Trials, Genomics and Prediction

Our theme in Trials, Genomics and Prediction aims to deliver a step-change in patient-centred, data-driven mental health research at scale.

Through our research we will increase the representation of study populations and incorporate data collected from wearables and smart phones, linking it to health records to allow real-time intervention, monitoring and dynamic prediction for patients.

We are improving clinical trials of new therapeutic interventions by developing efficient trial designs and linking to health records.

Our work in genomics is developing software pipelines for genomic prediction using polygenic scores, which are applicable across ethnicity and ancestry.

We are accelerating precision psychiatry through predictive models from genetic, clinical and psychosocial risk factors for disorder risk, prognosis and treatment response.

Researchers in our theme are developing methods for dynamic prediction that incorporate clinical and digitally-collected information which can be implemented in real-time systems.

Using our open-data science and collaborative research environment, we focus on creating code and software so that new methods can be demonstrated and implemented by the whole research community.

Theme Lead

NIHR Research Professor, Professor of Medical Statistics and Trials Methodology, King's IoPPN

Professor Richard Emsley

Deputy Theme Lead

Professor in Medical Statistics and Statistical Learning, King's IoPPN

Professor Daniel Stahl

Deputy Theme Lead

Professor of Genetic Epidemiology & Statistics, Head of Department, Social, Genetic & Developmental Psychiatry Centre, King's IoPPN

Professor Cathryn Lewis