Risk-Based Thinking in Process Validation - Pharmaceutical Technology

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Risk-Based Thinking in Process Validation
The author describes why statistical significance would impose an unreasonable burden on manufacturers.


Pharmaceutical Technology
Volume 35, Issue 2, pp. 68-76

Validation has been practiced within the global healthcare industry since the early 1970s. While its exact origins are a matter of contention, during its evolution and unquestioned expansion into other areas, one element has remained unchanged during the past 40 years: an expectation of three performance-qualification runs. This practice was not always universal; before the US Food and Drug Administration issued its Guideline on General Principles of Process Validation in 1987, practice was somewhat more diverse (1). Interesting developments that emerged during the drafting and review of the original document have contemporary relevance to the 2008 draft revision of that guidance (2).

When the initial draft of the guideline appeared in the mid-1980s, it included an expectation for three performance-qualification runs as evidence of process control. When this document was issued for public comment, the organization that later became the Pharmaceutical Research and Manufacturers of America coordinated the development of a consolidated industry response. Some firms requested that the three-test requirement be reduced to two based on the premise that one replicate was sufficient to demonstrate process reproducibility. In an effort to accommodate all concerned, the responsible industry committee members developed a draft recommendation that the three-lot requirement be replaced with "a statistically significant number of batches." An almost immediate uproar came from companies that were performing three or more lots in their validation efforts. Although three trials were more than two, they certainly were not "statistically significant." When the organization realized this point, its members rapidly achieved a consensus on the three-trial expectation, and the comments that the group submitted on FDA's draft never mentioned the number of trials. Members acknowledged during those discussions that while "a statistically significant number of batches" would be more appropriate scientifically, the implications of such an approach were daunting.

This situation has now repeated itself, with the roles reversed. In its 2008 draft, FDA held that the "rule of three" is no longer appropriate and implied that more batches must be evaluated to provide the statistical confidence that is a central focus of the entire document. The difficulties inherent in expectations of statistical confidence in the 1980s are unchanged today. At a basic level, when the sample population is large, a sample size of 30 units generally is considered statistically appropriate. This output volume is actually quite substantial. During the author's 20 years of working in three large pharmaceutical firms, he encountered only six products (two parenterals, two active pharmaceutical ingredients, and two oral solid dosage forms) where more than 30 lots had to be produced in a single year. It should be immediately apparent that the initial validation of even relatively large-volume products cannot be accomplished using "a statistically significant number of batches." The time required to make the number of batches would be significant, and, in most instances, the material costs would be staggering. Validation efforts that extend for more than a few weeks are impractical from a logistical perspective, given the cost of drug-product manufacturing and the amount of inventory that must be held pending the completion of the exercise.

At the other end of the spectrum are low-volume products. These products are far more common than one might believe—not every product is a commercial blockbuster. The limited production volumes of these products may entail the manufacture of a single lot every 18 months or so. Validating low-volume products in a statistically meaningful fashion thus would require a 45-year period. Considering that future care might entail customized medications intended for a single patient, the total production of those products might consist of only a single lot. Clearly, using statistics to determine an appropriate number of commercial-scale lots to satisfy validation requirements is impractical.


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