Psoriasis is the most prevalent chronic skin disease with a high physical and mental burden. Treatment has significantly advanced with biologics; highly effective yet expensive drugs. Many different biologics exist, yet guidelines on choosing amongst them are lacking. Furthermore, response to these biologics vary considerably, resulting in trial-and-error. The need to predict response prior to treatment would allow better psoriasis management. Here, we will identify biomarker candidates predicting response, eventually enabling prescription of the most effective drug per patient. Based on serum and whole blood, we will analyze protein signatures and immune profiles that correspond to treatment response. Hitherto, we will perform proteomics and immune phenotyping to screen for candidates. This project is based on a prospective and retrospective cohort, longitudinal trial including control group without medication. This allows us to find serological and/or cellular biomarker candidates that predict treatment response in patients with psoriasis amongst biologics. This project enables precision and personalized medicine in clinical practice, whilst creating novel industrial opportunities, companion diagnostics or identification of novel therapeutic targets.