Trials, Genomics and Prediction delivers a step-change in patient-centred, data-driven mental health research at scale.
Through our research we are increasing the representation of study populations and incorporating data collected from wearables and smart phones, linking it to health records to allow real-time intervention, monitoring and dynamic prediction for patients. For example, predicting how people might respond to a medication or someone’s health and lifespan.
We are developing efficient trial designs and linking to health records. This is improving clinical trials of new therapeutic interventions.
Our work in genomics is developing software pipelines for genomic prediction using polygenic scores, which are applicable across ethnicity and ancestry. Polygenic scores are calculated by looking at genetic variants across the genome to determine an overall risk of developing a disease.
We are accelerating precision psychiatry through predictive models from genetic, clinical and psychosocial risk factors for disorder risk, prognosis and treatment response.
Our researchers 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.
