Understanding the therapeutic effect of drug dose and scheduling is critical to inform the design and implementation of clinical trials. The increasing complexity of both mono, and particularly combination therapies presents a substantial challenge in the clinical stages of drug development for oncology. Using a systems pharmacology approach, we have extended an existing PK-PD model of tumor growth with a mechanistic model of the cell cycle, enabling simulation of mono and combination treatment with the ATR inhibitor AZD6738 and ionizing radiation. Using AZD6738, we have developed multi-parametric cell based assays measuring DNA damage and cell cycle transition, providing quantitative data suitable for model calibration. Our in vitro calibrated cell cycle model is predictive of tumor growth observed in in vivo mouse xenograft studies. The model is being used for phase I clinical trial designs for AZD6738, with the aim of improving patient care through quantitative dose and scheduling prediction.

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Because of the importance of intracellular unbound drug concentrations in the prediction of in vivo concentrations that are determinants of drug efficacy and toxicity, a number of assays have been developed to assess in vitro unbound concentrations of drugs. Here we present a rapid method to determine the intracellular unbound drug concentrations in cultured cells, and we apply the method along with a mechanistic model to predict concentrations of metformin in subcellular compartments of stably transfected human embryonic kidney 293 (HEK293) cells. Intracellular space (ICS) was calculated by subtracting the [ (HEK-OCT1), 1.216 0.07 and 1.2560.06, respectively, were used to determine the intracellular metformin concentrations. After incubation of the cells with 5 mM metformin, the intracellular concentrations were 26.4 6 7.8 mM and 268 6 11.0 mM, respectively, in HEK-EV and HEK-OCT1. In addition, intracellular metformin concentrations were lower in high K + buffer (140 mM KCl) compared with normal K + buffer (5.4 mM KCl) in HEK-OCT1 cells (54.8 6 3.8 mM and 198.1 6 11.2 mM, respectively; P < 0.05). Our mechanistic model suggests that, depending on the credible range of assumed physiologic values, the positively charged metformin accumulates to particularly high levels in endoplasmic reticulum and/or mitochondria. This method together with the computational model can be used to determine intracellular unbound concentrations and to predict subcellular accumulation of drugs in other complex systems such as primary cells.