Revolutionary high-resolution human 3D brain organoid platform integrating AI-ba...
Revolutionary high-resolution human 3D brain organoid platform integrating AI-based analytics
The long-term vision of the 3D-BrAIn consortium is to revolutionize personalized precision medicine for central nervous system (CNS)
disorders, by developing an innovative bio-digital twin model of the human brain that is personal...
The long-term vision of the 3D-BrAIn consortium is to revolutionize personalized precision medicine for central nervous system (CNS)
disorders, by developing an innovative bio-digital twin model of the human brain that is personalized, precise, and predictive.
In this pathfinder project we bring together three breakthrough technologies: 1) a novel, highly reproducible human brain modelling
technology using robust adherent iPSC-derived 3D cortical organoid cultures, 2) a unique, state-of-the-art 3D multi-electrode array
(MEA) technology for non-invasive high-resolution electrophysiological recordings and 3) a novel approach to analyse and interpret
the large quantities of functional data using tailored automated machine learning (ML)-based algorithms.
With this breakthrough approach we overcome significant hurdles that made it thus far impossible to create a truly representative
and functional model of the CNS for personalized medicine, drug screening and neurotoxicity testing. The revolutionary 3D-BrAIn
high-precision CNS platform will allow robust and accurate modelling of the CNS for a broad range of neuropsychiatric diseases.
Ultimately, the 3D-BrAIn technology will be translatable to multiple other organ systems (cardiomyocytes, pancreatic islets, retina), to
non-invasively obtain longitudinal 3D high-resolution electrophysiological recordings and effectively interpret them.
In this project a prototype of the 3D-BrAIn platform will be developed by growing functional 3D organoids that faithfully resemble
the human cortex on 3D MEA micropillar electrodes, enabling continuous functional monitoring and by developing ML-based
algorithms that can process and interpret the large spatiotemporal data sets. Once all individual components are optimized and
integrated, proof-of-concept will be obtained by validating the platform for two of the envisaged applications: CNS drug
development and neurotoxicity screening.ver más
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