Automating Aseptic Manufacturing

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An ongoing engineering challenge for aseptic drug manufacturing is to reduce the risk of contamination as much as possible. As it is well known that human operators are the biggest source of contamination in a cleanroom, a growing consensus is that automated systems that eliminate human intervention are the future of aseptic processing. Pharmaceutical industry experts point to the successful use of both conventional and robotic automation in other industries, such as semiconductor manufacturing and aseptic food processing, as well as in pharmaceutical packaging and warehousing, as a sign that the pharma industry should overcome its reluctance to change. This shift has begun in fill/finish processes and is moving further upstream into other aseptic manufacturing steps. Robotic technology, in particular, is finding use in drug compounding (1) and in closed, gloveless isolators.

Advances in robotics

While conventional automation is suited for larger volume operations with simple motion and few changes, robotic automation technology designed for cleanrooms offers the ability to perform different types of operations and handle multiple formats, such as vials and syringes. Robots, which can perform the repetitive tasks otherwise handled by human operators, enable the move to closed systems that can operate without human intervention.

“Over the past 30 years, the equipment evolution has been from open and manual, [to] isolated and manual, then isolated and automated, and [now] closed and automated. In the next 5–10 years, more robotic solutions will come into the pharma production world throughout all segments, driven by new regulations, more personalized medicine, and more flexible machines,” predicts Rudolf Michael Weiss, global head of pharma robotics at Stäubli Robotics.

Regulatory authorities have expressed support for automation technologies as a means to limit aseptic interventions, notes Laura Moody, North American product manager at machine builder Syntegon Pharma Technology, pointing to as far back as FDA’s 2004 aseptic processing guidance (2) and to recent conferences. “Even as recently as the 2021 International Society for Pharmaceutical Engineering Aseptic Conference, the reduction in risk to the drug product through the use of automation and robotics was reiterated by FDA representatives,” says Moody. She says that acceptance by regulatory authorities and pharmaceutical manufacturers is helping drive innovations in robotics.

Operating multiple-product filling lines in accordance with the European Union’s draft Annex 1 (3) can be achieved with various technologies. One method is to use restricted access barrier systems (RABS) with fully automated, hydrogen peroxide decontamination of the entire cleanroom prior to each batch, says Arno Schroff, director of site and plant development at contract development and manufacturing organization, Vetter. Closed isolators are another increasingly important solution. “Our long-term vision is shifting from a human-centered production towards a fully automatic process with robotic equipment to further reduce possible risk to the product,” he notes.

“The biggest news from the past year is that FDA and Health Canada have approved commercial products made using gloveless robotic isolators. Several of our customers have achieved this milestone,” says John Harmer, head of sales and marketing, aseptic filling, at Cytiva, which acquired Vanrx, a manufacturer of robotic aseptic filling machines, in February 2021. “The industry has moved beyond ‘Will they work?’ to ‘Where else can we use them?’. Our prediction is that robotics will play an increasing role in manufacturing personalized medicines including mRNA, peptides, bacteriophages, CRISPR-Cas9, and other genomic therapies.”

Reducing contamination

Compared to conventional RABS or isolator-based filling systems, gloveless robotic isolators eliminate human intervention. “The sources of interventions have to be designed out and built around the capabilities of robotics,” says Harmer. “Because these systems are standardized, they can cut a year off the typical process of building filling capacity. Robotics handle vials, syringes, and cartridges the same way within presterilized tubs, so flexibility is built in for the small-volume, high-value drugs that currently fill biopharmaceutical pipelines.”

Syntegon’s new robotic fill/finish system, the Versynta FFP [Flexible Filling Platform], was introduced in mid-2021 and is designed for small batches of up to 3600 containers (vials, syringes, or cartridges) per hour. The company’s microBatch system, currently in development with Vetter, is an automated production cell with a gloveless isolator designed for even smaller batches of 120–500 containers per hour, says Moody. She notes that this system is currently in the detailed design phase and is expected to be launched in 2022.

