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The Biomarker Black Box

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Lawrence Jennings, director of molecular pathology and diagnostics at Northwestern University's Children's Memorial Hospital, is just putting the finishing touches to a study on validating molecular assays in diagnostic laboratories. How people find biomarkers and bring them to use in a clinical setting is of great interest to him, and it's why GT's Meredith Salisbury caught up with him for a conversation about best practices and common mistakes in validation.

Genome Technology: Are there some best practice guidelines you'd offer readers?

Lawrence Jennings: I don't know if there's anything that's perfect. The things that we reference most often are the FDA websites themselves — they have specific recommendations. Usually it's directed toward industry, but for clinical laboratories that are developing tests they also fall under the purview of FDA to some degree. The FDA has jurisdiction over clinical laboratories and the results that come out of them; however, they have not really enforced their authority for a couple of reasons. One of them is that clinical laboratories are overseen by CLIA, and they also regulate the reagents — the ASRs and other reagents that go into the clinical laboratory.

In addition to the FDA, there are published guidelines — manuscripts that talk about bringing assays into a clinical laboratory. I think the problem is that with the FDA and with the people who write these standards, they view everybody who's developing a test and offering a test in the same regard. And for the smaller labs [the resource requirements] may be overwhelming. [They'll ask,] what do I need to do? Can I do fewer samples? Ultimately it's up to the director of the clinical laboratory to determine whether it meets the requirements for validation.

GT: What are some of the most common mistakes you see labs make?

LJ: I think the biggest mistake that most people have is distinguishing between analytical validation and clinical validation. It's really the clinical validation that matters. Analytical validation is of course required — but without getting to the clinical validation aspects, it means nothing. For example, analytical validation pertains to having an assay that identifies whatever analyte it's intended to identify and does that reproducibly and accurately — whereas clinical validation would take that result and give it clinical meaning. A lot of the laboratory tests that we see in our own institution began in a research laboratory where they might've done a research study that might have shown that this biomarker has some value. They might even decide this is clinically valuable — and it might be valuable within that laboratory under very specific circumstances. As long as they define those circumstances and they stay within that range then it's probably OK. But the problem comes when they start extrapolating to other patients or other analytes or when it's done in another institution that might not be doing it the same way.

GT: More recent tests look at several analytes in a panel. Is this proving to be more complex?

LJ: The challenge is on the clinical interpretation side. The technology and the techniques are advancing where that's not going to be the issue at all — whether people can do it. The FDA [statement on IVDMIAs] is meant to address specifically this point, that it's dangerous when people begin to offer tests that cannot be validated simply because they're operating in some kind of a black box. We brought this up within a committee meeting: at what point does this have to be an FDA-approved test? Among our committee members the feeling was that if the methods and clinical validation data are not publicly available — well, then, that's not acceptable.

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