Psychiatric drug development still leans on rating scales developed decades ago: subjective instruments that capture how a patient describes feeling but not what the brain is doing. In major depressive disorder (MDD), high patient variability, strong placebo responses and limited objective measures of treatment mechanisms can create challenges for trial design and go/no-go decisions. Electroencephalogram (EEG) and event-related potentials (ERP) offer objective, low-burden and inexpensive measures of brain function. This webinar explores where EEG and ERP can support MDD clinical trials, where they fit within a protocol and where their limitations should be considered. The featured speakers will examine the published literature alongside their own research, including EEG signatures that can distinguish MDD patients from matched controls and track symptom severity. These signatures capture different aspects of the disorder, including cognitive function, emotional processing and behavioral attention. The panelists will discuss how these EEG signatures appear largely non-redundant, suggesting that different paradigms index different facets of the disorder and that a single “depression biomarker” may not capture this complexity. The panelists will also review evidence showing that targeted pharmacological intervention can shift these measures, positioning them as pharmacodynamic rather than exploratory tools. The panel will focus on decisions development teams face when designing MDD clinical trials. Topics include whether EEG can improve pre-screening, inform dose selection and confirm target engagement earlier and more cost-effectively. The discussion will also address how anxiety, insomnia, disrupted sleep architecture and substance use disorders carry their own electrophysiological signatures and can confound a depression readout