The research interests of William V. Bobo, M.D., M.P.H., are focused on examining and predicting the clinical effects — both beneficial and harmful — of medications used to treat people with severe mood disorders. Dr. Bobo's research examines the effects of selective serotonin reuptake inhibitors (SSRIs) and serotonin and norepinephrine reuptake inhibitors (SNRIs) on vulnerable populations such as pregnant women, and applies artificial intelligence and other advanced computational approaches to health care.

Focus areas

• Studying symptom dynamics using machine learning to predict clinical outcomes of SSRI treatment in adults with depression
• Integrating pharmacogenomics biomarkers within a machine learning workflow for predicting short-term antidepressive response to SSRIs in adults
• Investigating prospective validation of a machine learning, artificial intelligence platform for predicting the response to SSRI and SNRI antidepressants in adults with major depressive disorder
• Conducting a population-based historical cohort study of the incidence, predictors and outcomes of antidepressant-associated poor neonatal adaptation syndrome in youth who were exposed to antidepressants in utero during the third trimester of pregnancy
• Conducting a retrospective, population-based cohort study on the risk of mood and anxiety disorders in youth who were exposed to antidepressants in utero

Significance to patient care

In collaboration with researchers at the University of Illinois at Urbana-Champaign, Dr. Bobo has developed a machine learning workflow that has shown considerable promise for accurately predicting the eventual treatment outcome of adults with major depression who receive SSRI or SNRI antidepressants. This workflow is now being turned into a practical tool that may aid clinical decision-making. Dr. Bobo's epidemiology studies are addressing important questions about the fetal, neonatal and developmental safety of antidepressants that are commonly used by pregnant women.