Data-Driven Approaches to Understanding Heterogeneity in Type 1 Diabetes: Towards Better Prediction and Personalised Care

Project Code

PHS27Ex Young

Project Type

Dry lab

Research Theme

Population Health Science

Project Summary Download

Summary

Over 400,000 people in the UK live with type 1 diabetes. The condition is highly heterogeneous, with substantial variation in age at diagnosis, disease progression, treatment response, and risk of long-term complications. As disease-modifying therapies emerge and precision medicine become increasingly achievable, understanding this heterogeneity is critical. This PhD will use large-scale routinely-collected healthcare data and cutting-edge statistical approaches to characterise disease trajectories, develop risk prediction models, and identify factors associated with differential treatment outcomes. The findings will improve understanding of long-term outcomes in type 1 diabetes and provide evidence to inform risk stratification and personalised approaches to clinical care.

Can the project be completed part time?

Yes

Lead Supervisor

Dr Katherine Young

Lead Supervisor Email

k.young3@exeter.ac.uk

University Affiliation

University of Exeter

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