Engineering Cells to Understand Cellular Transport

Many targets for the potential treatment of disease are located inside of the cell. Therefore, understanding how materials undergo internalisation is essential for informing the design of potential therapeutics to reach the desired intracellular target. This thesis records the development of novel methods to assess how materials are internalised into live cells. This includes a machine learning approach to identify internalised material in images of cells without requiring specialised sensors, and the use of gene editing to create tools for use in studying the pathways used by materials to enter the cell.