High-quality stability data are critical to the pharmaceutical and biopharmaceutical industries. These data form the basis for justifying specification limits (also called acceptance criteria in the International Conference on Harmonization [ICH] Q1 and Q6 guidances), for setting and extending product expiration dates, and for establishing product label storage statements. Annual, routine stability studies also can be used to support product or process modifications and are vital for ensuring the continuous quality of production batches. To facilitate the prompt identification of potential issues, and to ensure data quality, it is advantageous to use objective (often statistical) methods that detect potential out-of-trend (OOT) stability data quickly.
In general, OOT stability data can be described as a result or sequence of results that are within specification limits but are unexpected, given the typical analytical and sampling variation and a measured characteristic's normal change over time (e.g., an increase in degradation product on stability).
OOT stability results may have a significant business and regulatory impact. For example, if an OOT result occurs in the annual production batch placed on stability, the entire year's production could be affected, depending on the OOT alert level. Systems that are useful for detecting OOT results provide easy access to earlier results so that they can track stability data and trigger an alert when a potential OOT situation arises. Procedures describing OOT limits, responsibilities for all aspects of an OOT system, and investigational directions are all components of a company's quality system.Representatives from the US Food and Drug Administration and 77 individuals from more than 30 Pharmaceutical Research and Manufacturers of America (PhRMA) member companies met in October 2003 to address important stability OOT alert issues. Their discussions underscored the need to track OOT stability data, associated issues, and potential statistical or other approaches to establish OOT alert limits. Breakout sessions captured participants' perspectives on FDA expectations and guidances, acceptable OOT identification methodologies, and implementation challenges.
Workshop attendees concluded that the main focus for OOT identification and investigation should be annual, routine production stability studies rather than primary new drug application (NDA) batches because historical data are usually needed to determine appropriate OOT alert limits.
In addition, attendees clearly expressed a desire for a simple approach to tracking stability data that would allow at-the-bench, real-time detection of OOT results. This capability is important from an implementation standpoint so that a timely investigation can be initiated. Timeliness is especially important when an analytical error is suspected of causing OOT results. It was recognized that an efficient approach with such properties might be difficult to achieve.
Another recommendation was the need for standard operating procedures (SOPs) that address how to handle (e.g., identify, investigate, conclude, take action) OOT data. Workshop participants believed that a separate FDA guidance is not needed to develop such SOPs because the existing out-of-specification (OOS) guidance should suffice.
Three types of OOT results—which determine the degree and scope of an OOT investigation—were identified at the workshop. This article expounds on these outcomes and addresses other questions raised during the workshop and in a previous article (1). Recommendations put forward in this article are not requirements, but rather, are possible alternatives for handling OOT data.
Types of OOT data
A process control alert occurs when a succession of data points shows an atypical pattern that was possibly caused by changes to the laboratory or manufacturing process. These data points might originate from the same stability study (see Figure 2) or from multiple studies assayed within a reasonably close timeframe (within a few weeks) (see Figure 3). As these Figures 2 and 3 indicate, the trends for the batches in question vary substantially from those of comparable batches. Despite the deviating trends, no pending potential OOS situation occurs.
Lastly, a compliance alert defines a case in which an OOT result suggests the potential or likelihood for OOS results to occur before the expiration date within the same stability study (or for other studies) on the same product (see Figures 4 and 5).