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In contrast to differential equations, P systems are an unconven- tional model of computation which takes into consideration the discrete character of the quantity of components and the inherent randomness that exists in biological phenomena. The key feature of P systems is their compartmentalised structure which represents the heterogeneity of the structural organisation of the cells, and where one can take into account the role played by membranes in the functioning of the system, for example signalling at the cell surface [13], selective uptake of sub- stances from the media [14], diffusion across different compartments [15], etc. We show here that P systems can be a reliable tool for Systems Biology and could even outperform in some cases the current simu- lation techniques based on differential equations. We will also use a strategy based on the well known Gillespie algorithm [4] but running on more than one compartment called Multi-compartmental Gillespie Algorithm [13].