By Gareth John Macdonald
Bioprocessing 4.0 is a reality. It is part of a broader movement known as Industry 4.0, which is, essentially, the fourth industrial revolution. The idea of the fourth industrial revolution was introduced about 10 years ago, when German researchers suggested that manufacturing should exploit cyber-physical systems.1 Soon, the idea was popularized by World Economic Forum leaders who emphasized that cyber-physical systems were blurring the lines between the physical, digital, and biological spheres.2
In the years since, many industries, including the automotive and electronics industries, have been moving decisively toward Industry 4.0. However, the biopharma industry has lagged behind.
In an article that appeared in 2020, researchers at Sartorius explained that in the biopharma industry, unlike many other industries, processes are “not binary and generally involve complex living cells where variability is high making measurements and predictions of bioprocess performance challenging.” They added that the biopharma industry is “also heavily regulated, with special constraints around contamination and safety.”3
The following year, another group of Sartorius researchers sounded more optimistic. They maintained that biopharma companies could approach Bioprocessing 4.0 one step at a time. They stated, “Adopting available automation and real-time monitoring systems enabled by process analytical technology from suppliers with a global network, deep process knowledge, and understanding of pain points can facilitate the transition toward Bioprocessing 4.0.”4
Today, technologies to enable Bioprocessing 4.0 are being developed by multiple companies. Also, several large biomanufacturers are starting to realize Bioprocessing 4.0 visions. The technology provider’s perspective and the biomanufacturer’s perspective are both represented in this article. For the former, we consulted with Cytiva. For the latter, we consulted with Lonza and Pfizer.
An ongoing process
“Pfizer as an organization initiated a transformation in 2019 to become more agile and science driven,” says Mike Tomasco, vice president of digital manufacturing, Pfizer. “Our manufacturing organization had already begun some of that work years before, making key investments in both foundational and innovative technologies to upscale our digital capabilities.”
He stresses that the COVID-19 pandemic underlined the need for operational flexibility and increased drug industry use of innovative, connected bioprocessing systems: “It accelerated the need for more digital solutions to aid in running hybrid operations—essential works in the plant and nonessential works externally. The necessity that the pandemic brought to the operations created a new level of demand for ongoing capabilities.”
Pfizer’s manufacturing plant network comprises 36 internal facilities supporting the production of over 50 billion doses of medicine annually. Ten of its plants are dedicated to biotechnology manufacturing. In such a large network, it can be hard to determine which plants, manufacturing lines, and unit operations would benefit the most from digitalization.
Setting priorities can be easier if manufacturers apply a framework that Biophorum, an industry group, developed with input from several companies, including Pfizer. “One of the ways we measure our level of maturity for each site is through the BioPhorum Digital Plant Maturity Model (DPMM),” Tomasco relates. “It is a standards-based model that defines the stages of maturity for biopharma manufacturing processes as follows: Level 1: paper; Level 2: digital silo; Level 3: connected; Level 4: predictive; and Level 5: adaptive.”
More recently, Pfizer launched its Predictive Plant Acceleration program to bring operations to Level 4 on average. According to Tomasco, “Some operations are intended to reach Level 5, and some will purposefully reach Level 3.”
Faster production, lower costs
Pfizer’s belief in the value of digital manufacturing and supply operations reflects the benefits the firm has already achieved. “We have seen direct and indirect benefits that are measured both quantitatively—using key performance indicators with targets set at the plant level measured monthly—and qualitatively,” Tomasco details. “One of the clearest benefits is manufacturing cycle time improvement, which means we’re able to produce and quality check more medicines at faster rates, enabling us to get medicines to patients faster than before. Other direct benefits include cost savings, the creation of efficiencies, manufacturing throughput and yield improvements, reduction of human error, and energy optimization.”
The transition to digital manufacturing and supply operations was enabled by a new approach to information technology, which is a benefit in itself. Prior to its digital transformation, Pfizer used a “waterfall” model in which information technology systems were tested through a defined series of project phases—a series in which each phase had to be completed before the next could begin.
“Once we recognized that this was holding back our ability to innovate and deliver new capabilities to our manufacturing customers, we worked to rewrite the procedures to enable agile work practices as the standard instead of as an exception,” Tomasco recalls. “This changed the game completely.” The new procedures enabled Pfizer to develop and iterate solutions more quickly while maintaining GMP compliance.”
In addition to improving operations, the adoption of digital bioprocessing technology has created new opportunities for employees. However, these opportunities are not realized without effort. “The biggest challenge to date with our digital transformation is the need to implement change management at all levels of the organization,” Tomasco explains. “We are asking people to change how they work and collaborate with each other. We are transforming into a data-driven organization, which means that we need our operators and managers to trust what the data is telling them to do.”
The digitalization process has even impacted Pfizer’s approach to staff training. “We’ve been able to upskill resources in new ways and to achieve job competency more quickly without disrupting manufacturing operations,” Tomasco says. “Also, having a modern shop floor or laboratory experience helps to streamline decision making processes, leading to higher job satisfaction.”
“A digital transformation requires that you consistently look at the way you’re doing things and whether it will enable you to achieve what you’re after,” he concludes. “This is not always easy, but I think of it more as an opportunity versus a challenge.”
By facilitating upskilling, digitalized bioprocessing can help biopharma firms avoid a common struggle: attracting staff that already have whatever new skills are needed. But there are exceptions. For example, biopharma firms will have to attract staff that have digitalization skills.
