A Scalable Micropatterned Organoid Platform for Quantitative Modeling of Human Forebrain Development and Disease

However, challenges of morphological variability and limited scalability restrict their use for high-throughput disease phenotyping and drug-screens. Here, we introduce a micropatterned organoid platform enabling reproducible and scalable generation of forebrain-like structures.

By integrating micropatterning with established cortical differentiation protocols, we generate reproducible, miniaturized brain organoids that are suitable for AI-based, quantitative phenotypic analysis. As a proof-of-concept, we model DYRK1A syndrome, a neurodevelopmental disorder characterized by microcephaly and autism spectrum disorder, using genetically engineered isogenic embryonic stem cells (hESCs) and patient-derived induced pluripotent stem cells (iPSCs).