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Big Data EEG-Analysis for Advanced Personalised Medicine in Depression

Project description

Innovative personalised medicine diagnostic tool for major depressive disorder treatment

Major depressive disorder (MDD) is the leading most costly mental disorder, accounting for about 7 % of the European population. Current treatments are usually prescribed through trial and error, and patients rarely receive the correct treatment from the beginning. Israeli elminda has developed an innovative approach to predict responsiveness to antidepressants and transcranial magnetic stimulation (TMS) therapy for depression, aiming at dramatically reducing the time from diagnosis to amelioration of patient MDD symptoms. The EU-funded PREDICT project will develop this tool for personalised treatment of patients with MDD based on validated electroencephalogram and event-related brain-specific biomarkers.

Objective

Modern medicine has given us countless methods of understanding, measuring and managing such metrics of our health as temperature, weight, body fat percentage, cholesterol, PSA values, etc. A patient’s measured values are easily compared against well-established normal ranges. And yet a simple, non-invasive method for measuring and quantifying the health of our brains has eluded us. Being unable to accurately measure and compare how a brain functions hinders doctors’ ability to diagnose and treat suspected ailments. It also slows the substantiation of new therapies. And, just as importantly, it prevents each of us from truly understanding and taking ownership of the health of our body’s most important organ. Major Depressive Disorder (MDD) has been identified as the leading and most costly mental disorder, accounting for 33% of the total cost of brain disorders, and equal to 1% of the GDP. Each year, about 7% of the population suffer from MDD in Europe, equivalent to 52.98 million people. The current methods of treatment are prescribed through trial and error with patients rarely receiving the ‘right’ treatment from day one. This reduces response rates and delays remission, which has a heavy impact on the individual’s quality of life. elminda has developed the “PREDICT” tool which predicts responsiveness to antidepressants and TMS treatment, and thus dramatically reduces time from diagnosis to amelioration of symptoms for MDD patients. PREDICT determines personalised treatments for MDD patients based on validated electroencephalogram and event-related potential brain-related biomarkers. The tool predicts responsiveness to antidepressants and TMS treatment, and thus dramatically reduces time from diagnosis to amelioration of symptoms. This improves response rates, quality of life and results in significant savings for the healthcare systems.

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Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

SME-2 - SME instrument phase 2

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Call for proposal

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(opens in new window) H2020-EIC-SMEInst-2018-2020

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Coordinator

ELMINDA LTD
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.

€ 1 958 915,00
Address
Shenkar 1, WeWork Building
4673314 Herzliya
Israel

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SME

The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.

Yes
Activity type
Private for-profit entities (excluding 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.

€ 2 798 450,00
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