As early as 1997, automation was ready to offer potential benefits to the bioprocess industry (1). Professor Bernhard Sonnleitner of the Zürich University of Applied Sciences' Institute for Chemistry and Biological Chemistry suggested a “standard operating procedure” and pointed to the opportunities, requirements, and potential pitfalls of applying the principles of automation to bioprocess development and operations. If “boring and less interesting routine tasks” could “more efficiently and reliably be handed down to machines,” he explained, then personnel could “engage in more useful work.”

His proposal might be seen as a genesis of quality by design: First, measure everything that can be measured early on; then, determine which variables are most relevant and identify those that must be controlled/documented; and finally, collect data from the process and organize it according to those determinations. In just a few pages, Sonnleitner showed the way to developing what many practitioners now call profound knowledge (2). However, even he warned that “it will take some time and efforts” to make this state of the art into “state of routine as well.”

What Took So Long?

Over a decade later, we are finally well on the way. What took so long? According to Sonnleitner himself in a recent email, “developments have proceeded rather slowly” over the past 10 years. When I asked him why there were so few related papers published after his paper (until very recently, anyway), he pointed out that in general, development work does not find its way into journal publication as much or as easily as research does. “Development of ‘problem solutions’ does not really pay back very soon,” he said. “We need problem solutions rather than instruments.” And up to this point, he added, the “robustness of many methods, algorithms, and hardware is insufficient for industrial application. However, the PAT initiative seems to be very helpful and supporting. Obviously, such developments need much time.”

BPI contributing editor Lorna McLeod recently spoke with industry consultant Larry West (formerly of Finesse Solutions and Broadley-James Bioprocess Technologies) about the FDA's process analytical technology (PAT) initiative. He reminded her that it “came out with a firestorm of attention.” Early on, he said, some people were thinking “If you didn't do it right the first time, PAT would give you an opportunity to fix it.” But, he continued, PAT has “found itself usurped by the role of quality by design (QbD), operational excellence (OpEx), and all these other acronyms. PAT by itself was more or less compromised because many wondered what it did and did not entail. In combination with these other emerging solutions, it is giving everybody a sense of comfort that automation won't equal vengeful regulation.”

In another discussion, Norbert Hentschel of Boehringer Ingelheim Pharma in Germany told Lorna, “In our new cell culture faciltiy we have a MES system, but we actually don't use it for a formal PAT program. However, if processes are developed applying PAT concepts, I believe that some measurement can certainly be used to apply it in a manufacturing environment. But you can't look at PAT alone. It's part of quality by design in process development. This is the foundation of process understanding, and that is the foundation for process control with a PAT program. What's needed is linking the controls in a facility to an understanding of product, process, and quality. But it's hard to implement a PAT program with established processes.”

In a separate interview, Lorna asked Peter Watler of Hyde Engineering and Consulting (formerly of VaxGen, Amgen, and Allelix Biopharmaceuticals) why he thinks automation has taken so long to find inroads with bioprocessors. “We're waiting for additional sensors that are robust enough to stand up to a manufacturing environment,” he told her, “and that's coming along.” Ideally, something like online high-performance liquid chromatography (HPLC) would help determine chromatography pooling criteria and selection during processing. “This could also help control purification unit operations such as tangential flow filtration,” Watler explained. “It could be used to monitor contaminant profiles during diafiltration. Analytical sampling, analysis, and feedback information could all be packaged together. Naturally, it will take some time to get those technologies together.”

Watler described feedback control — wherein information obtained by, for example, such sensors triggers control actions — as an essential goal of PAT. He pointed out that the new FDA guidance on process validation (3) emphasizes feedback as a way to learn about a process through monitoring. “I think the regulatory guidance will help to stimulate the industry to keep moving in the direction of feedback control,” he said. Traditionally, process validation has translated to processes that are “locked in” and tightly controlled without deviation. So-called out-of-specification (OOS) results require investigation and corrective/preventive actions (CAPAs). Combining PAT with QbD should allow for normal fluctuations in temperature, for example, or material variabilities — especially with feedback controls set within design space parameters.

The process validation guidance, Watler says, “recognizes that there will be variability. It's asking manufacturers, ‘How are you going to deal with this variability? What kind of feedback control are you going to have?’ All that then ties back to PAT. Ultimately, we're controlling product quality, which is really the target of our manufacturing processes.”

