Professor Martin Landray
MB ChB, PhD, FRCP, FHEA, FASN, FBPhS, FESC
Professor of Medicine and Epidemiology; Deputy Director, Big Data Institute
- MRC PHRU Programme Leader - Clinical Trial Service & Epidemiological Studies Unit
- Honorary Consultant Physician - Cardiology, Cardiac and Thoracic Surgery Directorate, Oxford University Hospitals NHS Foundation Trust
Martin Landray is Professor of Medicine and Epidemiology within the Nuffield Department of Population Health and Deputy Director of the Big Data Institute within the Li Ka Shing Centre for Health Information and Discovery.
His work seeks to further understanding of the determinants of common life-threatening and disabling diseases through the design, conduct and analysis of efficient, large-scale epidemiological studies (including clinical trials) and the widespread dissemination of both the results and the scientific methods used to generate them. He leads international trials that have enrolled over 65,000 individuals with cardiovascular or kidney disease from 18 countries across 4 continents, and the results of completed studies have changed regulatory drug approvals, influenced clinical guidelines and changed prescribing practice to the benefit of patients.
He leads the Health Informatics Hub for UK Biobank, a prospective cohort study of 500,000 middle-aged men and women, and the Big Data & Clinical Informatics theme for the Oxford Academic Health Science Centre.
He is heavily involved in efforts to streamline clinical trials, working with national and international organizations (including FDA, EMA, MHRA, MRC) to facilitate high quality research is efficient in providing robust information for healthcare decision-making. 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 has served as a member of the NIHR Commissioning Board and the External Reference Panel for the Ministerial (Biopharmaceutical) Industry Strategy Group Research through Health Data Programme, and is a member of the NHS Digital Research Advisory Group.
Martin 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 American Society of Nephrology, the British Pharmacological Society, and the European Society of Cardiology.
A policy model of cardiovascular disease in moderate-to-advanced chronic kidney disease.
Schlackow I. et al, (2017), Heart, 103, 1880 - 1890
Lowering LDL cholesterol reduces cardiovascular risk independently of presence of inflammation.
Storey BC. et al, (2017), Kidney Int
The Association of Serum Free Light Chains With Mortality and Progression to End-Stage Renal Disease in Chronic Kidney Disease: Systematic Review and Individual Patient Data Meta-analysis.
Fraser SDS. et al, (2017), Mayo Clin Proc, 92, 1671 - 1681
ELECTIVE CONVERSION TO SIROLIMUS VS. CONTINUED TACROLIMUS IN KIDNEY TRANSPLANTATION (THE 3C STUDY): RESULTS OF A RANDOMIZED TRIAL
Haynes R. et al, (2017), TRANSPLANT INTERNATIONAL, 30, 63 - 64
Biliary Tract and Liver Complications in Polycystic Kidney Disease.
Judge PK. et al, (2017), J Am Soc Nephrol, 28, 2738 - 2748
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