The Devil’s in the Details

The reported benefits of continuous manufacturing for small molecules over batch manufacturing include accelerated product and process development, higher product quality, and reductions in capital, operational expenditures, and footprint. But to achieve higher product quality, the process operation needs to be maintained under a state of control – in general, based on product and process knowledge, and advanced model-based techniques, such as data reconciliation, model predictive control, and risk analysis. 

For pharma to move to fully continuous manufacturing, strategic and concurrent adoption of modern process systems engineering tools is needed. In particular, companies must take into consideration the ability of their equipment to connect with automation systems. Systems integration and automation systems, as well as supervisory control and data acquisition tools, are crucial to achieve reliable process operation. Tableting machinery, for example, needs to be complemented by advanced manufacturing components, such as process mechanistic modeling, online, inline and at-line process analytical technology, fault diagnosis, material tracking, and real-time risk assessment. For such process analytical technologies to be implemented, however, companies may have to consider modifying their tablet presses to gain access to the powder inside of the feed frame assembly. Similarly, the tablet press hopper may need to be redesigned to better accommodate upstream and downstream flow variability, and to install content uniformity and mass flow rate sensors.

 The measures for quality control of tablets in the context of a continuous process are not necessarily different from those used in the context of batch manufacturing, but continuous manufacturing systems can be equipped with control systems that are handling raw material variability and assuring product quality in real time. For these control systems to be successfully designed and implemented, a robust communication network, a redundant real-time sensor network, mechanistic reduced order models of unit operation, and model-based data reconciliation framework are essential. 

After developing and implementing the process systems engineering tools needed for continuous manufacturing and building process knowledge and a data-rich process historian, one can identify optimal and robust manufacturing routes, sensor placement, operation conditions and, naturally, whether batch, end-to-end continuous, or hybrid configurations are preferable.

Similar control systems can be applied to batch operations by implementing real-time process monitoring and then designing a control strategy to enforce quality at the end-point of each unit operation, but the same levels of efficiency and eco-friendliness (along with the other benefits that continuous manufacturing could provide) may not be achieved. 

But the adoption of continuous manufacturing will not happen unless the industry’s mindset changes. Fortunately, the challenges of developing new generations of equipment, sensors and automation are being embraced by academics, equipment manufacturers, and pharmaceutical companies. Similarly, some regulatory agencies are working with both the industry and academia in an effort to better understand continuous manufacturing.