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 projects. He has an active pipeline of research proejcts with the ultimate gola to bridge the gap between evidence and clinical practice.

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 transdiagnostic (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 from international cohorts on risk prediction: these studies aim to develop or replicate individualized prediction models to predict the onset of severe mental disorders, leveraging the U.S. database NeuroBlu.
   1. A 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. Postdoctoral Fellow: Gabriele Lo Buglio
3. Real world evidence studies from international cohorts on psychopharmacology response prediction: these studies aim to replicate and extend our prior nationwide Swedish register findings, in close collaboration with Heidi Taipale's group.
   1. A cohort study using the Holmusk-Neurublu data aims to build a prediction model among individuals with obsessive-compulsive disorder and major depressive disorder to examine which factors predict improvement in depressive symptoms after treatment initiation. PhD student: Saguna Katya
   2. A population-based cohort study using Ontario administrative data to examine the long-term safety and effectiveness of ADHD medications in individuals with schizophrenia-spectrum disorders, focusing on outcomes such as psychiatric and somatic hospitalizations, and mortality. Postdoctoral Fellow: Olivier Corbeil
4. Disparities in physical healthcare for those with and without mental disorders: A systematic review and quantitative appraisal of currently available cardiovascular risk assessment tools for use in clinical practice among people with severe mental illnesses.
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. PhD student: Gyselle de Geus