Predictive Medicine
Predictive medicine is the development of tools to quantify and predict the probability of a disease, its treatment, and its impact on the individual.
Sheffield BRC embeds digital-data and technologies integrated with computational, physical and AI models into clinical trials of new treatments. These approaches are core to Sheffield’s Insigneo Institute for in silico Medicine, an internationally recognised centre-of-excellence with over 280 members (see below). Computational models and diagnostic /predictive AI algorithms from routine X-ray, angiography and CT images are at the heart of our approaches. We target a reduction in clinical trial size and de-risk drug development in diseases across our BRC Themes through cost-effective methodologies and sensitive endpoints (imaging, functional biomarkers, predictive modelling).
in silico medicine, also known as ‘computational medicine’, indicates modelling and simulation technologies that directly contribute to the prevention, diagnosis, prognosis, treatment planning and execution, and management of disease. in silico medicine technologies provide subject-specific predictions of quantities that are difficult or impossible to measure directly, but that are important to support the medical decisions about that patient.
Investigators
Dr. Andrew Swift
Dr. Paul Armitage
Prof. Damien Lacroix
Prof. Steven Sourbron
Prof. Visakan Kadirkamanathan
Prof. Julian Gunn
Prof. Karl Herholz
Dr. Haiping Lu
Prof. Stephen Matcher
Prof. Allan Lawrie
Prof. Ivan Minev
Prof. David Kiely
Prof. Daniel Coca
Prof. Li Su
Dr. Paul Morris
Dr. Samer Alabed
Dr. Mahnaz Arvaneh
Dr. Alex Rothman