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3D Tumour-on-Chip Model to Predict the Efficiency of Anti-Cancer Drug Delivery from the Microvasculature

Research image

Efficient delivery of anticancer drugs into tumor tissues at maximally effective and minimally toxic concentrations is vital for therapeutic success. A tumour’s vasculature plays a pivotal role but, at present, only computational methods, or extremely simple physical 2D models, exist to predict the spatial and temporal distribution of drugs into a target tissue. Despite their simplicity, they are already challenging dogma. We propose a 3D tumour on chip model to comprehensively emulate a tumour’s microvasculature and better understand the effects such topologies have for the successful delivery of anticancer therapeutics. This work paves the way for building and applying functional 3D in-vitro human tumour models for oncology research, immunotherapy studies and drug screening.

Disciplines and Techniques
Project supervisor/s
Dr. Ali Salehi-Reyhani
Ali’s research focuses on the understanding and diagnosis of disease, with a specific interest in cancer.
King's College London
Dr. Martin Ulmschneider
Martin's research has developed a range of experimentally validated computational tools that allow atomic detail characterisation of the interactions of peptides with biological membranes, capturing the mechanisms of adsorption.
King's College University
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