Project description
A blood test for antidepressant medication choice
Treatment of major depressive disorder is based on a trial-and-error approach, with patients trying several different medications and often without the desired response. This has a huge socioeconomic impact affecting millions of people who struggle to recover. Funded by the European Innovation Council, the RxMine project introduces a novel platform to assist the search of the best antidepressant for each patient. The process involves the analysis of a patient blood sample to predict the individual response to various medications. It is based on a brain-in-a-dish model that allows high-throughput screening of available drugs and machine learning to identify the most effective choice in a fast and effortless way.
Objective
Major depressive disorder affects around 300M people globally and is the second leading cause of disability, with up to 14 years of life lost per patient and an annual burden of up to €170 billion to the EU. Despite numerous available drugs, 75% of patients do not receive adequate
treatment, 63% try multiple medications, and a third do not respond after two rounds of treatment. This trial-and-error approach is destructive to patients, time-consuming for physicians and expensive to health care systems. RxMine revolutionizes this process by combining innovative stem
cell technology, genetics, neurobiology, high-throughput screening and machine learning to test multiple antidepressants and screen drug effects using a patient-specific brain-in-a-dish model. RxMine identifies the optimal antidepressant for each patient and potentially reduces
hospitalizations by 89%, emergency-room visits by 71% and depression related healthcare costs by 40% with savings up to €6,000 per patient per year.
Fields of science
- natural sciencesbiological sciencesneurobiology
- medical and health sciencesbasic medicinepharmacology and pharmacypharmaceutical drugs
- medical and health sciencesmedical biotechnologycells technologiesstem cells
- engineering and technologymedical engineeringmedical laboratory technologylaboratory samples analysis
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Keywords
Programme(s)
- HORIZON.3.1 - The European Innovation Council (EIC) Main Programme
Funding Scheme
HORIZON-EIC-ACC-BF - HORIZON EIC Accelerator Blended FinanceCoordinator
6744332 Tel Aviv
Israel
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.