Industry 4.0 Is Here. Will Pharma 4.0 Catch Up? - Virtuosi

August 23, 2021

Industry 4.0 Is Here. Will Pharma 4.0 Catch Up?

While working in a lab a number of years ago, I recalled the small pleasure of receiving an email from the centrifuge notifying me that the run was complete. The simple act of lab equipment sending status emails spoke to a broader notion of widespread digitalization, advanced communications, and other technologies that have brought us into the Fourth Industrial Revolution. In some industries like automotive, Industry 4.0 has begun to transform many areas of manufacturing, such as incorporating smart sensors for greater process integration. The pharmaceutical manufacturing industry though has been slower in adopting Industry 4.0. Drug manufacturing is still largely based on batch production, rather than continuous production, and can result in longer between-step hold times with increased degradation risk to the product. One reason for the slow adoption of Industry 4.0 is due to the critical nature of the process and the requirement for human oversight.

The aseptic fill-finish process, one of the final steps in manufacturing when the product is filled into containers and labeled, relies on automation to minimize contamination. But real-world situations require workers on the floor to troubleshoot and perform supporting tasks, such as replacing a damaged filling needle or inspecting filled vials. Another reason is due to the many tests and checks that need to be put in place when changes are applied to large operations in order to ensure that these changes do not compromise the product and that they meet regulatory requirements. Strict manufacturing regulations and the rigorousness of testing make it extremely difficult to implement technological changes, even if those changes improve the overall process. But also, any production downtime to accommodate those changes means a delay of medicines to the public and loss of profits to the company.

The Fourth Industrial Revolution

Industry 4.0, a term coined during the Hannover Messe trade fair in 2011, represents a technologically driven information and communication era focused on platforms such as IoT, smart devices, and automation, amongst others. Industry 4.0 has changed how healthcare is monitored and delivered and now drives research and innovations in personalized medicines, drug modalities, and treatment delivery methods. In order to accommodate the rapid advances in drug discovery and development and to better serve the needs of patients, pharma manufacturing needs to shift toward more integration and flexibility. Adam Fisher, associate director of communications at the FDA’s Center for Drug Evaluation and Research, works with manufacturers through an immersive program to promote the adoption of innovative approaches in pharma manufacturing and identify gaps that exist within the regulatory framework for advanced manufacturing technologies. He pointed out that “[pharma manufacturing will] be based on these digitized and interconnected systems and lead to a switch in the type of skills the workforce will need” and that “this will create new opportunities for those people with skills beyond the traditional ones.”

Any production downtime to accommodate those changes means a delay of medicines to the public and loss of profits to the company

Risk-Averse Pharma and Education 4.0

Industry 4.0 has undoubtedly transformed how education and training are delivered, shifting from one-size-fits-all, in-class learning to more tech-driven, personalized education, where students learn through different ways, using different sources and technologies. Such a shift in the delivery of education was further spurred on by stay-at-home orders due to the COVID-19 pandemic, promoting the use of virtual classrooms and augmented or virtual reality (VR) methods.

However, workers in pharma are still largely trained using traditional methods. For example, trainees for on-floor operations are trained by reading standard operating procedures (SOPs), attending company lectures or workshops, shadowing senior operators, or being sent out for training. SOPs on their own merely guide the worker, as two trainees can execute the same SOP very differently. In addition, hands-on practice for a specific procedure is usually done on equipment in virtual mode or on dedicated training equipment, if possible, and almost never on actual production equipment. These methods are inefficient because months will usually pass before workers are entrusted, and made confident and comfortable, to operate equipment or conduct a procedure on their own. Some pharma companies approach training by offering academies or schools in which trainees learn from a combination of in-class and apprenticeship methods. The Rottendorf Academy complements its in-class education with hands-on training through apprenticeships that span several years — typically up to a year for a trainee to catch up on operations and greater than three years to achieve master level. Training is highly effective based on worker retention; however, the large investment in time, infrastructure, and instructors makes it impossible to scale or adopt easily.

Investing in continuous worker education is vital for organization success, especially during our current technological era coupled with an expanding talent gap. So, it’s surprising to see how little worker training has changed in pharma over the past few decades. Granted, manufacturing is a highly risk-averse industry given that any errors or changes in the process could mean life or death, but perhaps that risk-averse mindset has seeped into other areas like workplace training. Or perhaps training methods simply are not updated, because in pharma, technological advances are not typically applied to education. The issues preventing effective and efficient training must be addressed, because in order to make progress in pharma manufacturing, we need to first make progress in worker training. Not only does the training content need to change, but also the ways in which training is taught needs to change, because this will be key to how trainees learn.

When asked how he sees worker training change, Fisher commented that advanced manufacturing technologies will create new opportunities for a different skillset such as those in data science, systems engineering, information technology, and artificial intelligence. And because the skillset will change, the training will also change. He noted, “Even in training, I think there are advanced technologies that can help. For example, you may use something like real-time augmented reality, [which] is a powerful tool in teaching and understanding the various elements of a process or even a whole facility. I think there’s a very promising thing that can come from that type of training.”