Both solutions use robotics: while Versynta FFP uses a four-axis robot, developed by Syntegon, to transfer containers from one station to the next without glass-to-glass contact, Versynta microBatch is a fully automated production cell. It is designed for flexibility in the types of containers and closures that can be processed. “It allows for the container and closure of a drug product to be dictated by the needs of the drug and usage of the patient, not the limitations of the fill/finish machine,” comments Moody.

The gloveless isolator also eliminates the need for glove testing and glove management; features integrating air management, so that the isolator does not need a technical ceiling or interfaces to the building; and the design is standardized to allow quick delivery and validation, notes Moody.

Schroff adds that an automated de-bagging system for presterilized packaging components eliminates human intervention to prevent contamination of materials entering the isolator. Automated line set-up, monitoring, and fill-weigh checks for process control are other benefits, he notes.

The flexibility and rapid changeover required for fill/finish of small-batch parenteral drug products is better met by robotics than by traditional automation, agrees Joe Hoff, CEO of robotics manufacturer AST. Efficient cleaning, reliable sterilization, and high overall equipment effectiveness are other drivers for growth in demand of these systems, he adds. “The biggest challenges engineers face when designing isolated fill lines are fitting the design into a small, enclosed space; achieving good operator ergonomics; and ensuring all systems and penetrations are leak-tight and properly designed for cleanability and [hydrogen peroxide] sterilization,” says Hoff.

Although some may still hold the misconception that robotics can’t be used in cleanrooms because moving parts may generate non-viable particulates, this concern has already been resolved, suppliers say. Robotic suppliers point out that robots for pharmaceutical cleanrooms have a hygienic design for low particulate generation and resistance to standard cleaning chemicals. They can also be designed to be resistant to hydrogen peroxide so they can withstand frequent decontamination.

Another aspect of design is planning for changing parts and performing maintenance. Xavier Gómez Garcia, lyophilization portfolio manager at pharma equipment and engineering supplier Telstar, points out that haptic interfaces allow users to remotely manipulate a robot. “Some of these devices allow the user to also feel the weight of the real object, even without physically touching it. The precision is extremely high. [Systems could have a] built-in feature to change format parts and do basic maintenance through telematic [remotely operated] haptic devices, without the need of glove ports or operators near the process zone,” suggests Garcia.

Software for improving robotic motion continues to be improved. “The robot is embedded into the [information technology (IT)] structure of the machine, and new software features like tele-manipulation, remote joystick fault intervention, and [motion controls such as] anti-sloshing movements, for example, need to be developed,” says Weiss. He notes that Stäubli is currently developing specific pharma software features suited to robotics inside isolators.

Increasing predictability

In addition to lowering the risk of contamination, robots increase predictability. Compared to robots, humans can have difficulty being consistent with repetitive tasks requiring precision and accuracy, suggests Toni Manzano, cofounder and CSO of Aizon, a pharma/biopharma software as a service provider and co-chair of the Parenteral Drug Association’s first Robotics and Automation conference held in April 2021.

While people need to be trained and periodically retrained—and it can be challenging to duplicate a process in multiple locations—robots are trained once and have the same precision no matter what the time, day, or location, adds Martin Düblin, managing director of consultancy One One Eleven GmbH and co-chair of the PDA conference with Manzano. High levels of standardization across multiple facilities simplifies operation and inspection.

Another benefit of robotics is easier qualification, says Alex Armengol, international senior sales director for SP i-Dositecno fill-finish products and SP Industries’ global leadership team member. He explains that a performance qualification protocol tests whether the aseptic manufacturing procedures are adequate to prevent contamination during actual drug production—via process simulations or media fills using a sterile microbiological growth medium—and replicate organism detection and counting (RODAC) surface-contact testing. Robots will require less RODAC testing because of their controlled movement. “The behavior and movement of personnel is difficult to control. Everyone behaves differently and often randomly,” explains Armengol. “The methodical and controlled movement of robots within the aseptic processing area are key to providing a predictable quality environment. [In addition,] one robot can typically cover many critical areas within the aseptic processing space.”

