The virtual assay software for human in silico drug trials to augment drug cardiac testing

https://doi.org/10.1016/j.jocs.2020.101202Get rights and content
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Highlights

  • Human in silico drug trials improve early predictions of drug-induced adverse cardiac events.

  • Translation process from academic methodology to software for pharma industry.

  • Key milestones for a successful translation to industry.

Abstract

Prediction of drug effects on the heart still represents a challenge in drug development, given potential adverse outcomes. Computer modelling and simulations of the human heart offer a powerful technology to augment existing animal and clinical methodologies. Here we describe the translation process that led to the development and uptake of Virtual Assay, a user-friendly software to perform in silico drug trials in population of human cardiac models. Through this work, we contributed to the uptake of in silico modelling and simulations in industry and regulatory paradigms, and demonstrated accurate and mechanistic predictions of drug-induced cardiac pro-arrhythmic toxicity.

Keywords

In silico drug trials
Virtual assay
Human cardiac computer models
Drug safety and efficacy testing
Arrhythmia

Cited by (0)

Elisa Passini Elisa obtained a PhD in Bioengineering from the University of Bologna (Italy) in 2015. She joined the Computational Cardiovascular Science group at the University of Oxford in 2013 as a visiting student, under the supervision of Prof. Blanca Rodriguez. She is now one of the senior postdoctoral researchers in the group. Her research focuses on prediction of drug-induced cardiotoxicity using computational models of human cardiac electrophysiology.

Xin Zhou Dr Xin Zhou obtained her BSc and MSc degrees from Beijing Normal University and her DPhil degree from University of Oxford. During her DPhil studies, she worked in the Computational Cardiovascular Science group at the Department of Computer Science, University of Oxford, supervised by Profs Blanca Rodriguez, Alfonso Bueno-Orovio, and Kevin Burrage. She carried on her studies as a postdoctoral researcher after graduating in 2016. One of her research interests is in silico evaluation of the proarrhythmic risk of drug therapies. She is also interested in multi-scale modelling of cardiac electrophysiology for acquired and congenital disease conditions, such as acute myocardial ischemia, myocardial infarction, heart failure and inherited channelopathies.

Cristian Trovato Cristian Trovato graduated in Biomedical Engineering at the University of Bologna in 2016. He is currently a final year PhD student in Computational Biology and Health Informatics at the Department of Computer Science (University of Oxford), under the supervision of Prof. Blanca Rodriguez and Dr. Elisa Passini. His research interests include the investigation of human cardiac Purkinje electrophysiology and its pro-arrhythmic potential, using biophysically-detailed computational models and multiscale simulations.

Oliver Britton Oliver Britton did his undergraduate degree in Physics, before joining the Systems Biology DTC, to switch fields for his DPhil. He did his DPhil as part of the Computational Cardiovascular Science group, supervised by Profs Blanca Rodriguez and Alfonso Bueno-Orovio. He is now working on applying the methodology developed during his DPhil to studying human sensory neuron electrophysiology for pain research.

Alfonso Bueno-Orovio Alfonso obtained his PhD from the University of Castilla-La Mancha (Spain, 2007) in modelling and simulation of human ventricular electrophysiology, followed by industrial experience and a post-doctoral position at the Technical University of Madrid. He then joined the Computational Cardiovascular Science group at the University of Oxford in 2010, in the development of synergistic data-driven approaches for cardiovascular research. His work covers the many facets of structural-function interplay and population variability in the human heart, where modelling and simulation are used to augment experimental and clinical findings to investigate cardiac arrhythmias and mechanisms of drug action under different pathological conditions. He is currently an Intermediate Basic Science Research Fellow of the British Heart Foundation and Associate Professor of Computational Medicine.

Blanca Rodriguez Blanca Rodriguez is Professor of Computational Medicine and Wellcome Trust Senior Research Fellow at the University of Oxford, in the Department of Computer Science. She is also Head of Computational Biology and Health Informatics, Chair of the EPSRC Impact Acceleration Partnership fund, and holds advisory positions in several national and international organisations and funding panels. Her research is on investigating causes and modulators of variability in the response of the heart to disease and therapies within the Computational Cardiovascular Science team (www.cs.ox.ac.uk/ccs). She is from Valencia, Spain, where she studied Engineering and graduated with a PhD in 2002. She then trained as a postdoc at Tulane University, and joined Oxford in 2004, initially as a senior postdoc and then holding several independent research fellowships and grants.