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To expand upon what we discussed in our first blog of this series, let’s take a look at the main focuses of the FDA’s proposed quality metrics guide. A few of their priorities include utilizing CAPA systems that enable continuous improvement, decreasing the number of unexpected and out-of-specification results, and gaining a deep understanding of how a process should run (including the alert limits and action limits associated with it). This all works towards the goal of reducing product complaints and drug shortages.

Can a deep understanding of process knowledge set drug manufacturers up for success?

That is the hope. Collecting meaningful information about drug manufacturing processes can deepen employees’ process knowledge and provide many benefits. Knowing what to expect and identifying relationships between certain process attributes can shed light on issues that may not be easily detectable. This is especially critical because when many problems can start to appear, they don’t yet trigger a batch alert or failure. A process expert can identify these problems before they effect supply.

By using electronic databases, you can help build process expertise and sort through the information needed to be supplied to the FDA whenever it becomes required. Electronic systems will help to identify trending and relationships with regards to key process indicators, lab results, environmental conditions, and employee activity; just to name a few. The different types of systems that could be used for this type of data storage and analysis include LIMs, QMS, EAM, CMMS, electronic batch records and real time process data collecting applications.

Tracking specific equipment used in the production batches in these systems can be very beneficial as well. Monitoring equipment OOT’s (out of tolerances) and frequent unscheduled maintenance can help drug manufactures become actionable on potential problems within their production processes. This prevents batches from being affected or delayed, ultimately helping to maintain a reliable supply.  This can be extremely difficult to do with paper based systems, as trends are sometimes subtle and are developed over months. For example, a product temperature probe “check” may be increasing by 0.1 after every batch, but still within specification.  Identifying this trend could help someone repair that drifting probe before it fails in processing.

The FDA’s proposed quality metrics guidance proves that having electronic data can help drug manufacturers meet their inevitable requirements. Their hope is to enable drug manufacturers to acquire deeper process knowledge. We have seen manufacturing corporations have multiple advantages come from this; ultimately producing a significant increase in return on investment.