Pea-sized brain organoids grown from patient cells have revealed, for the first time, the distinct electrical patterns that distinguish schizophrenia and bipolar disorder from healthy neural activity. Johns Hopkins University researchers used machine learning algorithms to analyze the firing patterns of neurons in these lab-grown “mini-brains,” achieving diagnostic accuracy rates of up to 92%. The findings represent a potential leap from today’s trial-and-error approach to psychiatric care toward precision medicine based on biological markers. They’re collecting blood samples from additional psychiatric patients to test how various drug concentrations might influence the organoids’ electrical signatures. The technology could potentially reduce the months-long medication trials that psychiatric patients currently endure.