VR-based training like this can better teach students how to evaluate and create new protocols

Immersive Learning

To address the inefficiencies of worker training, several groups have developed solutions to teach trainees through interactive, mixed-reality approaches. The team at Quality Executive Partners (QxP) has created an immersive education experience, Virtuosi, with curriculums on manufacturing and microbiology that incorporate online instruction, digital coaching, and practice in VR.

Within the context of Bloom’s Taxonomy, VR-based training like this can better teach students how to evaluate and create new protocols, for example, once they’ve gathered theoretical knowledge. Bloom’s taxonomy describes the domains (cognitive, psychomotor, and affective) and hierarchical thinking that a student experiences during the learning process: firstly, to remember, understand, apply, analyze, and evaluate, and lastly, to create. Studies in health centers have demonstrated that simulated training of health professionals significantly enhanced their knowledge and their higher clinical and nontechnical skills. Additionally, the training acquired through simulations persisted in the long term. The authors recommended that the learning domains be considered when devising a simulated training program.

In another study, researchers at the Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, and the University of Copenhagen used the Labster ApS VR system to assess training efficacy on a common task employed in most pharma companies: calibrating and adjusting a pH meter. Sixty-nine trainees were divided into three groups for training either by reading the SOP, by VR, or by an in-person instructor with a pH meter. They were then randomly assigned to and assessed by an expert who had no knowledge of their training type. VR trainees scored higher when asked about their theoretical knowledge, compared to SOP trainees, and scored just as well as those trained by the instructor. More importantly, VR trainees performed tasks significantly better than those who read the SOP, as measured by the number of correctly executed tasks during pH calibration, although not as well as those trained by the instructor. In essence, VR simulations were observed to be 79% as effective as real-life training for students learning to perform pH calibrations. The authors also noted that the research participants were industry operator trainees and that their study was designed with the intent of developing a VR learning experience that could replace traditional training in pharma.

Such studies clearly demonstrate the utility in immersive training for workplace learning and development. Risk aversion may be one reason why immersive training is not widespread in pharma, but other reasons lie in the development of simulations. Craig Yu, associate professor in computer science at George Mason University, has been working on ideas to resolve some of the hurdles preventing more widespread VR training: “I think the bottleneck is really in the content creation (e.g., 3D modeling) and simulation. Think about creating a VR factory experience. The designer will need to create the realistic 3D models that mimic the equipment in the real factory counterpart. Moreover, those 3D models need to be ‘interactable’ so that the trainee can make use of those 3D models like using real factory equipment. Creating such content definitely needs a lot of manual effort and time. There’s also a lot of complexity in generating realistic simulation of the work processes too.”

Yu also pointed out that device costs and hardware limitations are the other major factors affecting easier adoption of VR training. His current work involves creating algorithms that automatically generate personalized VR training experiences in order to both reduce the manual effort and time involved in development and increase scalability. Pharma companies will not likely develop VR training in-house but, instead, will work with dedicated VR training experts to create the appropriate simulation for their workers. “VR training is definitely scalable for a large group,” said Yu. “You can let an unlimited [number] of workers go through a VR training module as long as they have access to VR devices. Another advantage is that people can download such VR training modules any place, any time, given they have the proper network access. VR training is definitely more scalable than traditional training that requires a real coach to conduct the training in situ.”

Mixed reality–based training has already been implemented in a number of institutions for purposes such as emergency response planning and training of public health units. The New York City Office of Emergency Management uses a virtual replica of New York City to train and prepare staff under different simulated scenarios, allowing them to practice under a controlled environment. The high-risk operations in pharma manufacturing would greatly benefit from this type of VR-based practice. It is highly amenable to unlimited practice, which is especially important because real-life practice on the production floor is usually not feasible. The immersive experience allows students of all ages, learning styles, and abilities to learn more effectively. With the increasing costs of drug development and changes in technology, pharma cannot afford to not improve worker education.

Future of Pharma Training

Around two-thirds of drug shortages are attributed to failed quality tests, which represents one of the biggest challenges in pharma manufacturing. To various degrees, government, academia, and industry are all putting together efforts for improving manufacturing via advanced tech, but worker training should be a top priority. As Brian Duncan, chief operating officer of QxP, commented, “Under the existing paradigms, system-level or foundational concept understanding is a major weakness. What happens when we migrate to technologies that require rapid adaption of processes which are heavily reliant on older technologies? How do we shift efficiently to new platforms? [This migration] places an even greater premium on concept-level understanding as well as the ‘why’ behind actions.”

