Translational quantitative systems toxicology to improve the understanding of the safety of medicines - Sofia: 116030

ended

TransQST will develop a Quantitative Systems Toxicology (QST) approach, employing pre-existing data where possible, in order to yield new mechanistic insight into drug-induced toxicity. A central tenet of our programme will be to ensure the human physiological and pharmacological relevance of any test system that has been (or will be) used for generating the input data for modelling. By adopting this approach, we will be able to accurately interpret what happens when test systems are perturbed by drug exposure, and ensure translatability of modelling tools. Mechanistic translational biomarkers are a core aspect of our approach and will be applied in parallel with evidence for understanding how to develop, model and apply such biomarkers in a QST setting. The project is structured in 8 work packages to provide the following outcomes: curate the best available experimental data suitable for modelling adverse drug reactions; provide fit-for-purpose QST models that will address key toxicity measures for liver, kidney, heart and GI-tract; provide quantitative risk assessment for off-target toxicity in man based on in vitro and in vivo models; provide a quantitative mechanistic read-across from species (in vivo and in vitro) currently used for the toxicological evaluation of a new drug; provide definition and applicability of the human physiological relevance of preclinical test systems; provide a battery of translational biomarkers that can be used for quantitative read-across from in vitro systems to man and which relate to intracellular pathways (and systems) relevant to drug toxicity. Led by the University of Liverpool, TransQST brings together 14 partners, characterized by their scientific rigour and proven track record. Collectively they will enable achievement of the goals of the call, thanks to their complementarity, proven ability to work together (and with EFPIA partners), and their understanding of how to ensure the relevance of QST to human biology.