PAT and AI in pharmaceutical automation

IT systems are increasingly intertwined with operational technology systems in modern manufacturing systems; control signals are sent to the machine, and the machine sends data to higher-level systems, such as supervisory control and data acquisition systems. In addition to machine data, data from process analytical technology (PAT) tools, used in automated systems, can improve quality and efficiency. In-process control (IPC) check-weighing in an automated filling system is one example, notes Armengol. Conventionally, check-weighing was a destructive test, but using the PAT tool of IPC, each container is weighed and no product is lost. “In this method, [empty] containers are placed on an in-process balance or load system, and the exact amount of product is dispensed and checked against the specification. Over a period of time, if the controller senses any changes to the fill weight, the system will adjust the pump appropriately,” he explains. Additionally, artificial intelligence (AI) algorithms can use data to predict machine behavior and potential failure points, adds Armengol. AI can identify process deviations, and decisions can be made in real time to reject or accept products.

These data can also be used by process experts. For example, Harmer says, “If the filling system contributes to a consistent stream of data about a customer’s manufacturing process, we have better evidence to optimize processes or improve drug product quality.”

Today’s machines are highly integrated into IT systems for sharing data such as batch records or for allowing remote viewing of machine performance or remote maintenance, but machines in the future will advance into intelligent feedback and even predictive maintenance, suggests Hoff.

Using AI in “smart” systems, set up to make decisions based on input from the process and algorithms derived from process knowledge, will increasingly play a role in automation systems.

“Smart systems, understood as the interaction between machines and AI, are able to repeat tasks consistently and, if they are well trained, make the right decisions in a systematic way,” explains Manzano.

A concern about how regulatory authorities will accept critical decisions being made by automated systems rather than human operators is creating hesitancy in pharma manufacturing. Other regulated industries, as diverse as banking and food manufacturing, have adopted fully automated mechanisms managed by AI, notes Manzano. One example of AI being adopted in pharma manufacturing is smart systems for feeding raw materials. He says that questions such as: “How do I proceed if a lot of raw material is finished in the middle of the mixing operation? Can I add a lot of the same substance from another supplier?” are examples of unusual situation that can be properly managed by AI connected to an automated system.

Handling of these types of questions would need to be validated, adds Düblin, who notes that a lack of experience by regulatory authorities is currently a limitation. Internal company inspectors also need to gain experience and confidence in smart systems.

Another area that has been tested and found to be successful is automated inspection of pharmaceutical finished products, managed by AI.

“AI has demonstrated a high value and a consistent response in complex tasks, including defect identification, deviation detection, multivariable control, and chained actions based on different scenarios, for example,” says Manzano. Good data that are digital and not managed in silos, but rather collected via the Internet of Things and managed via cloud technologies, are crucial for accurate AI results, he cautions.

“The way forward is to consider the whole process; digitalization yields the data needed to train robots or automated systems,” agrees Düblin.

Training

Training is an essential aspect of good manufacturing practices (GMP) in the pharmaceutical industry. “Training and retraining are one of the foundational core activities that regulatory agencies often review during inspections to ensure that ongoing training is provided to key personnel so that they can demonstrate process knowledge and their ability to adhere to routine standard operating procedures,” notes Armengol. Control systems for robotics are complex systems, and training is crucial for operating and maintaining these systems. “Automation and control are key to successful implementation of robotics, including the understanding of the mechanics and electronics involved in making the robots function as intended,” says Armengol. “Key to the training is the interface between the machine and the operator, known as the human machine interface or graphical user interface.”

Armengol suggests that hands-on training is critical for these systems. SP i-Dositecno is currently installing a modular robotic filling line and isolation system at the National Institute for Bioprocessing Research and Training (NIBRT) in Dublin, Ireland, which will be used in NIBRT’s aseptic biopharmaceutical fill/finish training.

Harmer points out that for automated systems, operators do not need to be trained in aseptic technique, as they do in conventional systems. Instead, training focuses on the workcell’s integration of robotics and the closed isolator. “In Cytiva’s training, users learn how the aseptic process automation works, how to create recipe-driven processes for specific drug products, and how the machine controls risk at each stage of the aseptic filling process,” he explains.

He adds that standardization of gloveless isolators means that improvements developed by one user can be made available for other users. “Cytiva’s aseptic filling business has an active user group that collaborates on training, regulatory strategies, and environmental monitoring approaches. This group suggests design and software improvements, which can be implemented during preventative maintenance of the filling machine,” he explains.

