Alasandro, Mark; James Bergam; Laura

¶ … Alasandro, Mark; James Bergam; Laura Faust, Marianne Gorko et al. (2003, April).

Identification of Out-of-Trend stability results: A review of the potential regulatory issue and various approaches. Pharmaceutical Technology.

Retrieved June 21, 2010 at http://pharmtech.findpharma.com/pharmtech/data/articlestandard//pharmtech/152003/52982/article.pdf

Out-of-trend results (OOT) are an important topic both for political and economic reasons in the pharmaceutical industry: they can affect how a drug is prescribed, administered, and regulated. Simply stated, an OOT is a statistical result about a drug that falls outside of expected parameters. A pharmaceutical company might attempt to establish an expiration date for a new medication, but an OOT result testing for drug efficacy can complicate setting such standards. Ideally, when reviewing statistical information, an alarm is sounded only when needed, and the risk of false alarms is minimized, while significant results are not overlooked.

When testing a batch, an anomalous result is usually flagged if three consecutive results are outside a preset limit or "the difference between consecutive results is outside of half the difference between the prior result and the specification" (Alasandro et al., 2003, p.42). Other red flags might be if results from the tests are greater or less than 5% of the initial result or the mean of all previous results or 3% of the previous result of the test.

A regression chart, a statistical by-time-point approach (to determine whether a result is within expectations in comparison with other batches measured at the same time), and a slope control chart method are all ways to examine the significance of deviations. Degradation of quality is of particular concern for pharmaceuticals, and "unlike batch-release results, which represent one point in time for a batch, stability results may change over the shelf life of the batch" (Alasandro et al.,, 2003, p.48). Thus while determining whether a batch is of a particular level of quality is vital, even more challenging is the question of how to anticipate significant changes in the quality of the medication over time.

The pharmaceutical industry presents unique challenges for business research. Like most enterprises today, quality control and zero defects is essential. But drug manufactures are dealing with life-and-death matters on a daily basis regarding product consistency: an individual who takes too much or too little of his or her needed dose because of a deteriorated drug could have his or her health severely compromised, and legal repercussions are the likely result for the company. Additionally, products even within batches can change over time, so even an initially 'perfect' product may show signs of degradation. In the interests of consumer safety, the effects of such degradation must be anticipated through statistical means, but it remains controversial as to what is the best way to accomplish this.