Abstract 4310: Impact of drug combination schedules on the evolution of tumor resistance

Abstract

Abstract The emergence of drug resistance during treatment is a critical limiting factor for the long-term effectiveness of anticancer therapies. The use of drug combinations limits the emergence of resistance, thereby prolonging their therapeutic utility. The effect of a drug combination is dependent both on the concentration of the individual drugs and the extent of their interaction (synergistic, additive, or antagonistic). Thus, understanding the scheduling implications for efficacy can be valuable for optimizing tumor response and time to resistance for the combination. To examine this more closely, we used a pharmacokinetic/pharmacodynamic (PK/PD) modeling approach, coupling one-compartment PK models of two hypothetical drugs based on set synchronous or asynchronous (offset) schedules with an evolutionary model of tumor clone growth. We simulated four tumor subpopulations representing binary resistance to one or both drugs, using an exponential growth model with growth penalties based on drug concentrations. We used the model to simulate the effects of pairs of antagonistic, synergistic, and additive drugs on the growth of sensitive and resistant populations in a tumor. Final tumor volume and resistant population were used to compare the efficacy of various drug schedules. As expected, the effect of a drug interaction—either synergistic or antagonistic—is greatest when dosing is synchronous, as this results in the greatest simultaneous drug concentration. The effect of a drug interaction is proportional to the sensitive population size, so the effect of drug interactions decreases over time as the sensitive population is eliminated. Intuitively, the final tumor volume decreases as the strength of a synergistic interaction increases until the sensitive population is eliminated. The resistant populations are unaffected by the strength of the interaction for both antagonistic and synergistic combinations. Resistant populations are not affected by interactions between drugs to which they are resistant, so the growth of resistant populations over time is independent of drug interactions. Crucially, for effective drugs—that is, drugs that eliminate the sensitive population—synergy and antagonism converge to additivity as the sensitive population dies out because the remaining resistant populations are not affected by drug interactions. As synergistic and additive drug combinations are equivalent in the long-term, synergy and asynchronous dosing could be used to limit toxicity without sacrificing efficacy. The evolution of resistance also explains why in vitro synergy or antagonism may not translate in vivo. Taken together, our work provides several unintuitive insights about combination drug scheduling with practical implications for therapeutic design. Citation Format: Madison Stoddard, Andrew Chen, Lin Yuan, Debra Van Egeren, Dean Bottino, Arijit Chakravarty. Impact of drug combination schedules on the evolution of tumor resistance [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4310.