Abstract

A wide range of simulation and modelling methods are applied to support the drug discovery process. In this presentation we will review a spectrum of methods and consider their relative strengths and weaknesses, in light of the requirements for their practical application in an industrial environment. Ultimately, the value from computational methods is derived by making good decisions regarding the optimisation of compounds, leading quickly to a high quality drug candidate with a good chance of success in clinical trials. We will discuss some of the challenges that this presents, in particular the need to simultaneously balance several, often competing, factors; a process described as multi-parameter optimisation. Finally, we will draw some conclusions regarding the need for new methods and the challenges facing their adoption.