Pharmaceutical quality is built on the principle that medicines are manufactured to be consistent and released in accordance with defined specifications. And while that principle remains true today, what is changing is how manufacturers create evidence that this quality is present.
Traditional quality control has relied heavily on testing at defined points in the process, including final product testing before release. This approach remains essential, but it can leave manufacturers with limited visibility into what happened during production. By the time an issue is detected, the batch may already have consumed valuable materials, equipment time and capacity. In high-value or high-volume manufacturing, that delay can have significant operational and supply implications.
Process Analytical Technology (PAT) and Quality by Design (QbD) offer a more proactive model. Together, they help manufacturers understand the relationship between process inputs, process conditions and product quality before routine production begins. Instead of treating quality as something confirmed at the end, they design it into the process from the start.
This shift is especially relevant for contract development and manufacturing organisations (CDMOs), which are often responsible for transferring processes developed elsewhere into a new site or operating model. Applying a QbD framework during this stage helps define what needs to be controlled and how those controls will be monitored as the process moves into routine manufacturing.
Moving from Reactive Testing to Proactive Control The value of PAT and QbD begins with knowing what has the greatest effect on product quality.
• Quality by Design (QbD) provides the structured methodology for identifying critical quality attributes (CQAs), critical process parameters (CPPs) and acceptable operating ranges.
• Process Analytical Technology (PAT) provides tools and data streams that can support real-time or near-real-time understanding of whether the process is operating as intended.
Using QbD and PAT together matters because data is only useful when it is linked to a defined quality objective.
In practical terms, that means the most important work often happens before a batch is manufactured. During technology transfer, the sponsor and CDMO need to align on the product’s CQAs, the process parameters that influence them and the site-specific considerations that may affect performance.
