Image from left to right: Elisa Passini, Cristian Trovato, Blanca Rodriguez.

What is UOXF´s main focus?
We are the Computational Cardiovascular Science Team, based at the Department of Computer Science of the University of Oxford (UK). Our expertise is in human-based computational modelling and simulation for in silico trials and cardiovascular research, to integrate and expand the information extracted from a range of experimental and clinical data. We have established collaborations across academia, pharma industry, clinicians, and regulatory agencies, to investigate the causes and modulators of variability in the response of the heart to therapies and disease. Our research lines include: data-driven modelling and simulation of human cardiac electrophysiology and electromechanics; human-based in silico trials for investigation of safety and efficacy of drug therapies; development of non-standard mathematical approaches for capturing biological variability; image-based anatomical modelling using cardiovascular imaging analysis.

How has participating in TransQST impacted your company?
The participation in TransQST gave us the opportunity to collaborate and work together with the numerous pharma companies included in the consortium. This allowed us to understand better the outstanding challenges in safety pharmacology and toxicology, and how our modelling and simulation methods can contribute to the field. It also helped us in understanding the industry perspective – quite different from the academic world.

What challenges has UOXF faced across the project? What are your main achievements in TransQST?
Our main challenge throughout the project has been to define the experimental data to use as inputs for our computer models, and to validate simulation results – and then to obtained them from the pharma companies in the consortium. These data come from previous experiments, and there have been quite a few discussions before we could reach an agreement on which compounds, animal species, and end-points it would have been best to focus on. Luckily, we already had numerous experimental data available from previous research, and this delay in receiving the data did not hinder the deliverables of the TransQST project.

Which TransQST outcome/s would you highlight? Why?
Within the heart work package, the main outcome of the TransQST project has been the development and validation of a computational framework to investigate drug-induced cardiotoxicity. Multiple models and corresponding validation studies have been developed and published during the course of the TransQST project, thus contributing to build confidence and disseminate the methodologies beyond the consortium.

What do you believe is the main contribution of TransQST in the field?
The main strength of the TransQST project is the fact that it has combined a large variety of expertise across academia and industry. The inclusion of multiple organs/systems gave the opportunity to understand the “bigger picture” of quantitative system toxicology, while also investigating a specific topic in detail, within each work package. These connections and collaborations will live beyond the end of the TransQST project, and will be very valuable to build further inter-disciplinary research projects.