Israeli startup uses AI to find best depression treatment

Prescribing the right anti-depression medication often involves tedious trial and error. Your psychiatrist suggests one type of pill, but it doesn’t work or has too many side effects. So you go on to the next medication and then another one until you finally find a prescription that seems to work. Meanwhile, the debilitating symptoms of depression continue. Neuroscientist Dekel Taliaz found the entire drawn-out process to be, well, depressing. So, together with his brother Oren, he set up a company bearing the siblings’ family name – Taliaz – to apply the latest in artificial intelligence and machine learning to enable psychiatrists to prescribe the right anti-depression medication the first time.

The company has developed proprietary algorithms that, when given a series of inputs including DNA swabs for genetic data; a detailed mental-health history; information on the patient’s environment and his or her demographic background; and any already existing clinical data from the patient’s electronic medical record (EMR), can predict the efficacy (as well as any adverse effects) of current antidepressants with up to 80 percent accuracy. That’s a significant improvement over what happens today, where some two-thirds of patients fail to get better following the first anti-depressant prescribed and another one-third quit their first-line treatment entirely. According to the World Health Organization, depression is the leading cause of disability worldwide, affecting more than 300 million people of all ages.-- More...

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