The Diagnostic Dilemma
Doctors will soon have an arsenal of new genetic tests to help select the appropriate treatments or drugs for patients. Will they know how to use them?
In the last year, several new genetic diagnostic tests have hit the market: two tests that can predict from a person’s genes how well he or she will metabolize certain drugs and a third that forecasts whether lung cancer patients will respond to a specific treatment.
The tests herald the arrival of personalized medicine, which will allow doctors to select treatments and optimize drug doses for individual patients. But, according to many physicians and researchers, such tests alone won’t be much help. Rather, doctors will need to learn how to incorporate them into their clinical practices, and scientists will have to figure out what kind of guidelines doctors need to do this properly.
“We need to provide enough context that the average doctor in Idaho can look at the labeling [on a drug that can be genetically targeted] and understand and truly know what to do,” says Wayne Rosenkrans, director of scientific and medical strategy at AstraZeneca Pharmaceuticals in Wilmington, DE.
Tarceva, a drug for lung cancer, and its accompanying diagnostic test are often hailed as a model for this intersection of genetics and pharmacology, called pharmacogenomics. In May 2004, scientists discovered a mutation in the gene for the epidermal growth factor receptor (EGFR) that predicts who will respond to the drug. (The drug is more effective in patients whose tumors carry the mutation.) Sixteen months later, in September 2005, a commercially available version of the test was on the market, made by Genzyme Genetics, a diagnostics company based in Westborough, MA.
Doctors can use the Genzyme test to help select the right treatment for a patient – but the results aren’t always black or white, for not all patients who respond well to Tarceva carry the EGFR mutation. “Biological complexity strikes again,” says Rosenkrans. “If you want an effective diagnostic, you can’t just look at the EGFR receptor.”
Lecia Sequist, an oncologist at Massachusetts General Hospital and part of the team that identified the EGFR mutation, is running clinical trials on use of the diagnostic test in the clinic. “When [the mutation] was first discovered, it seemed very exciting – like a simple answer you could give doctors about who would benefit,” she says. But as more and more data came in, scientists discovered other factors that also affect how well Tarceva works, such as extra copies of the EGFR gene. “The test is useful, but we’re still trying to figure out the best way to use it,” says Sequist. Genzyme is now developing a new test to identify extra copies of the EGFR gene.
Rosenkrans says he worries about the impact of oversimplifying the interpretation of genetic diagnostic tests. For example, Medicare Australia, a government organization that subsidizes health costs for Australians, requires evidence that a lung cancer patient has the EGFR mutation for them to subsidize the drug. “That’s an example of a health authority using diagnostics in an inappropriate way,” says Rosenkrans.
What’s more, dealing with the complexity of diagnostic tests will become an even bigger issues as the tests become more sophisticated. The EGFR test is relatively simple, for example, detecting a mutation in a single gene. Future diagnostic tests will likely rely on multiple factors, to predict the best treatment or to give a partial prediction of how a patient will react to a drug (see “Heading off Heart Attacks”).
According to Brian Spear, director for genomic and proteomic technologies at Abbott Laboratories in North Chicago, IL, the pharmacogenomics community needs to figure out how to deal with the complexity of genomic data in the clinic. “Should we be faithful to the truth, which can be very complicated and difficult to implement?” he asks. “Or should we smooth out the edges to a place where people can use it?…I don’t know the answer, but it’s a choice we’ll have to make.”
Lawrence Lesko, director of the FDA’s office of clinical pharmacology and biopharmaceutics, says doctors using these tools should weigh the results of genetic tests with other risk factors, such as weight and age. “I see diagnostics as an adjunct to therapy,” says Lesko. “People talk about responders and nonresponders, but I think we’re really talking about a spectrum of probability.”
Test makers, meanwhile, are working on educating doctors about their diagnostic tests. Swiss drug-maker Roche is launching an educational campaign to teach physicians about a new test, approved by the U.S. Food and Drug Administration in January 2005, which predicts how people will metabolize many popular drugs, including antidepressants, pain medications, and beta-blockers. The test has only recently been distributed to clinical laboratories that process these tests for physicians – so it’s too soon to say how it will fare in clinical practice.
Become an MIT Technology Review Insider for in-depth analysis and unparalleled perspective.Subscribe today