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Big Data EEG-Analysis for Advanced Personalised Medicine in Depression

Periodic Reporting for period 1 - PREDICT (Big Data EEG-Analysis for Advanced Personalised Medicine in Depression)

Reporting period: 2019-05-01 to 2020-04-30

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 “Opti-Me” tool which predicts responsiveness to antidepressants and TMS treatment, and thus dramatically reduces time from diagnosis to amelioration of symptoms for MDD patients. Opti-Me 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. The project will contribute to the following activities: (i) Finalize design and development of the PREDICT technology; (ii) Perform a clinical validation for the technology in a multi-center clinical study in leading medical centers in Europe; (iii) Advance the PREDICT tool to commercialisation in Europe by revising the IP portfolio, prepare for CE Marking of the PREDICT system and first reimbursement requests.
Within the period, we have been working towards the optimisation of the Opti-Me system and tests ready for clinical trials. The software team identified additional neuromarkers and optimised the algorithms to ensure the most accurate and effective predictive tool. The test procedure was reviewed and refined and the final reports produced were improved. In addition, we have been active in promoting the project and the results achieved so far. We participated in several events across Europe and Asia, and had articles published in leading tech magazines.
The project aims at achieving clinical validation of the Opti-Me tool through a multi-centre clinical trial in leading medical centres in Europe and Israel. The trial is expected to start in the second stage of the project and reach a recruitment of up to 400 patients. The tool aims to effectively predict response to both antidepressants and TMS thereby shortening time to find the proper treatment and increasing quality of life. Opti-Me offers a paradigm shift in mental health with clear benefits to the patients, doctors and payers.
Testing of the Opti-Me platform