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Psych-STRATA - A Stratified Treatment Algorithm in Psychiatry: A program on stratified pharmacogenomics in severe mental illness

Project description

Early detection and treatment of treatment resistances in psychiatric patients

Patients with severe psychiatric disorders such as schizophrenia, bipolar disorder and clinical depression often develop resistance to drug therapy. Even when the early signs of treatment resistance (TR) are detected, patients must undergo lengthy procedures before medical professionals can prescribe adequate pharmaceutical care. The EU-funded Psych-STRATA project intends to analyse extensive clinical, genetic and biological data of psychiatric patients to establish criteria for early detection of TR. Based on the findings, it will propose treatment strategies for patients at risk of TR. The project will further create machine learning models that can predict TR risk and patient response to treatment, thus assisting medical professionals in providing more personalised treatment.

Objective

A key problem in Mental Health is that up to one third of patients suffering from major mental disorders develop resistance against drug therapy. However, patients showing early signs of treatment resistance (TR) do not receive adequate early intensive pharmacological treatment but instead they undergo a stepwise trial-and-error treatment approach. This situation originates from three major knowledge and translation gaps: i.) we lack effective methods to identify individuals at risk for TR early in the disease process, ii.) we lack effective, personalized treatment strategies grounded in insights into the biological basis of TR, and iii.) we lack efficient processes to translate scientific insights about TR into clinical practice, primary care and treatment guidelines. It is the central goal of PSYCH-STRATA to bridge these gaps and pave the way for a shift towards a treatment decision-making process tailored for the individual at risk for TR. To that end, we aim to establish evidence-based criteria to make decisions of early intense treatment in individuals at risk for TR across the major psychiatric disorders of schizophrenia, bipolar disorder and major depression. PSYCH-STRATA will i.) dissect the biological basis of TR and establish criteria to enable early detection of individuals at risk for TR based on the integrated analysis of an unprecedented collection of genetic, biological, digital mental health, and clinical data. ii.) Moreover, we will determine effective treatment strategies of individuals at risk for TR early in the treatment process, based on pan-European clinical trials in SCZ, BD and MDD. These efforts will enable the establishment of novel multimodal machine learning models to predict TR risk and treatment response. Lastly, iii.) we will enable the translation of these findings into clinical practice by prototyping the integration of personalized treatment decision support and patient-oriented decision-making mental health boards.

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Topic(s)

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HORIZON-RIA - HORIZON Research and Innovation Actions

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Call for proposal

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(opens in new window) HORIZON-HLTH-2021-STAYHLTH-01

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Coordinator

UNIVERSITAET MUENSTER
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 3 753 831,71
Address
SCHLOSSPLATZ 2
48149 Muenster
Germany

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Region
Nordrhein-Westfalen Münster Münster, Kreisfreie Stadt
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 3 753 831,71

Participants (26)

Partners (4)

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