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"Horizon 2020 Programme" project MLTGI21028R
MLTGI21028R (964874) "Using real-world big data from eHealth, biobanks and national registries, integrated with clinical trial data to improve outcome of severe mental disorders" (1.06.2021−31.05.2025); Principal Investigator: Lili Azin Milani; University of Tartu, Faculty of Science and Technology, Institute of Genomics (partner); Financier: Commission of the European Communities; Financing: 444 000 EUR.
964874
MLTGI21028R
E-tervise, biopankade ja riiklike registrite reaalsete suurandmete kasutamine integreerituna kliiniliste uuringute andmetega raskete psüühikahäirete tulemuste parandamiseks
Using real-world big data from eHealth, biobanks and national registries, integrated with clinical trial data to improve outcome of severe mental disorders
Realment
1.06.2021
31.05.2025
R&D project
Horizon 2020 Programme
ETIS research fieldETIS research subfieldCERCS research fieldFrascati Manual research fieldPercent
1. Biosciences and Environment1.3. GeneticsB220 Genetics, cytogenetics 1.5. Biological sciences (biology, botany, bacteriology, microbiology, zoology, entomology, genetics, biochemistry, biophysics, other allied sciences, excluding clinical and veterinary sciences)33,0
3. Health3.1. BiomedicineB726 Clinical biology 3.1. Basic medicine (anatomy, cytology, physiology, genetics, pharmacy, pharmacology, toxicology, immunology and immunohaematology, clinical chemistry, clinical microbiology, pathology)34,0
4. Natural Sciences and Engineering4.16. Biotechnology relating to Natural Sciences and EngineeringT490 Biotechnology 2.3. Other engineering sciences (such as chemical, aeronautical and space, mechanical, metallurgical and materials engineering, and their specialised subdivisions forest products applied sciences such as geodesy, industrial chemistry, etc. the science and technology of food production specialised technologies of interdisciplinary fields, e.g. systems analysis, metallurgy, mining, textile technology and other allied subjects)33,0
PeriodSum
01.06.2021−31.05.2025444 000,00 EUR
444 000,00 EUR

Vaimsed häired on üks suurimatest koormustest Euroopa tervishoiusüsteemile, patsientide hulk on suur ja puuduvad tõhusad ravivõimalused. Paljudel ravimitel on tõsiseid kõrvaltoimeid ja rohkem kui kolmandik patsientidest ei reageeri ravile ootuspäraselt. Ravi optimeerimise aluseks on katse-eksituse põhimõte, mis kombineerituna erinevate ravimite koostoimetega ei anna soovitud tulemusi. Puuduvad uued ravimid koos uudsete terapeutiliste eesmärkidega samas kui olemasolevad on paljude inimeste jaoks ebatõhusad. Seetõttu oluline töötada välja uuenduslikud vahendid, et individualiseerida ravimist ning seega parandada kliinilisi tulemusi ja vähendada kulusid. REALMENT projekti peamine eesmärk on optimeerida vaimsete häirete ravi praegustel ravivalikutel põhineva uudse täppismeditsiini strateegiate loomise kaudu. Selleks kasutatakse nii andmeanalüüsi kui ka randomiseeritud kliinilise uuringu vahenditega. Arendatakse ka tehisintellekti ja masinõppe prognoosimis-ja stratifitseerimisvahendeid ning püüakse luua täppispsühhiaatria algoritmid.
Mental disorders represent one of the largest burdens for the European Health Care system, due to large number of patients and a lack of efficient treatment options. Today, drug treatment of mental disorders is characterized by severe a dverse effects andsuboptimal response in more than a third of the patients. Optimizing treatment is based on a trial-and-error approach, which combined with frequent multi-morbidities, often leads to polypharmacy and poor outcome. Due to limited understanding of the disease mechanisms that underlie mental disorders, new drugs with novel therapeutic targets are lacking, and existing treatments are ineffective for many people. It is therefore urgent that cutting-edge research approaches are deployed to develop innovative tools to individualize treatments using available psychiatric medication, and thus improve clinical outcomes and reduce costs for health care systems. The main goal of the multidisciplinary REALMENT project is to optimize treatment of mental disorders through novel precision medicine strategies based on current pharmaceutical options. Big data from populations (Nordic registries), cohorts (European biobanks), and eHealth samples (medical records), including whole genome genotypes (n=1.8 million), will be analysed in an EU-wide sustainable infrastructure using artificial intelligence and machine learning to develop prediction and stratification tools (precision psychiatry). These algorithms will be validated in large RCT data (n=10k) and re-phenotyping projects, and implemented in a clinical management platform (4MENT) which will be made available to provide decision support to clinicians to optimize therapeutic effects
Description in EstonianPercent
Basic Research50,0
Experimental Research0,0
Applied Research50,0
InstitutionRoleCountryTypeComment
CARDIFF UNIVERSITYpartnerGreat Britain
CorTechs Labs, IncpartnerUnited States
DNV GL ASpartnerNorway
HELSINGIN YLIOPISTOpartnerFinland
ISLENSK ERFDAGREINING EHFpartnerIceland
JANSSEN PHARMACEUTICA NVpartnerBelgium
KAROLINSKA INSTITUTETpartnerSweden
REGION HOVEDSTADENpartnerDenmark
SMERUD MEDICAL RESEARCH INTERNATIONAL ASpartnerNorway
STICHTING BURO ECNPpartnerNetherlands
STICHTING VUpartnerNetherlands
TARTU ULIKOOLpartnerEstonia
UNIVERSITA DEGLI STUDI DI BARI ALDO MOROpartnerItaly
Universitetet I OslocoordinaatorNorway
UNIVERSITETET I OSLOpartnerNorway