Too often, depression is used as a synonym for sadness. Unfortunately, Major Depressive Disorder (MDD) is anything but. Affecting over 300 million people, this psychiatric disease is the leading cause of disability, draining $925 billion from the world economy in lost productivity. Yet it remains as one of the most overlooked conditions in the world. This talk explores the problems of depression from several scientific angles, critiques current diagnostic tools and theories for the root cause of depression, and proposes new science-driven solutions to this mental health disorder. Specifically, this talk expands current investigations regarding the link between changes in gene expression to the development of depression by presenting the results of a new study that uses gene expression levels and machine learning to diagnose, identify a genetic biomarker of, and create the chemical composition of a drug against depression. Finally, the talk concludes by encouraging the audience to build a society that invites new ways of thinking about depression. Ananya Lakkaraju is a junior at Hamilton High School whose main interest is the intersection of biology and machine learning. She is heavily involved in Astralis, a research and innovation club at her school. She is also involved in her school’s Girls Who Code and Speech and Debate club, participating in Public Forum debate and Congress. Outside of school, Ananya volunteers at the Arizona Science Center, conducts research at ASU, and does research at home. She has participated in several science competitions, including AzSEF and ISEF. Her current research projects have focused on the use of machine learning for diagnosing and treating depression. In the future, she hopes to pursue a degree in CS/AI while applying these skills in the medical field. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at https://www.ted.com/tedx