Our BRC is underpinned by world-leading informatics and data sciences in pursuit of medicine that is: predictive, preventive, personalised and participatory.
We will enhance the collection, collation and analysis of data from multiple sources to find groups of patients who have distinctive patterns of disease, or different responses to treatment, but who are currently managed as if they had the same condition.
Patient-driven data from mobile and wearable technologies will play an increasing role in our research. Such technologies enable frequent measurement of disease and lifestyle patterns.
Computerised connections between patients, clinicians and researchers also provide smarter ways to run experiments. Our recruitment of patients into studies will be based on analysis of linked digital records, and we will use the same links between information systems to enhance the monitoring of study participants.
We will also investigate new ways to feed data analyses into the health and care decisions of patients and clinicians. Making complex information useful to the right decision-maker at the right time is a challenge for experimental medicine, particularly where information and health behaviours interact.
Our BRC will integrate these data-intensive methodologies across its research themes through a managed methodology research hub and shared e-infrastructure – creating a cohesive and responsive culture.
There is a lead methodologist embedded in each theme, to combine biomarker and phenomarker modelling activities in a concert of bioinformatics, biostatistics, health economics and health informatics.