“We surveyed 1,250 pharma and biopharma executives and found that it is becoming more challenging to secure the talent needed to adopt and advance digital and automaton strategies,” reports Mark Demesmaeker, PhD, head of digital product portfolio, Cytiva. “Organizations such as the National Institute of Bioprocessing Research and Training (NIBRT) are helping to bridge the gap between higher education and the specific skills needed for biopharma manufacturing.”
Cytiva sees digitization as a multistage process. “Customers realize that becoming more digitally mature on the route to Bioprocessing 4.0 is a journey that requires several years,” Demesmaeker elaborates. “We work with them to identify the areas where they stand to gain the most benefits in the shortest time.
“For emerging biotechnology companies, deploying mechanistic modeling to gain design confidence and ‘get it right the first time’ is most important. Conversely, contract development and manufacturing organizations seem most interested in data enablement—the automatic electronic capture of process, raw material, and machine data for conversion into knowledge.”
Representatives of contract development and manufacturing organizations can be expected to believe that Bioprocessing 4.0 is about building knowledge. One such representative is Lars Hermann, PhD, director of digital information science, Lonza. “We consider digital manufacturing technologies a key enabler to enhancing our manufacturing processes,” he says. “By harnessing state-of-the-art manufacturing execution systems in conjunction with electronic batch records and the industrial internet of things, we’ve been able to better contextualize our process data end to end.”
Lonza has focused on investing in “foundational technologies” such as manufacturing execution systems, advanced scheduling systems, integration-platform-as-a-service systems, and robust data engineering. The principles underpinning all these projects are quality and adaptability.
“Whether in our newest facilities designed with adaptability in mind, or through selectively retrofitting existing ones, digital manufacturing technologies help us increase agility, minimize production and release times, and make our processes more resilient and quality assured,” Hermann asserts. “For example, we are now able to substitute and complement wet work during process development with hybrid modeling to accelerate scale-up and reduce development time and waste.”
Technology transfer—the act of moving a production process from a customer’s development laboratory or pilot plant to a commercial production site—is another area where digital technology has helped Lonza. “Of particular importance to us are inbound technology transfers, which can be streamlined significantly through digital solutions,” Hermann notes. “For example, mutually agreed upon taxonomies and the strategic utilization of process information management systems and data exchange platforms help to accelerate knowledge transfer.
“Following transfers, the expectation often shifts toward granting customers near-real-time access to the underlying process data during manufacturing, at a granularity and scope required to satisfy their needs for things like continued process verification. These demands necessitate significant investments in our digital infrastructure and capabilities. This commitment not only enables us to gain a competitive edge, but also improves our capacity to attract and retain customers, building on our strong customer base.”
Hermann is enthusiastic about digitalization’s advantages, but he is also frank about its challenges. “In our manufacturing processes, the integration and application of digital technologies, such as artificial intelligence (AI), undoubtedly present some challenges,” Hermann admits. “AI algorithms and other advanced digital tools must be validated for use in GMP, and the models must be interpretable to comply with stringent regulations, particularly with regard to data integrity and quality.
“The use of cloud platforms with support from third parties may raise challenges around data security. The large data volumes generated by the industrial internet of things raise questions around retention policies and data integrity. Validation is another area where open questions remain, especially as AI models become more sophisticated.”
Additionally, retrofitting older plants is complex. “It may require significant investments in both time and capital,” Hermann says, “and it may introduce risks related to compatibility, security, and efficiency.”
Hermann also emphasizes the importance of keeping up with advances in technology: “The rapidly evolving landscape of digital technologies necessitates continuous learning and adaptation. Ensuring that our team is well trained and capable of leveraging these new tools effectively is essential.”
“We firmly believe that biopharma manufacturing will witness a paradigm shift toward more data-driven and software-defined systems,” Lonza’s Lars Hermann predicts. “This involves the implementation of sophisticated modularization and abstraction patterns that can manage escalating complexity while retaining flexibility—a trend currently being observed across the software industry.”
A similar outlook is held by Pfizer’s Mike Tomasco. “Digital technology is already changing manufacturing,” he declares. “The pace of deployment continues to accelerate, with ever-increasing data availability, advances in computing power and unprecedented growth of AI capability.”
The digitalization of biopharma is also seen as inevitable by Cytiva’s Mark Demesmaeker. “The biopharma industry,” he says, “must embrace digital solutions to enable fast, flexible, and reliable bioprocess development toward discovering and delivering future therapeutics.” He adds that digital solutions may encourage biopharma companies to expect conveniences of the kind associated with consumer products: “Today, you can forecast your pizza’s completion time on an app in real-time, but our customers cannot yet know the success of their therapeutic manufacturing batch for days or weeks after it finishes.”
- Kagermann H, Wahlster W, Helbig J. Securing the Future of German Manufacturing Industry: Recommendations for Implementing the Strategic Initiative INDUSTRIE 4.0. 2013. Final Report of the INDUSTRIE 4.0 Working Group. Acatech—National Academy of Science and Engineering. Published April 2013.
- Schwab K. The Fourth Industrial Revolution: What it means, how to respond. World Economic Forum. Published January 14, 2016.
- Demesmaeker M, Kopec D, Arsénio AM. Bioprocessing 4.0—Where Are We with Smart Manufacturing in 2020? Pharmaceutical Outsourcing. Published: September 8, 2020.
- Kumar G, Koch M, Arsénio A, Wagner J. Simplifying the Bioprocessing 4.0 Journey. Bioprocess International. Published September 30, 2021.