Research highlights - Informatics

Clinical Informatics

The major focus during 2013 – 14 has been to embed research into the implementation of the eHospital programme. This includes development of research functionality on Epic, including flagging data to a particular study, smart forms for study specific data collection, reports, condition triggered alerts to inform clinicians of eligible patients, subjects’ arrival and location in the Trust and significant events. An integration team is developing the ‘research gateway’, a user interface to access and interrogate the existing databases commencing with Epic, Joint Clinical Information System (JCIS), the transplant system, and the NIHR BioResource.  This will involve development of the necessary metadata and data linkages so that a researcher can build queries using tools that they are familiar with like Excel and Info Path that will retrieve data from across these silos without having to go through a data analyst.  Researchers will also be able to use the user interface to check quality and feasibility, and to make the study design, methods, and data accessible to present and future stakeholders. 


Working in close collaboration with the MRC Biostatistics Unit (BSU), the BRC is applying novel statistical approaches to projects within BRC themes:

Adaptive designs: IL-2 – the BSU and CCTU, in collaboration with Todd and Waldron-Lynch have designed an adaptive dose finding trial to investigate the dose of IL-2 that gives a 50% regulator T-cell response over baseline.

Dual-agent designs for phase I cancer trials – in collaboration with Professor Jodrell, BSU staff are investigating methodology for design and analysis of dual-agent dose escalation trials, and applying the methodology to a trial investigating an AK inhibitor in combination with paclitaxel.

Analysis of complex phenotypes: Linking MRI data with genetic data in multiple sclerosis – with Professor Sawcer, BSU staff are applying novel methodology that can link MRI and genetic data to investigate genetic causes of progression of multiple sclerosis (J Neurol 2014; Ann Clin Transl Neurol 2014).

Defining progression in phase II and III cancer trials – with Professor Eisen, BSU staff are investigating the issue of defining progression in phase II and III oncology trials. A methodology grant has been submitted to CRUK.

Biomarker driven inference: Biomarkers for prediction of breast cancer survival – with Professor Caldas. The association of 119 protein-based biomarkers with breast cancer survival has been tested using a newly developed Bayesian variable selection algorithm. Ongoing work on: (a) Predictive performance of the protein biomarkers above. Analysis conducted has shown a meaningful improvement over pre-existing risk factors. We are now exploring avenues to replicate. (b) Association with survival of novel biomarkers derived from Breast cancer tumour images using image processing algorithms developed by the Cambridge University astronomy group. Support to the analysis led by Dr Ali and Professor Caldas.


The BRC is supporting capacity building in Computational Biology and Bioinformatics, and providing leadership for two related NIHR initiatives, which require integration of phenotypic and genomic information; the NIHR BioResource and the NIHR Rare Disease Translational Research Collaboration. A key development has been the establishment of fellowships with the European Molecular Biology Laboratory - European Bioinformatics Institute (EMBL-EBI).