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QUEEN MARY UNIVERSITY OF LONDON

QUEEN MARY UNIVERSITY OF LONDON

16 Projects, page 1 of 4
  • Funder: UK Research and Innovation Project Code: 10029402

    To exploit novel data analytic approaches to reduce premature death and disability from hypertension. The analysis of data from a customised App and system will safely enable the progressive introduction of automated clinical decision-making, for the precise control of drug dosing.

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  • Funder: UK Research and Innovation Project Code: 10045317
    Funder Contribution: 135,869 GBP

    To significantly improve the accuracy of a novel immunotherapy, through sophisticated in-vitro tumour models (containing tumour cells, non-tumour cells, and immune cells). This will help to accelerate Cancer therapy development.

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  • Funder: UK Research and Innovation Project Code: 10042867
    Funder Contribution: 97,106 GBP

    To develop standardised tests for microplastic risk assessment.

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  • Funder: UK Research and Innovation Project Code: 10079657
    Funder Contribution: 504,078 GBP

    In our fast-changing society, poor mental health and social isolation are increasing among young people, exacerbated by the pandemic. Belonging – feeling connected to and accepted by others through supportive interpersonal relationships – is key to boosting mental health and overcoming loneliness. There is a lack of evidence-based interventions addressing belonging, particularly in schools, which remains a central space for adolescent socialisation. Digital technologies, while disrupting the social landscape, offer enormous potential for adolescent health management. This project develops Augmented Social Play (ASP), a pioneering digital mental health intervention format whose feasibility has been established through proof-of-concept prototype. ASP uses smartphones to deliver real world group experiences that combine immersive storytelling, augmented reality, collaborative face-to-face gameplay and evidence based psychotherapeutic methodologies to boost individuals’ mental health while fostering a greater sense of belonging within the group. Collaborating across academia, industry, education, health and the arts, and working with young people, we will co-develop ASP #1, a full-scale, multi-session intervention. We will implement this intervention in schools in Portugal, Czechia, and the UK, using strategies informed by policy review, and evaluate its efficacy, cost-effectiveness and implementation in order to present an evidence base to stakeholders including policy-makers, practitioners and media, stimulating wide uptake. We will further evolve ASP by collaborating with vulnerable adolescents to ensure we meet the widest spectrum of needs; by prototyping additional ASP interventions aimed at different populations and threats to mental health; and by creating comprehensive ethical guidelines. Our long-term goal is wide-scale adoption of ASP, making multiple smartphone-delivered group mental health interventions freely accessible to diverse populations and settings.

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  • Funder: UK Research and Innovation Project Code: 95386
    Funder Contribution: 70,062 GBP

    To implement and generalise SpinX (an integrated image analysis framework for automated single-cell analysis of 3-dimensional spindle movements) on ZEISS's APEER to support a wider customer base.

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