Skipping Steps to BioPharma 4.0

Image courtesy of National Institute for Bioprocessing Research and Training (NIBRT)

Over the past few years, the “4.0” suffix has become widely used (and, some might argue, hyped) in the pharmaceutical industry and beyond. Reflecting the extension of “Manufacturing 4.0” principles to biopharm, Biopharma 4.0 (1) centers around the use of sensors, process analytics, and real-time data. This approach allows integrated networks comprising the Industrial Internet of Things (IIOT) to capture, store, and analyze information from separate sources, and present it in optimal form. The result is improved cross-functional collaboration, predictive maintenance, and efficiency.

The operating systems required already exist. Combined with use of cloud computing, artificial intelligence, and technologies such as virtual and augmented reality, the principles behind BioPharma 4.0 are expected to decrease scale-up costs and timelines, improve manufacturing efficiency and quality control, and allow more effective models to be built for predictive maintenance and training.

Some manufacturers are piloting 4.0 approaches that are already yielding benefits for both small-molecule and biopharmaceutical operations (2,3). Others are still grappling with “3.0” or even “2.0” challenges and integrating the digital silos and islands of automation that remain within their operations.

For the biopharmaceutical industry, whose processes are more complex than those for most small-molecule drugs, adopting Biopharma 4.0 principles can help manufacturers address “formidable” challenges, says Mark

Demesmaeker, head of data analytics at Sartorius Stedim Biotech. In 2020, Demesmaeker notes, biologics will account for more than 25% of the pharmaceutical market, at a time when smaller volumes, higher product turnover, demands for lower cost of goods sold (COGS), improved product quality, and reduced time to market or clinic have become the norm. Factoring in the specialized requirements for personalized medicines, such as gene and cell therapies, and the introduction of more biosimilars, he says, and a more data- and analytics-driven approach is fast becoming “a cornerstone for future success” in biopharma development and manufacturing.

While investing in better automation and analytics, manufacturers can take advantage of modular, pre-validated, and pre-tested single-use equipment, bioreactors, and chromatography systems that include built in electronic batch record (EBR) and manufacturing execution system (MES) functionality. They can also utilize off-the-shelf modeling programs and improvements in single-use equipment automation.

Partnerships or acquisitions involving equipment vendors and process-control and software suppliers are helping to drive change. Today, all process-equipment vendors have allied with leading automation and control companies. For instance, Cytiva (formerly GE Healthcare Life Sciences) has connected its FlexFactory single-use platform to a Figurate distributed control system (DCS) since 2015. The company has formed partnerships with Rockwell, Emerson, and Siemens to bring plug-and-play automation to ppstream bioreactors and downstream chromatography scaleup for companies that might not be able to invest in foundational MES or EBR software on an enterprise level.

Recently, some of the greatest advancements have been made in automation for single-use technology, says Kevin Seaver, executive general manager of Cytiva’s automation and digital division. He recalls the early days of single-use equipment development at Xcellerex and working with sensor vendors and tubing welders on solutions. Today, the company can provide Figurate products that have already been tested and validated, to allow systems to work better together, enabling shorter implementation time for customers, he adds. “We have made sure that Figurate products are connected to platforms such as Rockwell PlantPAx, Emerson’s Delta V and Siemens PCS7,” says Joe Makowiecki, enterprise solutions director of business development at Cytiva. “Using automated FlexFactory approaches allows users to incorporate EBR or scheduling software. This reduces cost, provides an audit trail and releases batches faster. It also lets them use not only manufacturing but materials data,” he adds.

Another important change has been the move to different types of modeling, which has become vendor agnostic. “This process is become more ‘off the shelf’ with the goal of making it easier for end users to scale up without having to run extensive designs of experiments,” says Seaver.

In this same spirit, Sartorius introduced the third generation of its BIOSTAT STR single-use bioreactor, which runs the new Biobrain automation platform, designed to enable quick and easy system configuration. The system features integrated and redundant single-use sensors that provide real-time data to measure and control critical process parameters such as pH, dissolved oxygen, viable biomass, glucose, lactate, and foam.

