Antibiotic-associated encephalopathy (AAE) is a central nervous system disorder caused by antibiotics administration and classified into three types based on clinical symptoms. Type 1 AAE causes seizures and myoclonus, type 2 causes psychiatric symptoms, and type 3 is characterized by cerebellar ataxia. In this study, we investigated whether the electrical activity of in vitro human iPSC-derived neurons to antibiotics could be classified based on the 3 types of AAEs classified by clinical symptoms. Glutamatergic, GABAergic neurons and astrocytes differentiated from human iPS cells were seeded on micro-electrode array (MEA). The cumulative administration of 13 different antimicrobials detected changes in neural activity that differed according to AAE type. Next, we classified the antimicrobials by principal component analysis (PCA) and confirmed the AAE type of each agent. We found that Types 1-3 AAE agents were distributed separately. The classification of antibiotics depending on electrophysiological response characteristics was consistent with the clinical practice classification of AAEs. In conclusion, the combination of electrophysiological responses of human iPS cell-derived neural networks measured by MEA plus multivariate analysis methods will effectively detect and classify antibiotics developmental risks.

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