In systems biology, the number of available models of cellular processes increases rapidly, but re-using models in different contexts or for different questions remains a challenging issue. In this paper, we study the coupling of different models playing a role in the mammalian cell cycle and in cancer therapies. We show how the formalization of experimental observations in temporal logic with numerical constraints can be used to compute the unknown coupling kinetics parameter values agreeing with experimental data. This constraint-based approach to computing with partial information is illustrated through the design of a complex model of the mammalian cell cycle, the circadian clock, the p53/Mdm2 DNA-damage repair system, the metabolism of irinotecan and the control of cell exposure to it. We discuss the use of this model for cancer chronotherapies and evaluate its predictive power with respect to circadian core gene knockouts .