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Science Culture
I am Joint Lead of the Cambridge Mental Health Mission Mood Disorders Research Clinic; Deputy Lead of the Early Psychosis Workstream, Mental Health Translational Research Collaboration; Cambridge PI of the Early Psychosis Workstream, Mental Health Mission; Deputy Lead of Clinical Academic Training in Psychiatry, University of Cambridge; and an Early Psychosis Multi-arm, Multi-stage Platform Trial (PUMA) clinician. As a Clinical Lecturer in Psychiatry at the University of Cambridge, I investigate the landscape of early psychosis, schizophrenia, and mood disorders. My research focus centers on unraveling the psychiatric, immune, and cardio-metabolic dimensions of these mental illnesses. My approach combines psychiatric clinical informatics and data science. Through analysis of large datasets, I have constructed longitudinal “virtual cohorts” of psychiatric patients. These cohorts serve as powerful tools for characterising immune and metabolic markers across various stages of illness. The culmination of this work lies in the development of risk prediction models for health outcomes in psychosis. In particular, I’ve created a clinical risk prediction tool named MOZART, aimed at calculating the risk of treatment-resistant schizophrenia at the time of a first episode of psychosis. This work earned recognition, including the Schizophrenia International Research Society Early Career Award. My academic journey also includes a PhD in bioinformatics at Imperial College London, which focussed on the genetics of schizophrenia. Additionally, I have harnessed clinical research methods such as Magnetic Resonance Imaging and biomarker analysis to investigate cardiac and adipose tissue changes in schizophrenia. These investigations have led to a novel hypothesis regarding the potential etiology of cardiac alterations in this condition. Beyond research, I am deeply committed to medical education. I actively engage in teaching medical students and supervising research projects. Furthermore, I have introduced a resident doctor mentoring programme within the Cambridgeshire NHS mental health Trust. Looking ahead, my goal is to refine and validate MOZART further, leveraging larger datasets and industry collaborations. Ultimately, I aspire to integrate this valuable tool into clinical practice. As an academic clinician in psychiatry, I remain dedicated to advancing our understanding of mental illness and contributing to effective treatments.
MOZART: a risk prediction tool for treatment resistant schizophrenia
Commonly recorded clinical information at psychosis onset including blood markers can help predict whether a person will develop treatment resistant schizophrenia.
