• Professor Martin Landray, Professor of Medicine & Epidemiology and Deputy Director, Big Data Institute, University of Oxford

Associate Director

  • Professor Gil McVean, Professor of Statistical Genetics, Director, Big Data Institute, University of Oxford


Research initiatives

21st Century Clinical Trials
Principal Investigator: Professor Martin Landray

Our approach combines Electronic Health Records data for recruitment and long-term follow-up, protocol-specific software engineering to enhance protocol adherence, digital technology to capture physical and cognitive function with smartphones and sensors, and central statistical monitoring (key risk indicators, principal components analysis) to identify poor site performance. This initiative includes three sub-themes:

  • Facilitating recruitment (Professor Louise Bowman): feasibility, eligibility, invitation and consent management
  • Efficient assessment (Professor Will Herrington): ascertainment, adjudication, and analysis of trial outcomes
  • Appropriate regulation (Professor Martin Landray): clinical trial conduct and data access

Pathway to Impact: Success will be demonstrated through application to large trials in diabetes, cardiovascular and kidney disease supported by the National Institute for Health Research, the British Heart Foundation, and industry partners and will be exemplars for the UK Life Sciences Industrial Strategy.

Enhancing Prospective Cohort Studies
Principal Investigator: Professor Gil McVean

Prospective cohort studies (e.g. Million Women Study, China Kadoorie Biobank, UK Biobank) make increasing use of new Big Data approaches including linkage to routine health data, patient-oriented smartphone technology and remote sensors, multi-modal imaging, and high-throughput biochemical and -omic assays. Our work will address the challenge of converting large, multi-dimensional data into meaningful phenotypes. There are four sub-themes:

  • Remote phenotyping (Associate Professor Naomi Allen): Web-based platform for delivering questionnaires in large cohorts
  • Self-phenotyping (Dr Chris Hinds): patient-oriented systems to assess behaviour and performance
  • Integrated phenotyping (Dr Thomas Nichols): integrated assessment of functional decline
  • High throughput phenotyping (Professor Gil McVean): statistical pipelines for deriving clinical phenotypes

Pathway to Impact: Algorithms, software and tools will be evaluated in ongoing research cohorts and clinical studies and made available to the wider community.