Objective Kinase inhibitors (KIs) are a major class of highly effective anti-cancer drugs. Unfortunately, therapeutic use of KIs is often associated with cardiotoxicity (CT), a serious adverse condition which limits their use. This fellowship aims to develop mathematical systems pharmacology models for KI-induced CT. These models will be used to identify predictive CT signatures that will allow to decrease CT risk of new KIs. This innovative multi-disciplinary approach consists of integrating mathematical systems pharmacology modelling, with state-of-the-art experimental data generation. To this aim, KIs with different magnitudes of CT will be selected based on clinical adverse event databases. Human cardiomyocytes derived from pluripotent stem cells will then be treated with the selected KIs and in combination with CT modifying drugs. The effect of these treatments on changes on untargeted mRNA and protein expression will be measured and then analyzed using network modelling. This approach allows identification of key regulatory proteins. The selected proteins will then be quantified over time along with cardiomyocyte health markers. With this data, dynamical models will be developed to capture the relationship between exposure to KIs and the effects on protein expression and cardiomyocyte health over time. Ultimately these models will allow generation of predictive network-based dynamically-weighted signatures for CT.The fellow aims to establish himself as independent researcher in systems pharmacology. Training in state-of-the-art computational and experimental technologies at the leading systems pharmacology group at Mount Sinai in New York will fundamentally strengthen and broaden the experience of the fellow. This project will significantly contribute consolidate the career track of the fellow, foster future collaboration between Mount Sinai and Leiden University, and disseminate training in Europe. Fields of science medical and health sciencesbasic medicinepharmacology and pharmacydrug discoverynatural sciencesbiological sciencesbiochemistrybiomoleculesproteinsproteomicsmedical and health sciencesmedical biotechnologycells technologiesstem cellsmedical and health sciencesclinical medicineoncologybreast cancermedical and health sciencesclinical medicinecardiology Programme(s) H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions Main Programme H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility Topic(s) MSCA-IF-2014-GF - Marie Skłodowska-Curie Individual Fellowships (IF-GF) Call for proposal H2020-MSCA-IF-2014 See other projects for this call Funding Scheme MSCA-IF-GF - Global Fellowships Coordinator UNIVERSITEIT LEIDEN Net EU contribution € 242 929,80 Address Rapenburg 70 2311 EZ Leiden Netherlands See on map Region West-Nederland Zuid-Holland Agglomeratie Leiden en Bollenstreek Activity type Higher or Secondary Education Establishments Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Other funding € 0,00 Partners (1) Sort alphabetically Sort by Net EU contribution Expand all Collapse all Partner Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement. ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI United States Net EU contribution € 0,00 Address One gustave l levy place box 1075 10029 6574 New york See on map Activity type Higher or Secondary Education Establishments Links Contact the organisation Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Other funding € 160 130,40
