Neurotoxicity is a leading cause of pharmaceutical compound attrition. Drug-induced seizures can deprive the brain of oxygen resulting in brain injury and an increased incidence of mortality. These seizures are the result of excessive and synchronous firing of cortical neurons in the brain.
Improved assays are required to identify seizurogenic compounds in drug discovery. Microelectrode array assays have emerged as a promising tool to predict seizure risk by measuring drug-induced changes to the spontaneous firing activity of neural networks in vitro. In this Coffee Break Webinar, Dr. Benjamin Bader (NeuroProof) discusses how artificial intelligence-based machine-learning can be applied to these neural MEA datasets to improve the prediction of seizure risk.