Available
Project number:
2025_60
Start date:
October 2025
Project themes:
Main supervisor:
Professor of Genetic Epidemiology & Statistics
Co-supervisor:
Dr Angus Roberts, Senior Lecturer in Health Informatics, Department of Biostatistics & Health Informatics.
Additional Information:
Leveraging Electronic Health Records and Genetic Data for Personalized Antidepressant Treatment: A Causal Analysis Approach
The rising burden of mental health issues has led to a substantial increase in antidepressant prescriptions, with usage in England tripling between 1998 and 2018, accounting for 6% of all drugs dispensed. However, only one-third of patients respond to their first prescribed antidepressant, resulting in prolonged use and multiple medication trials. This highlights a critical gap in understanding antidepressant efficacy and treatment failure.
This PhD project aims to address this knowledge gap by analyzing electronic health records (EHRs) to assess treatment outcomes and integrate environmental, lifestyle, and genetic data to identify factors influencing individual responses. It will first utilize diagnosis codes and prescribing records from the Clinical Practice Research Datalink (CPRD) to create a comprehensive dataset of antidepressant use, examining treatment trajectories across depression episodes. Advanced algorithmic tools, including natural language processing (NLP), will be developed to analyze EHR data, generating metrics for treatment response and resistance. Descriptive and network analyses, as well as statistical models, will identify patterns in medication switching, trends, and differences in treatment responses based on demographic factors. Finally, the project will integrate EHR data with genetic information from the UK Biobank to explore biological mechanisms behind antidepressant outcomes. Causal analysis techniques like Propensity Score Matching and Causal Mediation Analysis will be employed to understand the direct effects of variables on treatment response.
This research will contribute to the development of personalized antidepressant prescribing, ultimately improving patient outcomes by uncovering patterns in treatment effectiveness.
We are now accepting applications for 1 October 2025
How to apply
Candidates should possess or be expected to achieve a 1st or upper 2nd class degree in a relevant subject including the biosciences, computer science, mathematics, statistics, data science, chemistry, physics, and be enthusiastic about combining their expertise with other disciplines in the field of healthcare.
Important information for International Students:
It is the responsibility of the student to apply for their Student Visa. Please note that the EPSRC DRIVE-Health studentship does not cover the visa application fees or the Immigration Health Surcharge (IHS) required for access to the National Health Service. The IHS is mandatory for anyone entering the UK on a Student Visa and is currently £776 per year for each year of study. Further detail can be found under the International Students tab below.
Next Steps
- Applications submitted by the closing date of Thursday 30 January 2025 will be considered by the CDT. We will contact shortlisted applicants with information about this part of the recruitment process.
- Candidates will be invited to attend an interview. Interviews are projected to take place in March 2025.
- Project selection will be through a panel interview chaired by either Professor Richard Dobson and Professor Vasa Curcin (CDT Directors) followed by informal discussion with prospective supervisors.
- If you have any questions related to the specific project you are applying for, please contact the main supervisor of the project directly.
For any other questions about the recruitment process, please email us at
