Officials at Catalent, a CDMO, recently announced plans for a new gene therapy facility, explaining that the $130 million expansion will add five Phase III through commercial-scale manufacturing suites.
The plant will make extensive use of automation according to Randy Henrickson, VP, commercial operations, Catalent Cell & Gene Therapy, who tells GEN the approach is key to managing data at the existing plants on the campus.
“Currently, we employ advanced process equipment skids and laboratory instrumentation with standalone automation controls and capabilities for data generation and localized storage,” he explains. “Our goal is to centralize data collection and analysis and have these skids and instruments communicate through the exchange of higher-level data, with a shop floor network (SFN).”
Henrickson says the approach allows data gathering from all operations, citing process equipment and lab instruments as an example.
“Data from these operations can then be used by development and, when validated, for CGMP reporting,” Henrickson adds. “Data can be viewed remotely, allowing users to observe process operations in real-time. Increased use of hardware and software sensor technologies allows users to be alerted of excursions outside given parameters.”
CDMO benefits
Catalent says there are significant benefits from an operations perspective. However, the CDMO also believes automated data gathering and management will impact product development timelines and quality.
“With SFN integration, it is possible to improve product lifecycle management by standardizing, streamlining, and collaborating based on historical data and more detailed process knowledge. Predictive analytics can be used to reduce waste and downtime, and to better assure quality standards are maintained and reduce variability through better process capability and increased yield,” Henrickson says.
He contrasted the approach with traditional paper-based methods in which data generated during a process are manually transferred.
“An advanced method based on automation and digitalization offers possibilities such as downloading setup parameters to the process equipment,” Henrickson continues. “And as mentioned above, data generated from the equipment can be captured and stored in centralized and organized databases for analysis by development or, when validated, CGMP reporting.”
Catalent is also pitching automation as an advantage for customers, particularly during technology transfer.
“As a CDMO, any technology transfer improvements are important, and making processes, specifications, methods, recipes, etc., available from centralized databases helps to accelerate transfer and reduce risk, for example in manual transcription errors,” Henrickson says.
Integration challenges
Integration is the biggest difficulty involved in setting up facility-wide, automated data management, according to Henrickson.
He tells GEN that while most bioprocessing systems feature a degree of automation capability, making sure the work together is tricky.
“Integrating many different systems in an efficient, simple, and holistic way is certainly a challenge and requires infrastructure, hardware and software systems, and technologies capable of reaching those many different vendors’ systems, and then be able to funnel data into centralized databases from where users can access it for processing, analysis, and ensuring its integrity and security,” he says.
More widely, use of automation and other bioprocess 4.0 type ideas in the CDMO sector is increasing, notes Henrickson, who says streamlining onerous tasks and reducing errors are major motivations.
“In many instances, certain repeatable tasks can be automated, this way elements of human error can be reduced or eliminated. Also, discrete data can be directly taken from the process or lab equipment and printed or later organized in records with less human intervention, also reducing potential errors that may occur during manual manipulation and entry in paper records,” Henrickson explains.
“Recorded electronic data can be retrieved for further analysis or in the case of GMP operations it can be used for investigations or any other quality/predicated rules requirements as well as achieving continuous process verification (CPV), which is one area the regulators have shown interest.”
Training is another area of innovation, particularly with the various travel restrictions resulting from the COVID-19 pandemic.
Henrickson adds, “Technologies such as Augmented Reality (AR) are finding application in bioprocessing operations, for example, training or operation of equipment with remote assistance. This has proven particularly useful during the COVID-19 pandemic, and Catalent is embracing digital collaboration tools for virtual viewing on the manufacturing floor through wearable technology.”