“Non-invasive measurements save set-up time, prevent interface issues and reduce the need for off-line manual sampling to enhance batch-to-batch consistency,” says global consultant Kevin McHugh. Users can incorporate feed controls, bleed controls, and connectivity to Repligen’s XCell ATF cell-retention devices to increase cell density and productivity, he says. Connection to Umetrics SIMCA, meanwhile, allows them to harness multivariate modeling and control, enabling them to predict yield and optimal harvest time points at the early stages of the perfusion process. The system can be directly integrated locally via a control tower or with a data historian, or more broadly via DCS platforms from Emerson, Siemens, or Rockwell.

As they explore off-the-shelf solutions, more companies are also investing in improved analytics and process control and investigating more of the building blocks of Biopharma 4.0. In scale-up, process intensification is driving the use of more advanced analytics. “About 30% of new molecules moving into clinical manufacturing will be implementing intensified processing in upstream or downstream operations,” says Andrew Bulpin, head of process solutions at MilliporeSigma. As a result, most companies realize that they need to upgrade their process analytics and automation. “Today’s processes already produce in excess of 1 billion data points per run, and with the adoption of intensified processing technologies with advanced sensor technologies and enhanced data capture capabilities, the volume of data and information gathered per batch is exploding,” Bulpin notes. Advanced analytical tools are required to ingest, normalize, analyze, and enable decision making at high volume and speed, he says.

Applying Biopharma 4.0 concepts

Currently, every key industry organization, from the International Society for Pharmaceutical Engineers (ISPE) to BioPhorum, has a Biopharma 4.0 initiative underway. January 2020 marked the official start of the Biopharma 4.0 Alliance, a partnership between the National Institute for Biotechnology Research and Training (NIBRT) in Ireland and the Boston Consulting Group.

The alliance is working with 17 different software, control, and equipment vendors as well as biopharmaceutical manufacturers on real-world Biopharma 4.0 use cases. A demonstration center (Photo) is now up and running to introduce more industry professionals to the concepts involved.

A number of biopharma equipment vendors have introduced products that directly apply Biopharma 4.0 concepts. Sartorius Data Analytics, for instance, is launching a modern data-science platform for process development and data management, and to support the trend to open-source data modeling (e.g., using the Python coding language) and hybrid modeling, which blends statistical and kinetic and metabolic modeling techniques, says Demesmaeker.

MilliporeSigma has launched the Bio4C Software Suite, which combines process control, analytics, and plant-level automation, allowing users to visualize, analyze, and control the entire manufacturing process and individual operational units, enabling enhanced process control and insights, says Bulpin. ProcessPad, another recent introduction, is designed to help users acquire, aggregate, and analyze data from equipment, paper and electronic records, and facility databases, to automate the generation of continuous process verification reports.

Emphasis on Raman sensors

On the sensor level, MilliporeSigma introduced Raman spectroscopy sensors and accompanying software to provide real-time process analytics across multiple critical process parameters via in-line measurement. Sartorius also rolled out the BioPAT Spectro sensor platform, which allows users to integrate Raman spectroscopy into ambr 15 and 250 development platforms as well as Biostat STR development, pilot, and production systems, says McHugh.

In reactor modeling, McHugh says, techniques such as tip-speed scaling are being replaced by more advanced and holistic approaches that weight many factors at the same time (e.g., power-per-volume, gas transfer, carbon dioxide stripping, eddy size, shear stress, and volume effects) for the entire duration of the process.

References

1. B. Marr, “What is Industry 4.0” forbes.com, Sept. 2, 2018.
2. M. Testas, et al., PharmTech 44(7) 35-36, 2020.
3. J. Markarian, PharmTech 42(4) 20-25, 2018.

About the Author

Agnes Shanley is senior editor to Pharmaceutical Technology.

Article Details

Pharmaceutical Technology
Vol. 44, No. 8
August 2020
Pages: 27–28

Citation

When referring to this article, please cite it as A. Shanley, “Skipping Steps to BioPharma 4.0,” Pharmaceutical Technology 44 (8) 2020.