A spheroid whole mount drug testing pipeline with machine-learning based image analysis identifies cell-type specific differences in drug efficacy on a single-cell level
In summary, this underlines that a novel cell-type-specific single-cell analysis method can reveal critical insights regarding the mechanism of action of drug substances in three-dimensional cell culture models.
Authors
- Julia Jabs (ORCID: https://orcid.org/0000-0002-4915-9966)
- Mario Vitacolonna (ORCID: https://orcid.org/0000-0002-8599-1696)
- Markus Reischl (ORCID: https://orcid.org/0000-0002-7780-6374)
- Roman Bruch (ORCID: https://orcid.org/0000-0003-2910-7605)
- Rüdiger Rudolf (ORCID: https://orcid.org/0000-0002-0833-1053)
- Richard Schneider
- Mathias Hafner (ORCID: https://orcid.org/0000-0001-6222-4219)
Institutions
- Karlsruhe Institute of Technology (DE)
- Technische Hochschule Mannheim (DE)
- Merck KGaA, Darmstadt (Germany) (DE)
- University of Mannheim (DE)
- Heidelberg University (DE)
- University Hospital Heidelberg (DE)
- University Medical Centre Mannheim (DE)
Publication Details
- Journal
- BMC Cancer
- Published
- 2024-12-18
- DOI
- https://doi.org/10.1186/s12885-024-13329-9
- Citations
- 6
- Primary Topic
- 3D Printing in Biomedical Research
- Type
- article
- Field-Weighted Citation Impact
- 1.11