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

Akos Diosdi, Timea Toth, Maria Harmati, Grexa Istvan, Bálint Schrettner, Nora Hapek, Ferenc Kovacs, Andras Kriston, Krisztina Buzas, Francesco Pampaloni, Filippo Piccinini and Peter Horvath ()
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Akos Diosdi: HUN-REN Biological Research Centre (HUN-REN BRC)
Timea Toth: HUN-REN Biological Research Centre (HUN-REN BRC)
Maria Harmati: HUN-REN Biological Research Centre (HUN-REN BRC)
Grexa Istvan: HUN-REN Biological Research Centre (HUN-REN BRC)
Bálint Schrettner: HUN-REN Biological Research Centre (HUN-REN BRC)
Nora Hapek: HUN-REN Biological Research Centre (HUN-REN BRC)
Ferenc Kovacs: HUN-REN Biological Research Centre (HUN-REN BRC)
Andras Kriston: HUN-REN Biological Research Centre (HUN-REN BRC)
Krisztina Buzas: HUN-REN Biological Research Centre (HUN-REN BRC)
Francesco Pampaloni: Goethe-Universität Frankfurt am Main
Filippo Piccinini: IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) “Dino Amadori”
Peter Horvath: HUN-REN Biological Research Centre (HUN-REN BRC)

Nature Communications, 2025, vol. 16, issue 1, 1-16

Abstract: Abstract 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.

Date: 2025
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DOI: 10.1038/s41467-025-63955-5

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