Professor Martin Landray
- Accurately estimating the burden of vascular disease using electronic health records
- Analysing big data from electronic health records to understand the determinants of cardiovascular disease
- Big Data Institute (BDI)
- Deep phenotyping of vascular events in large-scale epidemiological studies using electronic health records
MB ChB, PhD, FRCP, FHEA, FASN, FBPhS, FESC
Professor of Medicine and Epidemiology
- Research Director, Health Data Research UK
- Deputy Director, Big Data Institute
- Lead, Big Data & Computing Innovation, MRC Population Health Research Unit
- Lead, Clinical Informatics & Big Data, NIHR Oxford Biomedical Research Centre
- Lead, Health Informatics Hub, UK Biobank
- Honorary Consultant Physician, Oxford University Hospitals NHS Foundation Trust
Prof Landray’s work seeks to further understanding of the determinants of common diseases through the design, conduct and analysis of efficient, large-scale clinical trials and prospective cohort studies (including UK Biobank). He has led a series of major clinical trials assessing treatments for cardiovascular and kidney disease. These have enrolled over 65,000 individuals, producing results that have changed regulatory drug approvals, influenced clinical guidelines and changed prescribing practice to the benefit of patients.
He is heavily involved in efforts to streamline clinical trials, working with regulatory agencies to facilitate efficient and cost-effective trials. He is a member of the Steering Committee of the FDA Clinical Trial Transformation Initiative, leading the Monitoring, Quality by Design, and Mobile Clinical Trials projects. He is a member of the NHS Digital Research Advisory Group and the NICE Data & Analytics External Reference Group, and leads the 21st Century Clinical Trials programme for Health Data Research UK.
Prof Landray completed medical training at University of Birmingham (UK) and specialist training in Clinical Pharmacology & Therapeutics, and General Internal Medicine at University of Birmingham. He continues to practise clinical medicine as an Honorary Consultant Physician in the Cardiology, Cardiac and Thoracic Surgery Directorate at Oxford University Hospitals NHS Trust. He is a Fellow of the Royal College of Physicians of London, the Higher Education Academy, the British Pharmacological Society, and the European Society of Cardiology.
Assessement of Vascular Event Prevention and Cognitive Function Among Older Adults With Preexisting Vascular Disease or Diabetes: A Secondary Analysis of 3 Randomized Clinical Trials.
Offer A. et al, (2019), JAMA network open, 2
Efficacy and safety of statin therapy in older people: a meta-analysis of individual participant data from 28 randomised controlled trials.
Cholesterol Treatment Trialists' Collaboration None., (2019), Lancet (London, England), 393, 407 - 415
Erratum: Evans M, Grams ME, Sang Y, et al., for the Chronic Kidney Disease Prognosis Consortium. Risk factors for prognosis in patients with severely decreased GFR.(Kidney International Reports (2018) 3(3) (625–637)(S246802491830007X)(10.1016/j.ekir.2018.01.002))
Astor B. et al, (2018), Kidney International Reports, 3
Grams ME, Sang Y, Ballew SH, et al, for the Chronic Kidney Disease Prognosis Consortium. Predicting timing of clinical outcomes in patients with chronic kidney disease and severely decreased glomerular filtration rate. Kidney Int. 2018;93:1442-1451.
Chronic Kidney Disease Prognosis Consortium None., (2018), Kidney international, 94, 1025 - 1026
Relationship of Estimated GFR and Albuminuria to Concurrent Laboratory Abnormalities: An Individual Participant Data Meta-analysis in a Global Consortium.
Inker LA. et al, (2018), American journal of kidney diseases : the official journal of the National Kidney Foundation
IN the News
Lectures, webcasts and interviews
Big Trials, Big Data, Big Potential: population health research in the 21st century
Inaugural Lecture, University of Oxford, November 2015
New Technologies for Healthcare Research
Oxford Martin School, University of Oxford, January 2016
Big Data for Efficient Clinical Trials
National Academy of Medicine, Washington DC, October 2015
Big Data in Biomedicine
Interview, Stanford Medicine, May 2015
Quality by Design for Clinical Trials
Clinical Trial Transformation Initiative, Bethesda, April 2015
Big Data in Biomedicine
Interview, Stanford Medicine, May 2014
Big Data and Drug Discovery
University of Oxford Alumni, October 2013