Marco Solmi

Dr. Marco Solmi's main area of interest is epidemiological and evidence-based psychiatry, leveraging both meta-research techniques and national databases to answer clinically relevant questions. Clinically, he is most interested in prevention/early interventions for mental disorders, psychopharmacology, and physical health in those with mental disorders. He has experience in coordinating large international project, as co-PI of the Collaborative Outcomes study on Health and Functioning during Infection Times (COH-FIT), an online survey translated in 30 languages involving over 230 researchers from over 50 countries measuring functioning and physical and mental health in the general population during COVID-19 pandemic (www.coh-fit.com).
 

The SCIENCES lab, headed by Dr. Marco Solmi, focuses on epidemiology studies and evidence synthesis projects in the areas of COVID-19, physical health among those with mental health disorders, the effectiveness and safety of biological and psychosocial treatments for mental health disorders, and eating disorders. 

Dr. Solmi's current ongoing research activities include:

1. U-REACH (www.u-reach.org) stands for Umbrella-Review, Evaluation, Analysis and Communication Hub. It is an initiative and methodological framework designed to bridge the gap between complex scientific evidence and the real world. Its primary goal is to make high-quality health data accessible, understandable, and useful for everyone—including clinicians, patients, and the general public—rather than keeping it locked in academic journals.
2. Real world evidence studies form international cohorts on risk prediction: This cohort study using neuroblu data aims to replicate an existing prediction model to forecast the onset of a subsequent first psychotic or bipolar disorder in individuals with a non-psychotic/non-bipolar mental disorder. Student: Gabriele Lo Buglio
3. Real world evidence studies form international cohorts on psychopharmacology response prediction
4. Disparities in physical healthcare for those with and without mental disorders
5. Prediction Model of Antidepressant Response in Bulimia Nervosa: this retrospective cohort study aims to develop an prediction model for bulimia nervosa using real-world EHR data to support personalized treatment selection. Outcome measures include antidepressant treatment response, depressive and anxiety symptoms. Student: Gyselle de Geus