Automated spheroid generation, drug application and efficacy screening using a deep learning classification: a feasibility study.

ABSTRACT: The last two decades saw the establishment of three-dimensional (3D) cell cultures as an acknowledged tool to investigate cell behaviour in a tissue-like environment. Cells growing in spheroids differentiate and develop different characteristics in comparison to their two-dimensionally grown counterparts and are hence seen to exhibit a more in vivo-like phenotype. However, generating, treating and analysing spheroids in high quantities remains labour intensive and therefore limits its applicability in drugs and compound research. Here we present a fully automated pipetting robot that is able to (a) seed hanging drops from single cell suspensions, (b) treat the spheroids formed in these hanging drops with drugs and (c) analyse the viability of the spheroids by an image-based deep learning b

SUBMITTER: Benning L 

PROVIDER: S-EPMC7338379 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature