An AI analysis of people on sertraline found that the popular antidepressant would only work on one-third of patients.
The findings, which were published this week in the American Journal of Psychiatry, offer hope for better treatment of depression. By applying machine learning to medical data, the researchers accurately predicted early responses to the drug — the most commonly prescribed antidepressant in the US.
“With this method, we can already prevent 2/3 of the number of ‘erroneous’ prescriptions of sertraline and thus offer better quality of care for the patient. Because the drug also has side effects,” said study co-author Liesbeth Reneman, a professor of neuroradiology at Amsterdam UMC.
To forecast the responses, the researchers studied brain scans and clinical data from 229 patients with major depression. The data had been collected before and after treatment with sertraline or a placebo.
By inputting this information into an algorithm, the researchers could predict within a week whether the medication would work.
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“This is important news for patients,” Reneman said. “Normally, it takes six to eight weeks before it is known whether an antidepressant will work.”
The study also highlighted a biological determinant of sertraline efficacy.
“The algorithm suggested that those who had a lot of blood flow in the anterior cingulate cortex, the area of brain involved in emotion regulation, would be helped by the drug,” said study co-author Eric Ruhé, a psychiatrist at Radboudumc University Medical Centre.
These findings could lead to better treatment of depression. At present, patients often take sertraline for up to six months before determining whether it works. If it doesn’t, they may go through the same process again with other antidepressants.
The new method could provide a faster route to the right medication.
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