Network topology dictates sequential drug efficacy through bistability-mediated state switching

Sequential drug combinations can significantly enhance therapeutic efficacy, yet the general principles governing when and why sequential administration outperforms concurrent treatment remain poorly understood. While empirical evidence demonstrates that the order and timing of drug exposure can be critical, a mechanistic framework to predict which regulatory architectures are primed for sequential benefit is currently lacking. Here, we systematically enumerated and dynamically analysed 59,040 four-node network topologies to identify the structural design principles that dictate sequential efficacy. Our analysis reveals that only a small fraction of network architectures robustly confer a sequential advantage and identifies a minimal structural requirement for this benefit: a positive feedback loop between the primary drug target and its downstream oncogenic output, coupled with antagonistic crosstalk from a secondary drug target. We demonstrate that this architecture enables bistability, allowing the first drug to reconfigure the network into a suppressed attractor state that is inaccessible through concurrent administration. The treatment schedule determines which of two coexisting stable states the system ultimately occupies, with the gap time between doses defining a critical therapeutic window. Only when the first drug is given sufficient time to displace the system past a threshold does the sequential regimen achieve superior suppression. Our findings establish bistability-enabling network motifs as predictive determinants of sequential drug efficacy and provide a topology-based framework for the rational design of time-dependent combination therapies.