Biofilms are highly organized structures coordinately formed by multiple species of bacteria. In vivo biofilm formation has been observed in a variety of clinically significant problems and pose a serious problem in human health because they are highly resistant to antimicrobial agents and are extremely difficult to eradicate once they are fully developed. Therefore, understanding the mechanisms involved in the formation of biofilms is important for developing effective strategies for eradicating biofilms. Quorum sensing (QS) is one cell-cell communication mechanism that is used by bacteria during biofilm formation. QS-based communication in oral biofilms is extremely complex, as they contain several hundred species that dynamically interact in a specific sequence of colonization events to form spatially organized biofilm communities. Despite the spatial and temporal nature of oral biofilm formation, very little information is available on the role of spatio-temporal aspects of QS during oral biofilm development. We have developed a mathematical model to guide approaches to disrupt QS spatio-temporal dynamics and thereby, biofilm formation. This is important as biofilms are non-uniform along their length and depth; therefore, in order to present accurate gradients of external QS molecules to the biofilm, we have considered these heterogeneities. The key features of the model and important assumptions are (1) the production rate of quorum sensing molecule was modeled as Fisher growth kinetics that consists of a feedback regulation mechanism, (2) the QS molecule removal from the biofilm by the flow was modeled as a mass transfer coefficient, k, and is proportional to the concentration difference of QS molecule between the biofilm and the bulk fluid flow, (3) the concentration of QS molecule in the bulk fluid could vary with time and x-position (4) the initial concentration distribution of the QS molecule in the biofilm could be prescribed, (5) the biofilm was assumed to be homogeneous and of constant thickness, d, (6) bacterial growth rate is represented in the form of QS molecule production rate; no separate population dynamics for bacterial growth was used. The resultant partial differential equation is non-linear; therefore, a numerical scheme involving finite- difference discretization of the equations was utilized to solve the model. The ratio of the biofilm thickness (~250 microns) to its width was assumed to be 0.2. The initial concentration of QS molecule was set to be uniform throughout the biofilm. The bulk fluid QS concentration was set to be zero. The parameters Da and g were varied to study the effect of production and removal rates of QS molecule. The model simulations for Da=10 and g=10 show that the concentrations do not vary much across the width of the biofilm. This could be because the value of b was set at 0.2 which makes the axial dependency weak. More importantly, we set the bulk fluid concentration to be uniformly zero across the width of the biofilm (mimics a scenario when there are no QS molecules in the bulk fluid on top of the biofilm). When a sinusoidally varying concentration of QS molecule is imposed across the width of the film in the bulk fluid, it was observed that the concentration profiles of QS molecules are altered not only at the surface but also throughout the depth of the biofilm. Our QS model is expected to lead to approaches for selectively disrupting QS spatio-temporal dynamics using general QS disruptors or antagonists to QS molecules.