Self-organised three-dimensional (3D) cell cultures, collectively called 3D-oids, include spheroids, organoids and other co-culture models. Systematic evaluation of these models forms a critical new generation of high-content screening (HCS) systems for patient-specific drug analysis and cancer research. However, the standardisation of working with 3D-oids remains challenging and lacks convincing implementation. This study develops and tests HCS-3DX, a next-generation system for HCS analysis in 3D imaging and image evaluation. HCS-3DX is based on three main components: an automated Artificial Intelligence (AI)-driven micromanipulator for 3D-oid selection, an HCS foil multiwell plate for optimised imaging, and image-based AI software for single-cell data analysis. We validated HCS-3DX directly on 3D tumour models, including tumour-stroma co-cultures. Our data demonstrate that HCS-3DX achieves a resolution that overcomes the limitations of current systems and reliably and effectively performs 3D HCS at the single-cell level. Its application will enhance the accuracy and efficiency of drug screening processes, support personalised medicine approaches, and facilitate more detailed investigations into cellular behaviour within 3D structures.
Grants HUNRENTECH Horizon-BIALYMPH Horizon-SYMMETRY Horizon-SWEEPICS H2020-Fair-CHARM HAS-NAP3 TKCS PerMel-AI HUNTER-Excellence 2024 OTKA-SNN NKKP FIMM High Content Imaging and Analysis Unit Finnish Cancer Society MAECI Science and Technology Cooperation Italy-South Korea by the Italian Ministry of Foreign Affairs and International Cooperation Janos Bolyai Research Scholarship of the Hungarian Academy of Sciences Lenduelet BIOMAG