Controllers and Communications: Looking back at Sonnleitner's article, West remarked, “You know, 1997 seems like a lifetime ago. In defense of our industry, the reason we couldn't do what was inherently obvious to the author was the lack of core technologies: the controllers and the handshakes between them and bioprocess equipment such as reactors and chromatography skids. A 1997 bioprocess controller was about the equivalent of a 2002 videocassette recorder. They were built to function rudimentarily because that was what they were tasked to be. What we realized fully five years after that article was that if we continue to run our processes on glorified VCRs, we could never achieve the efficiencies and models needed to make this a business and not just science.

“So the controllers started to evolve, and with that evolution the associated pumps, mass-flow gas measurement devices, everything evolved with them to elevate our capability to where we are today. Full-blown automation didn't even really occur until 2005. It took that long for all the elements to finally come together and move forward. It wasn't a lack of vision; it was a lack of technology.”

Christopher Procyshyn is CEO of Vanrx PharmaSystems, Inc., an emerging player in isolation technologies and aseptic processing. He told Lorna, “Where a lot of difficulties happen is at the level of communication between those with the automation capabilities and those with the process needs. If we look at almost any other industry, automated systems and process control are frankly becoming quite ubiquitous. And the regulators are seeing successful projects and saying that obviously it can be done.”

He pointed to his area, aseptic processing, as an example. “Recent statements both in Europe and the United States call automated technologies and isolator systems the ‘new standard in aseptic filling.’ This suggests that they are ready to start pushing the envelope of what people have been comfortable with. But the real difficulty I've seen overall is a lack of understanding of the underlying processes. To automate a process, you have to understand it completely. People need to understand what's required and what's possible. I think more can be done on the vendor side to gain insight and knowledge of what customers need, then creating solutions and problem-solving at a deeper level. The communication could be better. [Respected consultant] James Agallaco has recently been rather vocal about this issue. It's really up to everybody to understand how far behind we are in this industry.”

In the same conference call, Lorna also spoke with Martin Rhiel of Novartis (formerly of WAG/Schering Plough and Cytos Biotechnology), who knew Professor Sonnleitner at the ETH in Zürich, Switzerland some years ago. “It was always difficult,” Rhiel reported, “to find the right sensors for your bioprocess. It's not like in other industries with everything chemically defined. If everything would work as well as a temperature probe, then of course one could use feedback controls for critical process parameters.”

Rhiel agrees that the real difficulty is a lack of profound process understanding. “Sensing does help us a lot,” he said, “but it is difficult to completely automate. Getting a reliable signal, having a reliable sensor with valid readings, that's a huge challenge. I think that's one of the reasons why we're not where we would like to be.” Because of the complex nature of bioprocesses, Rhiel says that even the best sensors currently available aren't yet reliably plug-and-play. “They're good, but not perfect yet. We use classical probes in our GMP environments, and for measuring biomass we have a sensor. This works quite well, it reliably monitors cell density, but for many other signals it can be difficult. Novartis actually started a PAT laboratory with online HPLC and other online probes about 10 years ago; it took quite a while to get reliable measurements. Luckily our company could work together in close collaboration with a Swiss vendor. With an integrated approach, we can solve a lot of problems with feedback and new testing approaches, but not yet within the GMP environment. It will be a major effort to qualify all this equipment.”

Hentschel told Lorna, “I know a lot of facilities with a very high degree of automation and control. In our newest cell culture facility (which started up in 2003), we have MES directly connected to our distributed control system (DCS). And the facility automation is directly controlled by electronic batch records. So I believe we've moved far beyond the degree of automation we had in 1997.”

Major companies have introduced automation in the form of communication between traditionally standalone devices such as blood gas analyzers and nutrient monitors. These are tied into automated sampling solutions, allowing such devices to run all day, every day without significant human intervention. The next step is tying that into bioreactors and chromatography skids to create an automated loop whereby a process is monitored continuously by a controller, which communicates its findings to technicians who can then make decisions and act upon them. That, West says, will be the next generation of automated bioprocesses.

The initial problem companies can face at that point, he admits, “is fear. Turning around and walking away from a system that's fully automated is a little bit intimidating.” Will that system perform to its promise? “There's a lot of potential to overpromise the technology,” he warns, which then fails to meet those expectations if the bar is set too high.

But are those fears grounded in reality? Or do most companies find success? West told Lorna, “Mostly they're reporting significant yield and performance improvements. Originally, the idea was that there would be cost benefits — and that was heightened with the recent economic turmoil — but the deliverable has proven to be not just the relative cost of putting someone into a more productive role doing something else.” Companies are seeing actual performance improvements, and those achievements are driving back into their systems.