Workers who fully understand how and why processes are conducted in a specific fashion are especially necessary now with the increasing number of novel drug modalities and a push toward more effective, personalized medicine. These workers are better equipped to recognize and provide the appropriate response to unexpected deviations. A deep understanding by all operators of the production process is crucial to successfully manufacture nontraditional drugs — in particular, cell and gene therapies. As researchers continue to develop new ways to produce these therapies, such as incorporating more automation during CAR-T cell manufacture, they currently still require extensive human handling. “This is creating a ‘war for talent’ within pharma today,” noted Duncan. “There aren’t enough workers with hands-on experience and, more importantly, a strong understanding of the science behind manufacturing advanced medicines. This is becoming a greater issue than manufacturing capacity currently.”


All views, research, and opinions are those of the Dr. Jen Huen, Ph.D.

This article was commissioned by Quality Executive Partners, Inc.


  1. Sjödin DR, Parida V, Leksell M, Petrovic A. “Smart Factory Implementation and Process Innovation.” Research Technology Management. 2018;61(5):22–31. doi:10.1080/08956308.2018.1471277
  2. Smart Manufacturing Market to Enlarge Vigorously; Launch of Subscription-based Smart Manufacturing Solutions by SK Telecom to Enable Speedy Expansion, states Fortune Business Insights.
  3. Kalsoom T, Ramzan N, Ahmed S, et al. “Advances in Sensor Technologies in the Era of Smart Factory and Industry 4.0.” Sensors (Basel). 2020;20(23):6783. doi:10.3390/s20236783.
  4. Arden NS, Fisher AC, Tyner K, et al. “Industry 4.0 for Pharmaceutical Manufacturing: Preparing for the Smart Factories of the Future.” International Journal of Pharmaceutics. 2021;602:120554. doi:10.1016/j.ijpharm.2021.120554.
  5. “Modernizing the Way Drugs Are Made: A Transition to Continuous Manufacturing.” Click here for reference
  6. CRB. “The Current State of Aseptic Processing & Fill-finish Manufacturing.” Click here for reference
  7. Mirasol F. “Automation Trend in Fill/Finish Reduces Contamination Risk.” BioPharm International. 2018;31(6):12–13.
  8. Pfeiffer S. “The Vision of ‘Industrie 4.0’ in the Making — A Case of Future Told, Tamed, and Traded.” Nanoethics. 2017;11(1):107–121. doi:10.1007/s11569-016-0280-3.
  9. Paul S, Riffat M, Yasir A, et al. “Industry 4.0 Applications for Medical/Healthcare Services.” Journal of Sensor and Actuator Networks. 2021;10(3):43.
  10. Paul D, Sanap G, Shenoy S, et al. “Artificial Intelligence in Drug Discovery and Development.” Drug Discovery Today. 2021;26(1):80–93. doi:10.1016/j.drudis.2020.10.010.
  11. Kapoor Y, Meyer RF, Meyer BK, et al. “Flexible Manufacturing: The Future State of Drug Product Development and Commercialization in the Pharmaceutical Industry.” Journal of Pharmaceutical Innovation. 2021;16(1):2–10. doi:10.1007/s12247-019-09426-z.
  12. Rogers S. “Coronavirus Has Made WFH the New Normal. Here’s How Virtual Reality Can Help.” Forbes. Click here for reference
  13. Haines G, Spreen M. “Why Training Matters.” Pharmaceutical Technology. 2015;39(12). Click here for reference
  14. Dukart HP, Patel P, Telpis V, et al. “Pharma Operations: Creating the Workforce of the Future.” McKinsey and Company blog. Click here for reference
  15. Adams NE. “Bloom’s Taxonomy of Cognitive Learning Objectives.” Journal of the Medical Library Association. 2015;103(3):152–153. doi:10.3163/1536-5050.103.3.010.
  16. Anderson L, Krathwohl D, Airasian P, et al. A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom’s Taxonomy of Educational Objectives. 2001.
  17. Konia M, Yao A. “Simulation — A New Educational Paradigm?” Journal of Biomedical Research. 2013;27(2):75–80. doi:10.7555/JBR.27.20120107.
  18. Wismer P, Lopez Cordoba A, Baceviciute S, et al. “Immersive Virtual Reality as a Competitive Training Strategy for the Biopharma Industry.” Nature Biotechnology. 2021;39(1):116–119. doi:10.1038/s41587-020-00784-5.
  19. National Academies of Sciences, Engineering, and Medicine; Health and Medicine Division; Board on Health Sciences Policy; Forum on Regenerative Medicine. “Navigating the Manufacturing Process and Ensuring the Quality of Regenerative Medicine Therapies: Proceedings of a Workshop.” Washington (DC): National Academies Press (US); 2017 Oct 26. doi:10.17226/24913.
  20. Hsu EB, Li Y, Bayram JD, et al. “State of Virtual Reality Based Disaster Preparedness and Response Training.” PLOS Currents. doi:10.1371/currents.dis.1ea2b2e71237d5337fa53982a38b2aff.
  21. Virtual Reality Laboratory Training. Click here for reference
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