Supervisors: Dr Ruby Chang, Richard Piercy

Department: Comparative Biomedical Sciences / Clinical Science and Services 

Project Details:

The development of therapies for Duchenne Muscular Dystrophy (DMD) has been hampered by the inadequacy of existing functional outcome measures and associated benefits/harms on comorbidities. Many of the functional measures were not designed to capture the nuanced, multi-dimensional progression of DMD. The necessarily relatively short duration of placebo-controlled trials in DMD (typically no more than 12 months) can further limit the appreciation of clinically significant differences between patients on treatment and on placebo; this is especially true considering the function of dystrophin in protecting muscle from stress-induced damage that only becomes clinically relevant in the longer term. This project aims to address these challenges by systematically evaluating longitudinal patterns and phenotypic associations among functional assessments, skeletal and cardiac MRI, muscle histology, and blood biomarkers from our Wellcome Trust and MDUK-funded natural history study of DE50-MD dog datasets. 

We hypothesis that aligning outcome measures with the multifaceted nature of DMD will enhance the detection of treatment efficacy and improve clinical trial efficiency. By applying advanced analytical approaches to preclinical DE50-MD dog datasets, the study will inform both preclinical and clinical trial designs. This will also strengthen the analytical power and contribute to more effective animal research, with important ethical and financial ramifications.

References:

1. Hornby NL, Drees R, Harron R, Chang R, Wells DJ, Piercy RJ. Musculoskeletal magnetic resonance imaging in the DE50-MD dog model of Duchenne muscular dystrophy. Neuromuscul Disord. 2021 Aug;31(8):736-751.

2. Hildyard JCW, Riddell DO, Harron RCM, Rawson F, Foster EMA, Massey C, Taylor-Brown F, Wells DJ, Piercy RJ. The skeletal muscle phenotype of the DE50-MD dog model of Duchenne muscular dystrophy. Wellcome Open Res. 2022 Sep 23;7:238.

3. Riddell DO, Harron RCM, Hildyard JCW, Wells DJ, Piercy RJ. Evaluation of a six-minute walk test in the DE50-MD canine model of Duchenne muscular dystrophy and its effect on blood-borne biomarkers. [version 1; peer review: 1 approved, 1 approved with reservations]. Wellcome Open Res 2024, 9:681 (https://doi.org/10.12688/wellcomeopenres.23269.1)

4. Riddell DO, Hildyard JCW, Harron RCM, Wells DJ, Piercy RJ. Longitudinal assessment of blood-borne musculoskeletal disease biomarkers in the DE50-MD dog model of Duchenne muscular dystrophy. Wellcome Open Res. 2022 Aug 17;6:354

Requirements:

Essential

• Must meet our standard MRes entry requirements
• Undergraduate degree in a relevant field (e.g. Biology, Mathematics, Physics, Statistics)
• Demonstrated experience in applying quantitative methods to biological or clinical data
• Highly motivated, curiosity-driven, and able to work independently
• Ability to manage time effectively and meet deadlines

Desirable

• Experience with statistical and/or mathematical modelling
• Experience with R software environment for statistical computing and graphs
• Well-developed collaborative and communication skills
• Experience of scientific writing

Funding

Fully Self-funded: The MRes student will be expected to meet their course fees and living expenses. This is a desk-based data analysis and modelling project and will not incur other expenses

Please note that EU/EEA and Swiss national students may no longer be eligible for the “Home” rate of tuition fees, dependent on personal circumstances (including immigration status and residence history in the UK) and UK government rules which are currently being developed. For up-to-date information on fees for EU/EEA and Swiss national students following Brexit please see our fees and funding page.

How to Apply

Deadline: 8th May 2026

For more information on the application process and English Language requirements see How to Apply.

Interviews will take place remotely (Teams, Zoom etc) within 4 weeks of the closing date.

We welcome informal enquiries - these should be directed to ychang@rvc.ac.uk