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The Capital Region of Denmark - a part of Copenhagen University Hospital

Neuropharmacological treatment: Precision medicine in epilepsy and depression

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The aim of this thematic alliance is to establish which key features predict drug response in patients with epilepsy or depression. Background: Epilepsy and depression are frequent and devastating brain disorders and both conditions are treated with pharmacological interventions that often fail to succeed. Epilepsy often co-occurs with mood disorders and there is reason to believe that the comorbidity is underrecognized in both patient groups. Comorbidity is also associated with less favorable outcome of drug treatment. That is, there is a huge unmet medical need to better diagnose and treat these two serious brain disorders.

Methods and Materials: We will make use of Danish registries to identify associations between intake of brain targeting drugs and clinical outcomes in order to uncover which patient features define a successful antidepressive or antiepileptic drug treatment. To investigate if we can identify patient subgroups, we will conduct advanced text-mining analyses which extract specific clinical features from electronic patient records. Through existing deep phenotyping or genetic databases with biobanks, those features will be related to, e.g., genetic and neuroimaging data to define biologically valid patient subgroups suffering from depression and epilepsy. To increase power to detect biomarkers and treatment response, we will establish new cohorts of patients with epilepsy and depression that we follow longitudinally.

Expected outcome and perspectives: It is our ambition to set the stage for a precision medicine approach in pharmacological treatment of epilepsy and depression, for the benefit of future patients. To succeed in our mission, we have devised a strategy for implementation of research outcomes in the clinic. It is our hope that in the long run, BrainDrugs can serve as a model to be implemented internationally, and for other brain disorders.

ID: 61962375