Prescribing the Right Agent for Depression in Adults (PRADA): an adaptive randomised trial using a web-based multi-modal clinical decision support system to personalise antidepressant treatment in routine healthcare globally

Grantholders

  • Prof Andrea Cipriani

    University of Oxford, United Kingdom

  • Prof Kamaldeep Bhui

    University of Oxford, United Kingdom

  • Prof Gerome Breen

    King's College London, United Kingdom

  • Dr Muhammad Husain

    University of Toronto, Canada

  • Dr Dung Jidong

    Mersey Care NHS Foundation Trust

  • Prof Taiwo Lateef Sheikh

    Ahmadu Bello University

  • Dr Qiang Liu

    University of Bristol

  • Lea Milligan

    MQ Mental Health

  • Prof Judit Simon

    Medical University of Vienna, Austria

  • Prof Nasim Chaudhry

  • Dr Georgia Salanti

    University of Bern

Project summary

Having developed a web-based tool that integrates socio-demographic and clinical measures, and includes patient preferences to personalise pharmacological treatment for depression in adults, we now aim to create an accessible multi-modal tool that will be scalable and widely usable by adding genetic predictors. We hypothesize it will result in better clinical outcomes. Pilot data show that easy-to-collect pharmacogenetic and polygenic score information can aid stratification of people experiencing depression. This can be collected using low-cost DNA-sequencing technology, in all clinical settings. A sequential, multiple-assignment, randomised (SMART) factorial trial with 2,055 depressed participants from Nigeria, Pakistan and UK will address these questions: (1) Can pharmacogenetic information personalise pharmacological treatment and improve real-world clinical outcomes? (2) What is the best adaptive therapeutic strategy in the early treatment process? (3) Can polygenic scores improve the long-term outcome of patients with depression? The primary outcome is treatment discontinuation at 8 weeks. We will also collect passive (sensor) and active (survey/questionnaire) outcome data on mood, anxiety and quality of life using mindLAMP (docs.lamp.digital) over 52 weeks. We will investigate the tool's acceptability and optimisation for different cultural contexts and gather insights regarding perception of depression. These data will support implementation globally, including low resource countries.