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Martin Landray


Professor of Medicine and Epidemiology

  • Deputy Director, Big Data Institute
  • MRC Investigator
  • Lead, Big Data & Computing Innovation, MRC Population Health Research Unit
  • Lead, Clinical Informatics & Big Data, NIHR Oxford Biomedical Research Centre
  • Research Director, Health Data Research UK
  • Honorary Consultant Physician, Oxford University Hospitals NHS Foundation Trust

Prof Landray’s work seeks to further understanding of the determinants of common diseases chiefly through the design, conduct and analysis of efficient, large-scale clinical trials. He has led a series of major clinical trials to address major population health issues. These trials have enrolled over 100,000 individuals, producing results that have changed regulatory drug approvals, influenced clinical guidelines and changed prescribing practice to the benefit of patients.

Since March 2020, Prof Landray has been co-chief investigator of the RECOVERY trial (, the world's largest trial of potential treatments for patients hospitalised with COVID-19. The trial was established at pace – moving from first draft protocol to first patient enrolled in 9 days - and has gone on to enroll over 40,000 participants. The protocol is deliberately streamlined, making extensive use of routine healthcare data to minimise the burden on clinicians and patients in the context of the ongoing pandemic. Within the first 100 days, the trial reported that dexamethasone reduces mortality by about one third for patients requiring invasive mechanical ventilation and by one fifth for those requiring oxygen. The result was immediately adopted into practice in the UK and around the world and has subsequently saved hundreds of thousands of lives. The trial has since found two further treatments The trial has now enrolled over 43,000 patients, provided clear evidence that the immunomodulatory drug, tocilizumab, and a monoclonal neutralising antibody combination further reduce mortality among the sickest patients, again changing national and international guidelines. Just as importantly, the trial has demonstrated that many widely used treatments have no meaningful benefit in these patients - examples include hydroxychloroquine, convalescent plasma, azithromycin and colchicine.

He previously led NHS DigiTrials, a collaboration with NHS Digital to facilitate the safe and efficient use of NHS data for clinical trials. He is Chief Executive of Protas, a not-for-profit company focused on smarter randomised trials for better public health. He leads the Good Clinical Trials Collaborative ( in the development and implementation of guidelines for randomised controlled trials, supported by the Wellcome Trust and Bill & Melinda Gates Foundation. In 2021, he was appointed to the Pandemic Preparedness Partnership (PPP) leading to the publication of the G7 100 Days Mission to Respond to Future Pandemic Threats which recommended significant regulatory improvements to facilitate the rapid generation of relevant and robust results from innovative randomised controlled trials.

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 Department of Cardiology at Oxford University Hospitals NHS Trust. In 2021 he was elected Fellow of the Academy of Medical Sciences and was knighted for services to public health and science. 

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