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Brain wave patterns could eliminate ‘trial and error’ approach to antidepressants

| | February 19, 2020
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Image: Reuters/Mario Anzuoni
This article or excerpt is included in the GLP’s daily curated selection of ideologically diverse news, opinion and analysis of biotechnology innovation.

Scientists have taken a small step toward personalizing treatment for depression.

A study of more than 300 people with major depression found that brain wave patterns predicted which ones were most likely to respond to the drug sertraline (Zoloft), a team reported [February 10] in the journal Nature Biotechnology.

If the approach pans out, it could offer better care for the millions of people in the U.S. with major depression.

In the study, researchers used artificial intelligence to analyze the brainwave patterns in more than 300 patients who’d been diagnosed with major depression. Then they looked to see what happened when these same patients started treatment with sertraline.

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And one pattern of electrical activity seemed to predict how well a patient would do. “If the person scores particularly high on that, the recommendation would be to get sertraline,” [psychiatrist Amit] Etkin says.

Also, people whose brain waves showed they wouldn’t do well with the drug, were more likely to respond to a non-drug therapy called transcranial magnetic stimulation.

The results suggest depression treatment doesn’t have to rely on trial and error. “By finding people who are particularly sensitive to an antidepressant, we can find those people for whom the drug is very effective,” Etkin says.

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