Abstract 4527: Dosing schedule effects on combination activity from first principles

Introduction Finding the ideal dosing schedule to optimize efficacy while balancing toxicity is a challenge for single agent clinical development, and takes on added complexity for combinations. In this work, we use theoretical modeling to investigate the role of schedule in determining combination activity, and propose a novel method of using dosing schedule to identify the in vivo interaction strength pre-clinically. Methods To evaluate the effect of schedule on tumor growth inhibition, we built a dynamic pharmacokinetic (PK)/effect (E) model to simulate tumor volume as a function of plasma concentration of a drug combination. The PK of each single agent was simulated using a one compartment model, and the inhibition of tumor growth rate was modeled as the sum of single agent effects and their product scaled by an interaction coefficient. We first simulated this model for various relative dosing frequencies and offsets between the two drugs to understand the relationship between schedule and activity for a synergistic combination. We next assessed the accuracy of estimating the interaction parameter using the activity discrepancy between in- and off-phase dosing schedules versus a traditional isobologram analysis. Using Fourier analysis of single agent PK profiles, we then identified an efficient study design to identify both the interaction parameter and optimal relative dosing schedule of the two drugs. Results Simulation of the PK/E model with parameter sweeps of dosing frequency and offsets led to a phase plot for combination activity showing peaks and valleys related to the concomitant exposure of the two drugs. From this, we surmised the interaction could be estimated based on the difference in tumor growth inhibition between schedules, and a comparison of in- and off-phase schedules performed well compared to isobologram analysis. Fourier analysis of simulated PK profiles of the two drugs revealed the concomitance as a function of dosing offset, and the pattern was maintained in the simulated activity. Using a study design with only four dose groups with different dosing offsets, we show it is possible to determine both the interaction coefficient (comparing one group at the peak and one at the valley of concomitance) and any effect of dose-ordering (two groups at different offsets but with the same predicted concomitance). Additionally, we demonstrate the difference in activity between synergistic and additive combinations manifests as beat frequencies present in the frequency spectrum, another possibility to identify synergy. Conclusions While combination development offers unique challenges, building an understanding of the PK/E relationship from first principles provides a framework to investigate drug interaction effects. The insights gained from studying combinations in vivo with a pre-clinical scheduling study may provide translational guidance on clinical questions around concomitance and dose-ordering. Citation Format: Andrew Chen, Jing-Tao Wu, Wen Chyi Shyu, Arijit Chakravarty, Christopher J. Zopf. Dosing schedule effects on combination activity from first principles. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4527. doi:10.1158/1538-7445.AM2015-4527