Dr Wahbi El-Bouri MEng (Hons), DPhil (Oxon), PGCert, AFHEA, MIET
Tenure Track Research Fellow, Digital Twins and in silico Clinical Trials Cardiovascular & Metabolic Medicine
- Work email W.El-Bouri@liverpool.ac.uk
About
Personal Statement
Keywords: Digital twins, in silico clinical trials, computational modelling, virtual physiological human
I joined the University of Liverpool and the Liverpool Centre for Cardiovascular Sciences in November 2020 as a Tenure Track Fellow in Digital Twins and in silico Clinical Trials. My background is in biomedical engineering, and as such I seek to use engineering principles, through in-silico modelling and data analysis, to help understand cardiovascular disease and its progression and for medical device and drug optimisation.
I completed my MEng (Hons) in Engineering at the University of Oxford in 2012 after which I went on to take up several jobs modelling heat pumps, hydroelectric dams, and assessing biofuel feasibility in India. I returned to Oxford shortly after to complete my DPhil in biomedical engineering, where my research focussed on multi-scale modelling of blood flow through the microcirculation in the human brain, with a focus on trying to link the ‘unobservable’ small scale vessels to observable clinical imaging through mathematical models. I completed my DPhil in 2017 and took up a research position at Southampton General Hospital and the University of Southampton where I worked on methods to measure intracranial pressure in patients non-invasively – specifically through measuring and analysing the movement of the eardrum. I returned to the University of Oxford in 2018 to take up a postdoctoral position on an EU funded Horizon 2020 grant entitled INSIST (In-silico clinical trials for the treatment of acute ischaemic stroke). This project aims to develop in-silico clinical trials to test mechanical thrombectomy devices on simulations of blood flow and metabolism in the entire human brain.
I joined the Liverpool Centre for Cardiovascular Sciences to work at the intersection of in-silico modelling, data science, and cardiovascular physiological understanding. The aim of my research is to develop in-silico models, informed by patient data, to develop personalised predictions for patient outcomes, as well as to develop population level in-silico clinical trials for various cardiovascular diseases and their treatments. The research will focus on translatability to patient populations to alleviate the burden of poor cardiovascular health.