Although biopharmaceutical production today generally takes place in centralized manufacturing facilities, industry and regulators are taking a close look at the benefits of decentralized or distributed manufacturing, which involves smaller and flexible-volume manufacturing operations in multiple locations closer to the site of use and even to point-of-care (POC) locations. POC manufacturing is seen as essential for efficiency in producing personalized medicines. In the near-term future, POC production is likely to be in a controlled environment such as a hospital, clinic, or pharmacy, while in the long term, POC production could extend to other locations. Such a model could enable quality drug production anywhere, from the battlefield to remote villages or even outer space, experts suggest.
The impetus for POC manufacturing comes in part from its potential to alleviate pressing problems, such as drug shortages, pandemic preparedness, and equitable availability of treatments. It is also driven by technological advances that promise to allow efficient and consistently high-quality production using new equipment, analytical tools, and quality control paradigms.
These technologies offer the benefit of making drugs much closer to where and when they are needed. “The advantages of making medicines on demand—to solve issues such as the difficulty of predicting demand and the complexity of the supply chain—are compelling,” states Govind Rao, professor at the University of Maryland, Baltimore County (UMBC) and director of UMBC’s Center for Advanced Sensor Technology.
FDA recognizes the need for flexible and agile manufacturing and sees the potential for portable, distributed manufacturing units to be used for POC manufacturing. In October 2022, the Center for Drug Evaluation and Research (CDER) published a discussion paper that highlighted areas to consider for drugs regulated by CDER as well as the Center for Biologics Evaluation and Research and called for public feedback (1). FDA and the Product Quality Research Institute (PQRI) also held a workshop in November 2022 to gather input from stakeholders. For advanced manufacturing technologies—particularly distributed manufacturing, POC manufacturing, artificial intelligence (AI), and end-to-end continuous manufacturing—seeking input is the first step in FDA’s new Framework for Regulatory Advanced Manufacturing Evaluation (FRAME) initiative, according to a presentation by Michael Kopcha, director of CDER’s Office of Pharmaceutical Quality (2).
The European Medicines Agency’s (EMA) Quality Innovation Group is focused on a similar list of advanced manufacturing technologies, which were discussed at a March 2023 focus group meeting (3). That decentralized manufacturing is being discussed is one reason for optimism regarding its uptake in Europe, suggests Celeste Lamm, director of Global Regulatory Affairs, CMC at Merck. In addition, she points to the European Commission’s proposed new directive (4) that includes a pathway for decentralized manufacturing within the European Union and provides an architecture for responsibility between a central site and decentralized sites. “However, the proposal limits decentralized manufacturing to applications where the central site is located within the EU, and it isn’t clear how the regulation would be applied if some of the decentralized sites were outside of the EU,” Lamm says.
Regulatory uncertainty is an ongoing challenge, with unanswered questions around how connected sites that are located in different regions will be regulated and a lack of global harmonization. Agencies in different regions are communicating with each other, and it is hoped that approaches will be similar. Because no final guidance has been released by any regulatory agency, any differences in requirements are still unknown, Lamm cautions.
Change will take time. Lamm sees similarities between the pace of adoption of distributed manufacturing and that of continuous manufacturing. “Both regulators and industry acknowledge the benefits, but adoption has been slow, because existing traditional manufacturing is frequently sufficient, and it can keep costs down to use existing facilities,” Lamm says. “Adoption of innovative manufacturing technology occurs gradually as there is opportunity to replace existing lines, where existing technology isn’t sufficient (for example, when local manufacturing is needed), and where there is enough clarity to calculate the long-term benefit to justify investment.”
Consistent quality
A significant hurdle for distributed and POC manufacturing is how to ensure consistent quality of the drug product, but there is a growing availability of technologies that can meet this challenge. For example, prefabricated, portable cleanrooms and automated processes that fit in these spaces meet the need for standardization of equipment, process, and systems that is crucial to consistency. In addition, digital technology and cloud-based systems in use today make it easier to connect the data and quality systems of different locations. With these tools, distributed manufacturing can even reduce risk and contribute to consistency.
“Using enterprise quality systems across distributed sites is the natural extension of how we currently work in a global environment,” says Lamm. She says that regulators accept aspects of digitally connected quality system solutions, but they note that it is important to ensure that all personnel are similarly trained and are following the same practices.
“There are many flavors of distributed manufacturing for consideration when training personnel,” Lamm adds. Variations include the number of sites and the complexity of the manufacturing process. “The conversation regarding appropriate quality approaches for distributed manufacturing is ongoing, particularly for high volumes of sites or complex manufacturing processes. It is critical that we continue the dialogue between industry and regulators to address concerns.”
ML in QA/QC
Quality assurance/quality control (QA/QC) methods for distributed manufacturing will need to be different from those currently used in centralized manufacturing, says Rao. His group at UMBC recently patented a method for using machine learning (ML) to ensure consistent product quality in UMBC’s Biological Medicines On-Demand (Bio-MOD) system, which uses a cell-free method for end-to-end continuous manufacturing of biologic drug substances (5).
