MRC DTP in Precision Medicine

Using data science and advanced imaging on patient-matched mini-avatars to improve precision medicine approaches.

Supervisors

Professor David Bryant, School of Cancer Sciences, University of Glasgow

Professor Crispin Miller, School of Cancer Sciences, University of Glasgow 

Professor Neil Carragher, Institute of Genetics & Cancer, University of Edinburgh

Summary

This PhD project aims to advance precision medicine by using data-driven approaches to study cancer using organoids—miniature, lab-grown versions of patient tumours. Unlike traditional methods that rely on outdated cell lines, organoids closely mimic the unique characteristics of each patient’s cancer, making them powerful tools for developing patient-tailored therapies.  

The project focuses on developing innovative techniques to analyse these organoids, using advanced data science methods, including artificial intelligence (AI) and machine learning (ML). By applying these tools, the research will identify key patterns and insights into how different cancers grow, spread, and react to various drugs. This approach aims to discover new, personalised treatment strategies that are more effective for individual patients. 

The student will receive training in cutting-edge techniques, such as high-content screening for detailed cell observation, AI/ML integration for predictive modelling, and multi-omics analysis to explore the molecular details of tumours. By combining precision medicine with data science, this research aims to enhance our ability to match cancer treatments to the specific genetic and molecular features of each patient’s tumour, improving outcomes and paving the way for more personalised cancer care.