Through the tumour labyrinth: developing a mechanistic understanding of blood flow and oxygen delivery in tumour vasculature

Blood flow patterns in tumour vasculature are known to be highly irregular, with the distribution of red blood cells (or haematocrit) showing marked deviations from those observed in healthy tissue vasculature. These abnormalities present a challenge for drug delivery and have been linked to tumour hypoxia and enhanced tumour angiogenesis.

To date, many of the available computational models of tumour blood flow describe blood as a homogeneous fluid and employ phenomenological rules to determine haematocrit changes at vessel bifurcations. This is, in part, due to the computational challenges associated with simulating haematocrit changes in a mechanistic way, i.e. by explicitly describing the transport of red blood cells (RBC) in plasma. Unfortunately, such simplified approaches fail to capture the complex haemodynamics encountered in tumours.

Co-supervisors Bernabeu and Krüger have recently developed an extension to the blood flow simulation platform HemeLB that enables the simulation of blood flow as a suspension of RBCs. Close collaborators in Oxford and Barcelona have considerable experience of simulating blood flow and oxygen distributions in tumours and have recently developed a microfluidics assay that recapitulates RBC dynamics in tumour vascular networks. Both computer simulations and microfluidics experiments are informed by novel intravital microscopy data of mouse tumour xenographs generated the Oxford team.

In this project, we aim to integrate data from computer simulations, microfluidic platforms, and intravital microscopy in order to develop a mechanistic understanding of blood flow and oxygen delivery in tumour vasculature. This knowledge will allow us to formulate a theory of transport in the tumour vasculature that is suitable for evaluating therapeutic vascular normalisation strategies.

Supervisors:
• Dr Miguel O. Bernabeu, Centre for Medical Informatics.
• Dr Timm Krüger, School of Engineering.

Requirements
A strong academic track record with a 2:1 or higher in a relevant undergraduate degree, or its equivalent if outside the UK. A strong performance in a relevant postgraduate degree is desirable. Proven experience in one or more of the following is desirable: mathematical modelling, computational fluid dynamics, image processing or competence in one scientific programming language (e.g. C++, Python, Fortran). The successful candidate will work in a highly interdisciplinary environment and should be able to work independently and as part of a distributed international team.
Following interview, the selected candidate will need to apply and be accepted for a place on the Usher Institute Medical Informatics PhD programme. Details about the PhD programme can be found here: https://www.ed.ac.uk/studying/postgraduate/degrees/index.php?r=site/view&id=924


Application procedure
Please provide a CV, a personal statement detailing your research interests and reasons for applying, degree certificate(s), marks for your degree(s) and 2 written academic references. All documents should be in electronic format and sent via e-mail to: [Email Address Removed]

For further information about the project contact the primary supervisor: [Email Address Removed]

The closing date for applications is 30 June 2018

Interviews will be held during July 2018.

The studentship will ideally begin in September 2018.