A simple blood test to choose the best treatment for each patient with depression.
RxMine uses stem cell technology and machine learning to personalize antidepressant treatment, aiming to significantly reduce healthcare costs and improve patient outcomes for major depressive disorder.
Projectdetails
Introduction
Major depressive disorder affects around 300 million 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.
Current Challenges
Despite numerous available drugs, the following challenges persist:
- 75% of patients do not receive adequate treatment.
- 63% try multiple medications.
- 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 for healthcare systems.
Innovative Solution
RxMine revolutionizes this process by combining innovative technologies:
- Stem cell technology
- Genetics
- Neurobiology
- High-throughput screening
- Machine learning
These technologies are utilized to test multiple antidepressants and screen drug effects using a patient-specific brain-in-a-dish model.
Expected Outcomes
RxMine identifies the optimal antidepressant for each patient and has the potential to:
- Reduce hospitalizations by 89%
- Decrease emergency-room visits by 71%
- Lower depression-related healthcare costs by 40%, with savings of up to €6,000 per patient per year.
Financiële details & Tijdlijn
Financiële details
Subsidiebedrag | € 2.499.000 |
Totale projectbegroting | € 3.570.000 |
Tijdlijn
Startdatum | 1-6-2022 |
Einddatum | 31-5-2025 |
Subsidiejaar | 2022 |
Partners & Locaties
Projectpartners
- GENETIKAPLUS LTDpenvoerder
Land(en)
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Vergelijkbare projecten uit andere regelingen
Project | Regeling | Bedrag | Jaar | Actie |
---|---|---|---|---|
Subtype as a key to reduce heterogeneity of treatment effects in major depressive disorderSUBTREAT aims to enhance treatment for major depressive disorder by identifying subtypes through advanced data science, exploring their causes, and developing predictive algorithms for tailored therapies. | ERC Starting... | € 1.500.000 | 2022 | Details |
Focused Ultrasound Personalized Therapy for the Treatment of Depression (UPSIDE)The UPSIDE project aims to develop a minimally invasive hybrid neurotechnology for targeted brain stimulation and biomarker monitoring to enhance treatment for Treatment-Resistant Depression. | EIC Pathfinder | € 4.149.921 | 2022 | Details |
Kassadin-2Het project ontwikkelt een Early Warning algoritme voor terugvalpreventie bij depressie, geïmplementeerd in de eHealth applicatie Goalie, om recidive te verminderen en kosten te verlagen. | Mkb-innovati... | € 319.200 | 2017 | Details |
Identifying the Fast-acting Antidepressant Signatures of Treatment Response with psychedelic compounds using a novel behavioral tracking system and single-cell resolutionFASTer aims to revolutionize behavioral neuroscience by using advanced tracking and molecular techniques to identify brain circuits and genes involved in the rapid antidepressant effects of psilocybin. | ERC Starting... | € 1.500.000 | 2024 | Details |
Bidirectional Brain/Neural-Computer Interaction for Restoration of Mental HealthThis project aims to develop a portable neuromodulation system using quantum sensors and magnetic stimulation to precisely target brain oscillations for treating mental health disorders. | ERC Consolid... | € 1.999.875 | 2025 | Details |
Subtype as a key to reduce heterogeneity of treatment effects in major depressive disorder
SUBTREAT aims to enhance treatment for major depressive disorder by identifying subtypes through advanced data science, exploring their causes, and developing predictive algorithms for tailored therapies.
Focused Ultrasound Personalized Therapy for the Treatment of Depression (UPSIDE)
The UPSIDE project aims to develop a minimally invasive hybrid neurotechnology for targeted brain stimulation and biomarker monitoring to enhance treatment for Treatment-Resistant Depression.
Kassadin-2
Het project ontwikkelt een Early Warning algoritme voor terugvalpreventie bij depressie, geïmplementeerd in de eHealth applicatie Goalie, om recidive te verminderen en kosten te verlagen.
Identifying the Fast-acting Antidepressant Signatures of Treatment Response with psychedelic compounds using a novel behavioral tracking system and single-cell resolution
FASTer aims to revolutionize behavioral neuroscience by using advanced tracking and molecular techniques to identify brain circuits and genes involved in the rapid antidepressant effects of psilocybin.
Bidirectional Brain/Neural-Computer Interaction for Restoration of Mental Health
This project aims to develop a portable neuromodulation system using quantum sensors and magnetic stimulation to precisely target brain oscillations for treating mental health disorders.