iCASE students apply for a specific project which has been designed by two supervisors - one from Warwick and one from an industry partner. They spend a minimum of three months based with their industry partner.
This doctoral training programme aims to create a new generation of researchers, capable of integrating quantitative and analytical methods to drive discovery and innovation in the biomedical, biotechnology and pharmaceutical sectors. The programme includes a one-year MSc in Interdisciplinary Biomedical Research and a three-year PhD supervised by internationally leading experts from the physical and biomedical sciences and industry.
Projects available for September 2021 entry:
Warwick supervisor: Prof. Nigel Stallard
Industry supervisor: Dr Fabio Rigat, Janssen Pharmaceuticals
In collaboration with Janssen Pharmaceuticals, this PhD project will address important questions in the optimal design of clinical development programmes in oncology. You will develop statistical modelling methods that describe the main sources of uncertainty in oncology clinical trials and formally incorporate stakeholder views, including clinical trial statistical properties and patient preferences, via multi-attribute utility functions. This will lead to strategies, including non-parametric Bayesian approaches, for optimal dynamic data-dependent updating of oncology clinical development programmes. The project gives a unique opportunity to embark on challenging biomedical statistics research in a pan academic-industry environment via the MRC iCASE studentship as part of the DTP in Interdisciplinary Biomedical Research. The project would suit a student with a good undergraduate degree in statistics, mathematics or a related discipline.
Warwick Supervisor: Prof. James Covington
Industry supervisor: Dr Emma Brodrick, IMSPEX Diagnostics
Respiratory conditions, including Covid-19, are a cause of major health concern worldwide. The current pandemic has focussed the need for rapid, accurate and point-of-care diagnostics to help manage and stratify patient care. Breath testing offer a means to fulfil this need. This project aims to further develop breath testing for the rapid diagnosis of respiratory infections, such as Covid-19, by measuring the chemical components, by mass spectrometry and artificial olfaction, in breath and relating these to the patient’s status.
Industry Supervisors: Dr Marcus Swann and Prof Steven Percival 5D Health Protection Group
Wound dressings are used to speed up the wound healing process while preventing infections. Ideally, wounds should be allowed to heal undisturbed, however the status of the wound needs to be evaluated regularly, to check for infection and enable rapid intervention. Even though antimicrobial dressings are available, their use can be detrimental and may be slowing down wound healing. The project aims to solve these issues through the development of smart dressing that can detect infections in real-time and allow for better wound management.
During the project, you will develop biological models to recapitulate infected wounds and test a range of sensor technologies to detect infection. You will then develop a smart dressing prototype based on the most appropriate sensor technology (including read-out) that is most suited for the application, taking manufacturing and assembly constraints into consideration.