The Validation Devil is in the Details

By Patrick McGee

As with most popular quotes, “the devil is in the details” has been around for so long and has been used so much that it has become a cliché. But like most clichés, it is only cited so often because it is so true. We have all learned, whether through personal experience or that of others, that if you don’t sweat the details, you’ll have a devil of a time with whatever project you work on.

Take method validation, which is a vital part of the pharma and biotech industry. Although it’s not very sexy, it’s one of those things, like changing your motor oil or flossing, that simply must be done unless you want a bad outcome.

“All analytical methods intended to be used for analyzing any clinical samples will need to be validated. Validation of analytical methods is an essential but time-consuming activity for most analytical development laboratories,” writes Chung Chow Chan, PhD, author of one of two method validation articles in this issue (see “Principles and Practice of Analytical Method Validation"). “There are many reasons for the need to validate analytical procedures. Among them are regulatory requirements, good science, and quality control requirements.”

Quality control, as we all know, equals efficacy and safety for patients who are the end users of the drugs and biologics our industry produces. As Dr. Chan notes, the managers of quality control units “would definitely want to ensure that the analytical methods that the department uses to release its products are properly validated for its intended use so the product will be safe for human use.”

But despite the obvious importance of this validation, we are only human, and mistakes are made, errors that can lead to citations from the Food and Drug Administration (FDA), something no company wants. In the second methods validation article in this issue, Bridwell and colleagues outline cases that resulted in such citations (see “Perspectives on Method Validation").

In one case, the FDA cited a pharmaceutical manufacturer for not validating its product quality method. The reason the manufacturer gave for this inadequate validation was the complexity of the sample matrix being tested. “In this case, researchers could have no confidence in the data generated, because if the matrix was in fact complex, significant unseen issues might exist with the accuracy of test data,” the authors write. But they add that regardless of sample matrix complexity, “an adequate level of method validation is required to ensure that test results are reliable.”

In another case discussed by the authors, a firm was cited for using an inadequately validated method, and, in yet another, method validation was performed, but the validation criteria, which were determined beforehand, were not properly adhered to or specific enough to prohibit reanalysis without due cause.

“In all the reviewed scenarios,” the authors write, “proper validation designed to match the intended use of the method was shown to be critical in the implementation of an accurate and reliable analytical assay.”

So make a new year’s resolution to perform proper validation. It will surely make for a more pleasant, productive, and profitable 2010.

Sincerely,

PATRICK McGEE
Editor
pmcgee@wiley.com