ArticlebioRxiv : the preprint server for biology2026
Stochastic Evolutionary Control in Heterogeneous Populations.
Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Therapeutic resistance, which poses a central challenge in cancer and infectious disease treatment, arises from the evolutionary dynamics of heterogeneous populations as a natural consequence of the evolutionary tendency towards higher fitness. Here we introduce SHEPHERD (Stochastic Heterogeneity-informed Evolutionary Policy Hampering the Expansion of Resistance to Drugs), which integrates Wright-Fisher (WF) population genetics modeling with Markov Decision Processes (MDPs) to design optimal adaptive drug policies which reduce the fitness of evolving disease, mitigating resistance. While MDPs have been applied to evolutionary control under the strong-selection, weak-mutation (SSWM) assumption-where populations are effectively homogeneous-SHEPHERD operates beyond this regime, effectively capturing the full stochastic dynamics of genetically heterogeneous populations experiencing mutation and selection of a wide array of strengths. Using synthetic multi-drug fitness landscapes, we show the benefit of the optimized SHEPHERD protocol for
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