Article | July 14, 2020

Use Advanced Analytics To Usher In The Continuous Manufacturing Era

By Lisa J. Graham, Ph.D., P.E., Vice President of Analytics Engineering, Seeq

Data

Regulatory support and innovations in technology have fueled the adoption of continuous manufacturing in pharma over the last several years, which exhibits a move toward operations excellence marked by rapid production within multi-use facilities, reduced scale-up risk, and greater quality expectations. The end-to-end, integrated, and intensified processing approach to drug production offers a wide range of benefits that help drive the industry’s goals to increase efficiency in drug development and manufacturing while lowering costs. With continuous manufacturing, you only have to run the process longer to generate the volumes required, significantly reducing the delays and risks associated with scale-up in batch manufacturing. Maintaining a steady state of production with continuous manufacturing also eliminates batch variability and improves product quality and availability. By facilitating scale-up while simultaneously ensuring high quality, continuous manufacturing opens the door to accelerating the development to commercial launch process.

However, the complexity of how quickly data must be analyzed is greater with continuous manufacturing. The start-and-stop steps of batch manufacturing allow more time for analysis and decision-making as opposed to continuous processing, where material rapidly moves from one unit operation to the next. As a result, analytics must be performed faster to quickly identify any issues and take action before valuable product is lost. In addition, continuous manufacturing consists of interrelated unit operations, where the control of a single unit operation affects what is happening in the next, requiring a greater level of understanding about how the various steps interact. Therefore, implementing continuous manufacturing requires a robust data collection and integration strategy across your entire organization.

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