’s coming next is that increasingly we’re going to deploy other ways to make products; for example, continuous manufacturing is a different way to make products.”

Muzzio recently started working with Janssen and Siemens on a continuous manufacturing project at Rutgers.

“Continuous manufacturing requires real-time control so that the process is running at a set point where you want it to run - and you can determine that it’s running that way. Without PAT, continuous manufacturing doesn’t work,” Muzzio said. “What you’re doing in continuous manufacturing is making predictive models as agile as possible so you can use it in real time and then import it into your system and control your process. Continuous manufacturing is where you bring everything together.”

The need for top-down support of PAT implementation cannot be overstated for successful enterprise-wide adoption. Otherwise, companies risk getting stuck in the pilot stage. There is an enormous difference between a company implementing PAT for a project here and a project there, and a company that takes a strategic approach to PAT implementation.

An important part of the Rutgers-Janssen continuous manufacturing project is Sipat, a standardised, modular PAT data management application/software solution developed by Siemens. Through Sipat, it is possible to control CPP (critical process parameters) and CQA (critical quality attributes) that are intermachine-related. Eventually, one of the key elements of the project will be Siemens’ ability to offer Janssen the capability of using information on materials, process and finished product in an integrated way so that the company can ensure the product is under control all the time, ensuring final product quality.

Hot-melt extrusion: an upcoming technology for the continuous approach

One part of the process chain for a continuous line in manufacturing is hot-melt extrusion. Other industries, such as plastics and food and beverage, have been implementing hot-melt extrusion for some time, but it is a new concept for biopharma. Through a cooperation agreement, the Research Center for Pharmaceutical Engineering (RCPE) in Graz, Austria, and Siemens AG teamed up to learn which parameters are of interest to biopharma and how to control them during hot-melt extrusion for biopharmaceutical manufacture.

“One of the trends we see is that the industry is moving towards a continuous manufacturing approach, and when you use a continuous approach, there are different analysers, new steps and new processes. An upcoming technology for pharma is hot-melt extrusion, which gives a continuous run of blending, mixing and conveying. For our project with RCPE, we are looking at many different variables and possibilities in continuous manufacturing data,” said Barbara Kavsek, Team Lead Process Analytics, Life Science Systems, Siemens AG.

Added Daniel Markl, Junior Researcher, RCPE, “It’s very important to monitor all these parameters. For this, we are using Sipat. We have a Sipat installation at RCPE configured for an extruder, a feeder and a spectrometer. We built a chemometric model, set up the analysers and used Sipat to monitor, measure and finally predict the API concentration. We also established a feedback loop, which allows us to control the process.”

The project is in the pilot stage for proof of functionality, proof of feasibility and, to a certain extent, proof of concept.

“Hot-melt extrusion is a new topic, and pharma companies want to know the feasibility of these probable changes to the whole manufacturing system,” Kavsek said.

Personalised medicine

In addition to continuous manufacturing, Rutgers’ Muzzio believes that there will be other new processes that will be just as transformative to biopharmaceutical manufacturing, if not more so.

“For personalised medicine, we’re eventually going to have to learn how to manufacture for the individual,” he said. “Personalised medicine manufacture is surely going to lead to very small systems, micro-manufacturing that makes micro-batches. In each of those systems, we’re going to make a small number of units, and we are going to have to assay them non-destructively. We will not be able to take 20 out of 20 units, for example, and send them to the lab. We’re going to need to be able to predict what we’re doing and what we’re supposed to do. We’re going to have to learn assay product properties without destroying product units. We’re definitely going to use PAT for personalised medicine.”

On the horizon: OPC UA ADI

Facilitating a standard data collection and communication between PAT analysers and automation or data mining infrastructure is the next generation of communication protocol for PAT data management, according to Johan Vanhoutte, Project Manager, Industry Sector, Siemens. OPC UA (OLE for Process Control-Unified Architecture) is a platform-independent standard through which various kinds of systems and devices can communicate by sending messages between clients and servers. Siemens has implemented the OPC UA ADI (OPC UA for Analyzer Devices) standard into Sipat.

“Making a good (specialised) instrument is the focus of small vendors; they have less interest in having IT people develop a lot of software for their instruments. So, they try to find standards in the market, and that’s where Siemens wants to help them overcome that hurdle.”

Though PAT adoption by biopharmaceutical companies has not yet hit the inflection point, it is clear from the companies themselves and the vendors who provide services to them that this point is coming soon. Companies that are prepared for PAT adoption to become an expectation on the part of FDA and a requirement for competitive advantage will be well positioned for the future.