Part 7. Automating liver cancer organoid drug screens

Tijmen Booij
About Presenter: Tijmen studied Bio-Pharmaceutical Sciences at Leiden University in the Netherlands and performed his PhD degree on the topic of phenotypic screening of 3D cell cultures, with a focus on Polycystic Kidney Disease, in the Leiden Academic Centre for Drug Research (LACDR). During his PhD studies, Tijmen learned to work with various 3D-cell culturing techniques, phenotypic screening, and lab automation. After completing his PhD studies in 2017, Tijmen moved to Zürich to work as screening specialist for the NEXUS theragnostics discovery unit, a technology platform of ETH Zürich. Here Tijmen is currently responsible for assay development, with a focus on advanced cell-culture models, and for maintaining the in-house compound collection, and has over the past three years developed fully automated 3D-cell culture and organoid high-throughput screens at NEXUS.

Take a look of this webinar by Dr. Tijmen Booij, ETH Zurich NEXUS, to see a case example of patient-derived liver cancer organoid drug response screening. The workflow is done with automation and in 1536 well-format with proven reproducibility.

Over the last years, drug screens with organoids have gained in popularity due to their improved physiological relevance, which is expected to reduce the number and size of in vivo studies that are required to confirm in vitro results.

Currently most organoid screens are being performed in the range of hundreds to perhaps a few thousand compounds per screen. From the technical perspective, setting up high-throughput screens with organoids is still a challenge. On the one hand this is due to the availability of sufficient organoids, but on the other hand also because of the reagents that are traditionally used.

As technology platform of the ETH Zürich, NEXUS has over the last couple of years performed several successful organoid screens for different disease systems, where we observed that animal-derived hydrogels are a consistent source of variation and additionally complicate the automation of screening assays.

To improve throughput and remove potential sources of variation in our organoid screens, we optimized screening conditions using organoid models for Hepatocellular Carcinoma with UPM Biomedicals’ GrowDex and GrowDex-T. We report the successful adaptation of our organoid screening methodology for these HCC organoid lines, and expect that a similar conversion will be possible for many other organoid types.


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