HCS-3DX, a next-generation AI-driven automated 3D-oid high-content screening system
Ákos Diósdi, Tímea Tóth, Mária Harmati, István Grexa, Bálint Schrettner, Nora Hapek, Ferenc Kovács, András Kriston, Krisztina Buzás, Francesco Pampaloni, Filippo Piccinini, Péter Horváth
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. Standardisation of working with 3D cell cultures in high-content screening (HCS) approaches remains difficult. Here, the authors propose HCS-3DX, a system for HCS of 3D tumour models at single-cell resolution by combining micromanipulation, custom multi-well plates, advanced imaging and AI-based analysis.