Mental disorders present a significant global health challenge, markedly contributing to disability and diminished quality of life worldwide.
Presently, treatment options are sparse, and drug discovery efforts are hindered by ineffective understanding of underlying disease mechanisms.
Our primary objective is to identify and repurpose existing drugs to treat mental disorders.
We utilize advanced computational methods applied to real-world data from electronic health records and nationwide healthcare registers and biobanks across several countries.
We propose a four-step strategy:
- Identification: Use Danish EHRs to identify drugs with potential collateral benefits for mental disorders.
- Prioritization: Prioritize drug-disease associations using genetic, transcriptomic, proteomic, metabolic pathway, and drug-protein interaction data.
- Replication: Replicate the candidate associations using national EHRs from Norway, Sweden, and Estonia.
- Biomarker Approach: Identify biomarkers signatures of patient subgroups with distinct drug-disease effects.
Our team has privileged access to national registers and extensive Nordic biobank data in four countries, coupled with state-of-the-art, secure, and efficient analytical infrastructure. We integrate expertise from psychiatry, epidemiology, pharmaco-epidemiology, pharmaco-genomics, genetics, psychopharmacology, machine learning, and bioinformatics.
The concluding series of biomarker analyses will serve a dual purpose: independently validating the initial drug-disease associations and enabling patient stratification for precision treatment.
Our project will advance personalized psychiatry, and further the transitioning from group-level treatments towards tailored, individualized therapies. Notably, the research team includes members with lived experiences who will ensure that aims, strategies and dissemination are informed by patient perspectives.