Project Structure

Work Package	Leaders	Description
WP1 Consortium Management and Oversight	ULIV ABBVIE	Set up management structure. Guarantee the Project is implemented according to work plan and Scientific activities are managed efficiently. Manage resources, procedures and tools to ensure quality on results.
		Other contributors: UL, IMIM, SYNAPSE, ELI-LILLY
WP2 Communication, Dissemination and Regulatory Interactions	SYNAPSE ABBVIE BI	Ensure effective communication and work dynamics between participants. Promote dissemination of information and knowledge generated to relevant stakeholders. To ensure interaction with regulatory authorities.
		Other contributors: ULIV, UL, IMIM, UM, EMBL, UOXF, SIMCYP, UNIVIE, UKA, IFADO, OC, EMC, SARD, IRIS, ORION
WP3 Database, Knowledge Management and Interface	EMBL SARD BI	Define data management needs of model builders and users with Agile methodology. Develop database infrastructure supporting the needs of the model builders and model users. Identify, integrate, and curate relevant data from existing sources and new experiments. Disseminate and maintain project results in an efficient and sustainable manner.
		Other contributors: IMIM, UM, SIMCYP, UNIVIE, ABBVIE, IRIS
WP4 Systems Modelling Tecnologies	FIMIM AZ BI	Provide computational enabling technologies for building the TransQST systems modelling toolbox, that will constitute the building blocks to develop the models in different organs/systems within the project (heart, liver, kidney, GI; WP5-8), according to the data availability for each organ/system.
		Other contributors: ULIV, UL, UM, EMBL, UOXF, SIMCYP, UNIVIE, UKA, IFADO, ABBVIE, ELI-LILLY, SARD, GSK, IRIS, JANSSEN, ORION
WP5 Liver	ULIV ELI-LILLY	Incorporate PBPK and biological modelling approaches (e.g. weighted gene co-expression network analysis and genome scale metabolic modelling) to establish a framework for multi-scale quantitative systems toxicology modelling of drug-induced liver injury. The resulting model(s) will be translatable from preclinical species to man and encompass the dose-related progression from minor perturbation, through adaptation to toxicity. Initial proof of concept will be derived for two compounds, one which is expected to translate to human and the other that will not: acetaminophen (APAP), fialuridine (FIAU), respectively.
		Other contributors: IMIM, UM, EMBL, SIMCYP, UNIVIE, UKA, IFADO, ABBVIE, IRIS, ORION, VERTEX
WP6 Kidney	UL ELI-LILLY	Move away from descriptive transcriptomics at the level of single experiments and mechanistic characterization of single treatments to a fully integrated quantitative systems toxicology model that merge systems biology and PBPK modelling to form a basis for human translation for DIKI risk identified non-clinically. To demonstrate proof-of-concept for this overarching goal, we will focus on two main targets in renal toxicity: the proximal tubular system and glomeruli. We will build an integrated systems model of renal injury using available rat and mouse transcriptomic data.
		Other contributors: ULIV, IMIM, EMBL, SIMCYP, UKA, IFADO, ABBVIE, GSK, IRIS
WP7 Heart	UL GSK	Develop translational quantitative systems pharmacology/toxicology models to predict drug-induced cardiac toxicity “beyond QT”, integrating preclinical in vitro and in vivo safety data, PBPK models of exposure at the cardiac site of action, multi-scale computational models of cardiac (patho)physiology and real-life patient outcomes.
		Other contributors: IMIM, EMBL, UOXF, SIMCYP, EMC, ABBVIE, ELI-LILLY, SARD, AZ, IRIS
WP8 GI-Immune System	UM JANSSEN	Create mechanistic models that account for the proliferation and differentiation of cells in the intestinal epithelium parameterized with species-specific values for transcriptomic responses and a range of functional endpoints and biomarkers, thus enabling interspecies translation; Develop and apply approaches that incorporate in vitro toxicity data generated from relevant in vitro animal and human cell models (e.g. intestinal organoids) for interspecies scaling; Develop models that account for the interaction between immune cells and stem cells for predicting drug induced inflammation-mediated chronic GI toxicity.
		Other contributors: ULIV, UL, IMIM, EMBL, SIMCYP, OC, ABBVIE, AZ, GSK, IRIS
From 01/01/2017 to 31/08/2022