Implementation of a multi-OMICs workflow to derive human reference points and health-based guidance values (HBGVs) from quantitative in vitro data
Traditionally, food safety heavily relies on epidemiological data, which is often not available for new products, or on animal studies, which poses ethical issues regarding animal welfare and can only partly predict the human effects. To address these limitations, New Approach Methodologies (NAMs) are being developed worldwide. Among these, we have chosen to focus on microphysiological systems (MPS). Building on our experience with 3D multi-cellular in vitro models, this project will advance said models toward greater physiological relevance. The main challenge lies in managing the increased complexity associated with such sophisticated systems.
The project will develop advanced dual-organ microfluidic models combining lung–liver and intestine–liver systems to better reproduce human physiological responses to chemical exposure. These MPS will be coupled with a multi-omics approach, including transcriptomics, metabolomics, and epigenomics, to generate an integrated view of the biological processes involved. By combining these experimental data with a dedicated bioinformatics pipeline, the project aims to identify molecular mechanisms of action (MoA) and discover novel biomarkers associated with chemical exposure.
The innovative aspect of the project lies in the integration of physiologically relevant dual-organ microfluidic models with comprehensive multi-omics profiling and advanced bioinformatics analysis. LIST is responsible for the design, development, and qualification of the dual-organ microfluidic models, as well as for generating the biological samples for OMICs analyses.
Main deliverables include experimental OMICs datasets for 6 data‑rich chemicals (phase 1) and 25 data‑poor chemicals (phase 2), relevant to food and feed safety assessment, and a validated experimental workflow with an analysis pipeline to predict molecular mechanisms and derive reference points.
The main impact of the work lies in supporting the development of advanced methodologies for chemical safety assessment. The generated datasets and the validated workflow will contribute to improving mechanistic understanding of chemical toxicity and may facilitate the identification of reference points for safety assessment.
The results may support future Integrated Approaches to Testing and Assessment (IATA) for food and feed safety.
