Machine learning to predict human mesenchymal stem cell responses to bone graft substitute structure and local the mechanical environment in 3D in vitro ‘Tissue in a Tube’ bioreactors.

Description

Achieving reliable bone regeneration and fracture repair in all patients continues to challenge clinicians. The negative impact on patient recovery rates and ongoing quality of life, resulting from poor fracture repair, also presents health and social care systems with a significant financial burden. To address this challenge, a number of different synthetic biomaterials have been developed globally. Synthetic bone graft substitutes (BGS) such as Inductigraft™ was developed by researchers within QMULs School of Engineering and Materials Science (SEMS) collaboratively with Baxter Inc, to replicate the clinical success achieved by bone auto-grafting (without risking complications from retrieving donor bone from the patient). Whilst clinically successful in procedures such as spinal fusion, there is increasing interest in developing a deeper understanding of the mechanisms by which non-biologic BGS chemistry and structure can boost the rate and quality of bone regeneration and so translate into other areas of orthobiologic biomaterials innovation and personalised medicine.

This Barts NHS trust Biomedical Research Centre funded PhD studentship (https://www.qmul.ac.uk/nihr-bartsbrc/nihr-barts-brc-research-themes/precision-musculoskeletal-care/) will develop the use of machine learning in analysis of RNA Sequencing data to investigate the response of human mesenchymal stem cells (hMSC) seeded on Actifuse™ and Inductigraft™ BGS scaffolds within a 3D in vitro ‘tissue in a tube’ (TiaT) bioreactor system. The aim is to predict hMSC responses and osteogenic potential to variations in BGS pore characteristics and local environmental factors to inform the development of orthobiologic biomaterials based personalised strategies in musculoskeletal medicine. This exciting interdisciplinary project will be co-supervised by Prof Karin Hing, Prof Myles Lewis and Prof Simon Rawlinson, bringing together expertise in biomedical-materials engineering, clinical bioinformatics and cell mechanobiology

Eligibility

• The minimum requirement for this studentship opportunity is a good honours degree (minimum 2(i) honours or equivalent) or MSc/MRes in a relevant discipline.
• For 2024-5, the UKRI and Queen Mary stipend rate is £21,237;
• If English is not your first language, you will require a valid English certificate equivalent to IELTS 6.5+ overall with a minimum score of 6.0 in Writing and 5.5 in all sections (Reading, Listening, Speaking).
• Candidates are expected to start in January (Semester 2).

Contact

For informal enquiries about this opportunity, please contact Karin HING, Myles Lewis or Simon Rawlinson.

Apply

Start an application for this studentship and for entry onto the PhD Medical Engineering full-time programme (Semester 2 / January start):

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Please be sure to quote the reference “SEMS-PHD-603” to associate your application with this studentship opportunity.