Schizophrenia is a severe psychiatric disorder that can have a devastating impact on the health, quality of life, and lifespan of affected individuals. It is also frequently highly disruptive for the health and wellbeing of their families. Around half of the people with schizophrenia do not achieve sustained benefits from their first treatment, and nearly a third of those with this disorder do not improve even after several treatments have been tried. While it is known that treatment response in schizophrenia is highly variable, it is not clear why this happens or what is the best way to clinically manage it. Additionally, in practice, tailoring treatment to individuals often involves numerous changes in medications, each requiring benefits to be balanced with the risks of adverse effects. This is a process that can take a long time, and which can exacerbate the disadvantages and disabilities that can accompany the disorder. Finding how to improve the process of treatment selection for people with schizophrenia is thus a research priority highly ranked by patients, carers, and clinicians.
Conducting this kind of research has been historically difficult to do as it requires large amounts of complex clinical data. Our group at Cardiff University has recently been able to overcome this major challenge by gathering large and diverse samples including thousands of individuals with schizophrenia. These are an invaluable resource for research, as they allow us anonymised access to genetic information and electronic records from the NHS. The main aim of this 4-year PhD project is to develop novel analyses, grounded in state-of-the-art health informatics, to follow the progress of these individuals throughout their treatment, revealing the real-world effects that medications have on specific psychiatric symptoms and adverse effects. This will ultimately be used to carry out the most detailed analysis to date on treatment response in schizophrenia and its relationship to clinical, demographic, and genetic factors. Results of this research are expected to illuminate new ways in which routine NHS data can be used to improve the safety and efficacy of antipsychotic drugs.
This project is supported by a “John Grace QC” scholarship from Mental Health Research UK and will be hosted by the schizophrenia research group at the MRC Centre for Psychiatric Genetics and Genomics at Cardiff University that is at the forefront of genetic research into this disorder, including recent work on cohorts with rich amounts of clinical data [PubMed ID: 31155017, 33168126, 33837784]. It is also embedded in an ongoing collaboration with Cardiff and Vale University Health Board to develop the research potential of electronic medical records in mental health [https://www.ncmh.info/resources/cris/]. Throughout the project, the PhD candidate will be mentored by Dr Antonio Pardiñas and Dr Sophie Legge on the statistical analyses of genetic and clinical datasets. The candidate will also acquire experience in the methodologies used for the Natural Language Processing of NHS clinical records, through a collaboration with Dr Jose Camacho-Collados, UKRI Fellow of the Cardiff University Data and Knowledge Engineering Group. Prof. Michael O’Donovan, lead of the Psychosis Research Theme of Cardiff University and co-chair of the Schizophrenia Working Group of the Psychiatric Genomics Consortium will oversee the project.
Entry Requirements
Applicants should possess a minimum of an upper second class Honours degree, master's degree, or equivalent in a relevant subject.
Applicants whose first language is not English are normally expected to meet the minimum University requirements (e.g. 6.5 IELTS)
International applicants are welcomed if the difference in fees can be covered.
How to apply
This studentship has a start date of October 2022. In order to be considered you must submit a formal application via Cardiff University’s online application service. You can access the application service at this link Medicine - Study - Cardiff University
There is a box at the top right of the page labelled ‘Apply’, please ensure you select the correct ‘Qualification’ (Doctor of Philosophy), the correct ‘Mode of Study’ (Full Time) and the correct ‘Start Date’ (October 2022). This will take you to the application portal.
In order to be considered candidates must submit the following information:
• Supporting statement
• CV
• Qualification certificates
• References x 2
• Proof of English language (if applicable)
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