Virtual Organisations for Trials and Epidemiological Studies (VOTES) was funded (£2.8m) by the Medical Research Council (MRC) in the UK. The VOTES project investigated the application of Grid technologies to the clinical trial and epidemiological domains. Specifically VOTES focused upon: patient recruitment, data collection and study management aspects of clinical trials and epidemiological studies. As widely recognised, the clinical trials domain is a particularly challenging one in that potentially overlapping, dynamically varying, geographically distributed, heterogeneous groups of people, resources and data sets need to come together for given trials. In particular the virtual organisations for clinical trials have very strict security requirements on the data sets, the resources (DBs etc), who is allowed to see, use them, in what context etc. A paper describing the output of VOTES is given here.

Advanced Arterial Hypotension Adverse Event prediction through a Novel Bayesian Neural Network (AvertIT): was funded for 3-years (2m€) through the EU FW7 in 2008. The goals of AvertIT were to develop bed-side brain trauma systems that allow prediction of hypotensive events across 6 major neurological centres across Europe. Through integrating a variety of heterogeneous clinical data sets including real-time patient monitoring data sets (blood pressure, ECG etc), demographic data sets and laboratory/treatment data, and exploiting algorithms that have been trained through novel Bayesian algorithms, it is expected that hypotensive events in brain trauma patients can be identified with a 15 minute time window. This project undertook a large-scale multicentre clinical trial to judge the validity of the models put forward for adverse event prediction. A paper describing the output of AvertIT is given here.