As discussed in our previous blog on this topic, cost effective high throughput transcriptomics, combined with advanced data interpretation, offers unique molecular insight for early toxicology screening.
Further to the launch of our high throughput transcriptomics platform in partnership with our parent company Evotec, Cyprotex continues to perform research in this exciting field and recently presented the poster ‘Transcriptomic profiling of in vitro 2D and 3D models to predict Drug Induced Liver Injury (DILI)’ at SOT 2021 and APT 2021.
DILI remains a leading concern for drug development and a major reason for drug withdrawals post market approval. Our transcriptomics DILI service combined with machine learning algorithms has been shown to advance DILI prediction from 70% to 82% with known DILI reference compounds and further offers mechanistic insight in to the adverse outcome pathway (AOP) and mode of action, greatly aiding drug development.
Our latest poster describes the work conducted to:
- Develop a database of known DILI and marketed compounds dosed in a variety of liver models including primary human hepatocytes, HepaRG cells, HepaRG 3D spheroids, human liver microtissues (hLiMTs) and primary rat hepatocytes
- Analyse cell models using high content imaging (HCI) and high throughput RNAseq, with human DILI liability prediction using artificial intelligence and machine learning
- Compile a database of DILI, marketed compounds, and mechanistic chemicals to be used to further predict the likelihood of DILI in new chemical entities (NCEs)
We demonstrate that transcriptomic data are highly reproducible and can be used to elucidate the mode of action of NCE’s and determine both off target and compound class effects. Combined with machine learning, this approach clearly demonstrates DILI predication with a higher degree of accuracy in comparison to using high content imaging alone.
To read more about our state-of-the-art transcriptomics platform, download our free publication; Drug Discovery Update #10, Transforming Toxicology Prediction via PanOmics.
Contact us to request a copy of the poster.
Get in touch to enquire about the transcriptomics assay.Tags: 3D models, DDI, toxicology, Transcriptomics