A qualitative approach to cell growth modeling and simulation for cancer chemotherapy

A qualitative model of cell growth that is based on qualitative process theory is presented. The model can be used to analyze the effects of the interaction of antiproliferative drugs on cells when the effects of each specific drug are known, which is useful when designing multidrug protocols for optimal cancer treatment. This model encompasses both structural and behavioral aspects. This makes it suitable for drawing conclusions about differences among different types of cell growth and about system behavior under different situations. adding some significant options with respect to closed-form cell cycle models. Moreover, qualitative modeling, unlike closed-form modeling, allows causal explanations of events: in this respect, the qualitative simulation presented-based on reasoning in terms of processes, individual views. and history limits-makes causes of specific behaviors even clearer than qualitative simulation based on constraints. This model is able to adapt to the amount of information supplied by the user: if this is scarce (only relating to the cell cycle phase on which each drug acts), the model will produce a simulation in which only cell cycle phase information for the combination is present; if the information supplied is more detailed, the simulation output will be more detailed as well.<
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