Today’s bioprocessing technicians are highly skilled professionals who can operate large automated equipment, juggle numerous support activities, and document manufacturing deviations. In coming years, their jobs will become even more rigorous as companies push more decision-making to the production floor to save time and resources. With the trend toward smaller batches made in bench-scale and/or single-use equipment, this strategy becomes easier to implement. One way to foster improved decision-making on the production floor is to hire or promote employees who understand the basic scientific principles underlying a bioprocess. What abilities and skills does the workforce of the future need to make the best decisions? And how can that workforce be developed?
A Changing Paradigm
The typical biomanufacturing company advances a drug substance from research to the marketplace by navigating though a rigorous gating process that enables process development, technology transfer, process performance qualification, and production. Subject-matter experts (SMEs) in each phase conduct the work in their project plans and then communicate their findings to those working in the next phase. Their efforts encourage specialization and facilitate attention to certain details, but also can lead to resource inefficiency, longer cycle times, and greater risk of miscommunication. By the time a bioprocess makes it into manufacturing, it may no longer be optimized, and much of its development history will be buried in multiple laboratory notebooks. Time, and maybe product, can be wasted when production personnel need to contact the original development engineers or support staff to help troubleshoot a process failure. Fortunately, several industry trends are challenging this paradigm and fueling a demand for new skills on the production line.
Pressure to reduce prices has forced companies to take a closer look at the cost to commercialize and manufacture a drug product. They are asking tough questions such as, “How much will all this specialization cost?” and “Will faster decisions on the production floor reduce waste?”
Development of advanced analytics is making it possible to monitor and release products in real time.
Rapid adoption of single-use disposable technologies has reduced the number of routine manual interventions for cleaning, sterilization, and similar operations.
Autologous cell therapies and gene therapies for rare diseases require smaller volumes, and bench-scale equipment is typically used.
A Workforce Transformed
Given these trends, it’s advantageous for companies to build organizations in which production personnel understand underlying scientific and engineering principles that support bioprocesses and can react quickly to manufacturing deviations. In bioprocessing operations that use large, highly automated stainless steel equipment (e.g., for production of monoclonal antibodies), technicians with a background in science will be able to troubleshoot problems and make corrective actions in real time without help from support staff. The growth of advanced analytics and process analytical technology (PAT) is producing more process data, but until every deviation can be predicted and every corrective action can be programmed, the bioprocess technicians’ jobs will become more challenging (1).
Autologous cell therapies and gene therapies for rare diseases require smaller volumes than for production of monoclonal antibodies and often can often use single-use technologies that are facilitate operations. With these products, research scientists can be given a greater role in shepherding a therapy through its life cycle — all the way to the production line. With this goal in mind, a scientist can focus development activities on establishing a commercial manufacturing process capable of consistently producing the specified drug substance according to ICH Q8 (2). Outputs include critical quality attributes, design space, and control strategy. PAT strategy can be developed here, as well. At this point, it would be natural for a scientis