Abstract
We consider rule-based models extended with time-dependent reaction rates, a suitable formalism to describe the effect of drug administration on biochemical systems. In the paper, we provide a novel and efficient rejection-based simulation algorithm that samples exactly the trajectory space of such models. Furthermore, we investigate a model of drug administration in the context of a plaque-formation process of Alzheimer's disease, a polymerization process best described by a rule-based model to counteract the intrinsic combinatorial explosion of the underlying reaction network. Furthermore, time-dependent rates are needed to model the effect of drugs. We apply the simulation algorithm to study the efficacy of different drug administration policies.
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