###Ultrasound Mediated Drug Delivery in 3D Advanced Pancreatic Cancer Models
Project ID: 2228bd1051 (You will need this ID for your application)
Research Theme: Healthcare Technologies
UCL Lead department: Division of Surgery and Interventional Sciences
Lead Supervisor: Pierre Gélat
Project Summary:
Pancreatic cancer is the fifth most common cause of cancer death in the UK. One characteristic of pancreatic cancer in humans is the presence of a dense fibrous stroma which may comprise up to 80% of the tumour mass. Even though chemotherapeutic agents have been shown to be effective in cells in vitro, their effectiveness in treating patients has been disappointing due to limited blood perfusion and insufficient drug delivery to the tumour.
Focused ultrasound is an emerging treatment modality which has been used to enhance the transport of therapeutic agents across vessel walls and their delivery to areas of the tumour with low vascular density. Maximising the potential of this technique will require a thorough understanding of the underlying mechanisms of the effects of focused ultrasound in tissues.
You will work alongside leading researchers in the fields of biomedical ultrasound and tissue engineering at the UCL Centre for 3D Models to develop new breakthroughs in the effective treatment of pancreatic cancer through: •Improved in vivo biomimetic models of the disease which address the limitations of 2D cell lines •Computational models capable of simulating the interactions between ultrasonic fields and fluid flow and drug transport within the tumour.
You will develop an experimental platform centred around polymeric scaffold based multicellular models of pancreatic cancer, exposing them to ultrasonic fields. Key biomarkers and hallmarks of disease progression will be correlated with ultrasonic and fluid flow parameters. This project will also involve the development of computational fluid mechanics models to support experiments and derive vital information relating to the mechanisms of drug delivery.
This is a highly interdisciplinary project, and applications are encouraged from a range of backgrounds. The experience of working with cell cultures and/or proficiency in applied mathematics, physics and computing (ANSYS, MATLAB, Python) will constitute a distinct advantage.