In work part-funded by the caLIBRAte project, the teams worked to utilize a ‘big data compacting and data fusion’ concept to capture diverse adverse outcomes on cellular and organismal levels, creating a ‘predictive toxicogenomics space’ (PTGS) tool. Within the paper, it is presented that PTGS explains dose-dependent cytotoxicity effects, provides a virtual cytotoxicity probability estimate intrinsic to omics data, predicts chemically-induced pathological states in liver resulting from repeated dosing of rats, and furthermore, predict human drug-induced liver injury (DILI) from hepatocyte experiments. Analysing 68 DILI-annotated drugs, the PTGS tool outperformed and complemented existing tests, leading to a hereto-unseen level of DILI prediction accuracy.
caLIBRAte partners Pekka Kohonen and Roland Grafstrom, from the Institute of Environmental Medicine, Karolinska Institutet are co-authors of an open access Nature Communications paper entitled "A transcriptomics data-driven gene space accurately predicts liver cytopathology and drug-induced liver injury".
DOWNLOAD the full paper here.