Agent-based modelling has emerged as a promising approach for studying cell signalling pathways due to its ability to grasp the critical role of local interactions within biochemical reactions. The flexibility of agent-based models allows for the emergence of complex behaviours from simple local rules, reducing the reliance on extensive experimental data. This potential can be harnessed to investigate the behaviour of mutated pathways in cancer and identify therapeutic targets for developing personalised treatments. In this study, we define an agent-based model to simulate the inhibitory effect of the targeted therapy drug dabrafenib on the BRAFV600E-MEK-ERK signalling cascade in melanomas. We tested an abstraction method that sets up the simulation in a three-dimensional environment but takes a slice of its volume to carry out the simulations. The model’s reliability is supported by validation against a clinical study, providing encouraging evidence for the use of agent-based models as in silico support in cancer therapy design.