Fragment-based drug discovery (FBDD) is an efficient methodology for the generation of lead compounds. However, structure-based optimisation of weakly binding fragments into high affinity drug molecules often means that difficult synthetic challenges arise, hence there is a growing demand for cutting-edge synthetic methods and experimental techniques. This project focusses on machine-learning methodologies to more effectively plan and execute synthetic sequences to obtain desired target molecules mandated by FBDD optimisation.

Connor is currently an Assistant Professor of Chemical Engineering at the University of Nottingham Faculty of Engineering.