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Conjugative plasmids are also the basic bricks for more complex applications in synthetic biology but despite of the high relevance, there are either no dependable technique readily available yet, which have been thoroughly tested and systematically validated against the experimental data or just an accepted standard to model the plasmid spread dynamics using single cell resolution.   We are primarily concerned, in this work, with providing a robust operational model for conjugation using an individual-based approach which can be easily adapted and used a standard modeling tool for simulating the kinetics of conjugative plasmids. In order to accomplish that goal we must bring to light some hidden aspects of conjugation which cannot be observed in whole population experimental setups and only can be detected at a single individual resolution. This approach has an added value because at the same time we produce a more dependable model we are providing useful hints about the local intra intracellular behavior of conjugation which certainly is useful to understand the process.  That is not an easy task because we have to make many assumptions and simplifications to provide a usable abstraction for the process. It has been used in other works as the model abstraction for conjugation, a set of rules relying on parameters like some arbitrary probability value, the pilus scan speed, the action radius of conjugative pili\cite{citeulike:10283930} or even simply the number of infected individuals on the neighborhood\cite{citeulike:3567840}.     As general rule good initial assumptions are those which are biologically consistent and could be almost axiomatically accepted. The assumptions which fall in this category are fundamentally that most of processes inside of any cell are uphill which basically means that they have fight against an energy gradient, in other words they have a cost. The second assumption is that cellular processes for healthy cells are subjected to some precise set of timing constraints for all cellular activities and any deviation on timers is disruptive for cellular activities.   In this work we introduce an individual-based model of bacterial conjugation constructed using a modular design which has been used to evaluate the better alternative for modeling and understand the conjugation systemically.  \section{Theoretical Framework}