Barriers to automation

Despite the benefits of automation and the inevitable use of automation in facilities of the future, there are multiple barriers to upgrading existing facilities with new, automated lines, including the need to revalidate and the initial investment cost. Armengol notes that for small- and some medium-size companies, this cost barrier may be difficult to overcome.

Although industries such as semiconductors had a strong business case to automate because of their narrow profit margins, biopharma, with its higher profit margins, has less incentive to change, suggests Manzano. On the other hand, says Düblin, recalls and batch losses are costly, so a business case for automation can be made.

“Roadblocks to modernizing a fill/finish cleanroom are regulatory, cost, capacity, and time,” agrees Hoff. “Unless a facility has an unused or available fill suite they can expand into while maintaining their existing fill suite, it is unlikely they have the time or capacity to shut down a validated and qualified process to modernize.”

In addition, the design of existing facilities and equipment may not be conducive to automation. “Retrofitting within an existing machine is usually difficult due to the lack of space and freedom of movement for the robot,” notes Moody. One option is to automate the secondary processes, such as the supply of packaging materials, around the existing machine, she suggests.

Autonomous mobile robots and automatic guided vehicles for transporting materials are an example of automation that can be applied to existing processes, agrees Weiss.

Another challenge is the reluctance to replace humans with robots. The lockdown restrictions of the COVID-19 pandemic that created worker shortages have made the consistent availability of robots more appealing, but the concept of this change in work still creates hesitancy. Although it is true that implementing automation will eliminate certain types of jobs, it will create some others that need different skills, says Düblin. Not wanting to change operators’ jobs shouldn’t override the benefits brought by digitalization and automation. “It is the responsibility of enterprises to adapt,” he asserts.

Ongoing implementation ahead

Despite some barriers to use, the advantages of and continued improvement in robotic automation will drive continued implementation in aseptic processing, experts agree.

“To date, the strength of robots is primarily in performing repetitive tasks, and [robots] have so far been less suitable for constantly changing ones. But a lot is happening in this area right now,” says Moody. “The limits will continue to shift due to new technologies such as AI and reduced costs for robotic solutions. Going forward, we will be able to equip all areas needed for the operation of a filling machine with robotics. Examples of future robot applications include upgrading the filling path or inserting and changing sediment plates for microbiological monitoring.”

“Robots will become mainstream [in pharma manufacturing] within the next few years because of enhanced flexibility, repeatability, and precision,” adds Armengol.

Garcia suggests that the pending publication of Annex I is driving demand for plant retrofits. “New regulations are clearly accelerating the change in the pharmaceutical industry, encouraging both drug companies and equipment manufacturers to embrace new technologies that can minimize the risk of contamination for the final product. Annex I is pushing the industry towards automatization, [particularly] in critical processing zones, including all the operations in primary packaging, filling, and capping, [which generally have] freeze dryers in between,” says Garcia. He notes that new, automated loading and unloading modules for freeze dryers and autonomous filling and capping stations that incorporate PAT tools are being used.

“In the past 25 years, primary packaging lines have evolved from dozens of manual operations, typically through glove ports, to fully automated lines. Until now, automation has been quite rigid to fulfill high production volumes in centralized manufacturing plants,” notes Garcia. The growing need for sterile manufacturing of smaller batches, however, is driving growth of more flexible robotic automation. “In my opinion, companies with centralized factories will work together with new and flexible plants where GMP robots will play a crucial role. Local manufacturing hubs with an agile supply chain will be a vital asset,” he predicts.

References

1. J. Markarian, Pharm. Tech. 45 (6) 26–28 (2021).

2. FDA, Sterile Drug Products Produced by Aseptic Processing–Current Good Manufacturing Practice Guidance for Industry (2004).

3. EC, Draft Revision to Annex 1, Manufacture of Sterile Medicinal Products (2020). 

About the author

Jennifer Markarian is manufacturing editor of Pharmaceutical Technology.

Article details

Pharmaceutical Technology
Vol. 45, No. 10
October 2021
Pages: 16–21

Citation

When referring to this article, please cite it as J. Markarian, “Automating Aseptic Manufacturing,” Pharmaceutical Technology 45 (10) 2021.