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Diosdi, A.* ; Toth, T.* ; Harmati, M.* ; Istvan, G.* ; Schrettner, B.* ; Hapek, N.* ; Kovács, F.* ; Kriston, A.* ; Buzas, K.* ; Pampaloni, F.* ; Piccinini, F.* ; Horvath, P.

HCS-3DX, a next-generation AI-driven automated 3D-oid high-content screening system.

Nat. Commun. 16, 16:8897 (2025)

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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.

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