Efforts to optimize biopharmaceutical manufacture often focus on the facility. Developers use data to try to optimize culture conditions and increase yields upstream or employ novel filtration technologies to speed downstream processing.
But data-driven, industry 4.0 ideas can be applied more widely, according to Claudia Berrón, senior vice president, business development and commercial operations at Avantor, who suggests the process of biopharmaceutical raw material characterization stands to be revolutionized.
“Characterization is such a focus area because inherent raw material variability could impact both upstream and downstream processing steps in the production of a biologic,” she says. “Without rich data that allows a biopharma manufacturer to know and understand the characterization of the materials they are using, the smallest variability even within established compendia specifications in what might be considered a well understood raw material, such as a buffer, could have a detrimental impact on the outcome of an entire process.”
With full characterization biopharmaceutical manufacturers can quickly narrow down root causes and trace them back to a specific raw material, potentially saving months spent trying to understand a variability, Berrón adds.
Raw material supply chains are highly complex. Multiple manufacturers, wholesalers, and distributors in many countries can be involved, which makes tracking the flow of materials a significant challenge.
This complexity also makes it ideal for digitization and the application of “bioprocess 4.0” ideas, according to Berrón, who says the secure transfer of raw material data has significant benefits.
“Data mining from the biopharma supply chain, which is known to be incredibly complex, and digitizing crucial raw material information continues to be a target in biopharma 4.0,” she tells GEN.
“Gaining such in-depth visibility from suppliers driven by strong collaborative efforts gives biopharma manufacturers the ability to more accurately assess and predict the process performance of any given raw material ahead of its use.”
Pre-weighed powder and liquid materials used in single-use systems are an example of where a data driven approach has benefits. Traditionally such materials are delivered in drums, pails, and super sacks and they need to be QA tested upon receipt and then sub-divided before they can be used in a process.
“By contrast,” Berrón says, “materials delivered in pre-packaged, exact weight single-use packages, with complete e-delivery of documentation with the material, can help streamline a manufacturing process. Since only that material in that specific package will be used for a given production run, the traceable e-data that accompanies that package can be automatically incorporated into upstream or downstream operations.”
Packaging of the materials may even allow for quick identification with non-destructive techniques, such as Raman ID, she continues, adding that “Raman ID data is also a rich data set of raw material variability that can be mined to spot and trend variability linking it for that particular package to process yields or quality.”
The key to unlocking such benefits is in the hands of the raw materials suppliers, Berrón emphasizes.
“Through supplier collaboration, available datasets can be leveraged, without the biopharma manufacturer having to build that database itself,” she says. “The time savings of implementing pre-weighed raw materials with e-data supplied is dramatic: in one instance, taking a process from 30 hours of labor to nine hours of labor to receive and prepare materials for use in production.”
