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The aim of the PerPain project is to identify subgroups of patients with specific mechanisms of disease maintenance based on psychological comorbidity and to assess the efficacy of tailored pain treatments as well as their underlying mechanisms to further improve the treatment in these patients. We are developing a data driven algorithm to identify patients with specific comorbid mental disorders and psychobiological pain determinants for a mechanism-based personalized treatment allocation of CMSP (chronic musculoskeletal pain) patients. The aim of our research group is to enable personalized treatment via output prediction. It results in an optimal assignment strategy of patients into treatment-specific subgroups where a maximum on treatment response is to be expected. Our assignment strategy is based on individual treatment effect estimation using causal inference techniques.