• Developed the first systems toxicology based classifier to predict the effects of engineered nanomaterials based on a combination of intrinsic and mechanism of action properties.
• Defined new hybrid approaches, based on omics data modelling and classical toxicology testing, to replace in vivo studies with in vitro assays to model the effects of engineered nanomaterials.
• Established strategies of multi-omics data modelling to define adverse outcome pathways (AOP) of engineered nanomaterials (ENMs).
• Developed the first biosignature-based read-across computational framework to link chemical exposures to human diseases.
• Discovered new key epigenomic motifs as potential therapeutic targets of cancers.
• Developed user-friendly software for omics data analysis and modelling to facilitate the integration of omics-derived evidence in chemical risk assessment.