Elisa Passini
Dr Elisa Passini
Interests
My research interests include mathematical modelling of cardiac electrophysiology, by combining clinical and experimental data with modelling and simulation, to gain new insights into the ionic mechanisms underlying cardiac arrhythmias in humans.
I am particularly interested in variability and in understanding how this variability determines "When and Why?" patients may be at risk. By investigating the different responses to diseases and drug action, we aim to improve patient diagnosis and treatment.
I am currently working on human in silico drug trials in populations of cardiac action potential models, to identify new biomarkers of drug safety and efficacy.
This research promote the use of computer models for prediction of drug-induced arrhythmias at early stages of drug development, as a cheap and fast alternative to animal models.
I have been working on human hypertrophic cardiomyopathy, excitation-contraction coupling in human cardiomyocytes, and investigated how changes in the extracellular environment (e.g. electrolyte concentrations) may affect cardiac electrophysiology.
I'm a member of the Computational Cardiovascular Science group, which is part of the Oxford BHF Centre of Research Excellence.
Academic Links:
Research Gate | LinkedIn | Google Scholar | OrCiD
Awards:
- Sep 2017 - Technological Innovation Award, Safety Pharmacology Society Annual Meeting, Berlin (Germany)
- Jan 2017 - Recognition Award, University of Oxford (UK)
- Sep 2015 - Junior Travel Award, Safety Pharmacology Society Annual Meeting, Prague (Czech Republic)
- Jun 2015 - Travel Award and Best Poster Award, 39th Annual Meeting of the EWGCCE, Milan (Italy)
Biography
I obtained a MSc (Mar 2011) and a PhD in Bioengineering (May 2015) from the University of Bologna, Italy. During my PhD I visited the Computational Cardiovascular Science Team (Department of Computer Science, University of Oxford) to work on hypertrophic cardiomyopathy (Oct 2013- Dec 2014), and since Jan 2015 I joined the group as a postdoctoral Researcher with Prof. Blanca Rodriguez.
Selected Publications
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Phenotypic variability in LQT3 human induced pluripotent stem cell−derived cardiomyocytes and their response to antiarrhythmic pharmacologic therapy: An in silico approach
Michelangelo Paci‚ Elisa Passini‚ Stefano Severi‚ Jari Hyttinen and Blanca Rodriguez
In Heart Rhythm. Vol. 14. No. 11. Pages 1704–1712. November, 2017.
Details about Phenotypic variability in LQT3 human induced pluripotent stem cell−derived cardiomyocytes and their response to antiarrhythmic pharmacologic therapy: An in silico approach | BibTeX data for Phenotypic variability in LQT3 human induced pluripotent stem cell−derived cardiomyocytes and their response to antiarrhythmic pharmacologic therapy: An in silico approach | DOI (10.1016/j.hrthm.2017.07.026) | Link to Phenotypic variability in LQT3 human induced pluripotent stem cell−derived cardiomyocytes and their response to antiarrhythmic pharmacologic therapy: An in silico approach
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In silico trials in human ventricular and purkinje cell models predict safety and efficacy of 10 antiarrhythmic drugs
C. Trovato‚ E. Passini‚ A. Tissier‚ N. Nagy‚ A. Varro'‚ S. Severi and B. Rodriguez
In EP Europace. Vol. 19. No. suppl_3. Pages iii116–iii116. June, 2017.
Details about In silico trials in human ventricular and purkinje cell models predict safety and efficacy of 10 antiarrhythmic drugs | BibTeX data for In silico trials in human ventricular and purkinje cell models predict safety and efficacy of 10 antiarrhythmic drugs | DOI (10.1093/ehjci/eux140.007) | Link to In silico trials in human ventricular and purkinje cell models predict safety and efficacy of 10 antiarrhythmic drugs
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Human In Silico Drug Trials Demonstrate Higher Accuracy than Animal Models in Predicting Clinical Pro−Arrhythmic Cardiotoxicity
Elisa Passini‚ Oliver J. Britton‚ Hua R. Lu‚ Jutta Rohrbacher‚ An N. Hermans‚ David J. Gallacher‚ Robert J. H. Greig‚ Alfonso Bueno−Orovio and Blanca Rodriguez
In Frontiers in Physiology. Vol. 8. No. September. Pages 1–15. 2017.
Details about Human In Silico Drug Trials Demonstrate Higher Accuracy than Animal Models in Predicting Clinical Pro−Arrhythmic Cardiotoxicity | BibTeX data for Human In Silico Drug Trials Demonstrate Higher Accuracy than Animal Models in Predicting Clinical Pro−Arrhythmic Cardiotoxicity | DOI (10.3389/fphys.2017.00668) | Link to Human In Silico Drug Trials Demonstrate Higher Accuracy than Animal Models in Predicting Clinical Pro−Arrhythmic Cardiotoxicity