PT  - JOURNAL ARTICLE
AU  - Christophe Deben
AU  - Edgar Cardenas De La Hoz
AU  - Maxim Le Compte
AU  - Paul Van Schil
AU  - Jeroen M. Hendriks
AU  - Patrick Lauwers
AU  - Suresh Krishan Yogeswaran
AU  - Filip Lardon
AU  - Patrick Pauwels
AU  - Annemie Bogaerts
AU  - Evelien Smits
AU  - Steve Vanlanduit
AU  - Abraham Lin
TI  - OrBITS: A High-throughput, time-lapse, and label-free drug screening platform for patient-derived 3D organoids
AID  - 10.1101/2021.09.09.459656
DP  - 2021 Jan 01
TA  - bioRxiv
PG  - 2021.09.09.459656
4099  - http://biorxiv.org/content/early/2021/09/11/2021.09.09.459656.short
4100  - http://biorxiv.org/content/early/2021/09/11/2021.09.09.459656.full
AB  - Patient-derived organoids are invaluable for fundamental and translational cancer research and holds great promise for personalized medicine. However, the shortage of available analysis methods, which are often single-time point, severely impede the potential and routine use of organoids for basic research, clinical practise, and pharmaceutical and industrial applications. Here, we report the development of a high-throughput automated organoid analysis platform that allows for kinetic monitoring of organoids, named Organoid Brightfield Identification-based Therapy Screening (OrBITS). The combination of computer vision with a convolutional network machine learning approach allowed for the detection and tracking of organoids in routine extracellular matrix domes, advanced Gri3D®-96 well plates, and high-throughput 384-well microplates, solely based on brightfield imaging. We used OrBITS to screen chemotherapeutics and targeted therapies, and incorporation of a fluorescent cell death marker, revealed further insight into the mechanistic action of the drug, a feature not achievable with the current gold standard ATP-assay. This manuscript describes the validation of the OrBITS deep learning analysis approach against current standard assays for kinetic imaging and automated analysis of organoids. OrBITS, as a scalable, high-throughput technology, would facilitate the use of patient-derived organoids for drug development, therapy screening, and guided clinical decisions for personalized medicine. The developed platform also provides a launching point for further brightfield-based assay development to be used for fundamental research.Competing Interest StatementThe authors have declared no competing interest.