Speaker
Description
Antiviral resistance threatens global health and necessitates innovative approaches for treating infections. One strategy is identifying and targeting viral phenotypes where susceptible viruses exert a dominant effect over their resistant counterparts, mitigating resistance evolution. The candidate poliovirus antiviral pocapavir exhibits this effect in cell culture and mouse models, however, resistance evolved in 43/91 subjects in a human clinical trial setting. Determining the factors that contributed to these differential outcomes will be crucial for adapting these targeting approaches for success in humans. We developed a model of intra-host poliovirus evolution in the presence of pocapavir and found that the conditions under which resistance evolves depend strongly on the spatial and population context of the virus. When the viral MOI is high or if there is a strong spatial constraint on the spread of its progeny between host cells, interference between viruses prevents resistance from evolving. Conversely, if the viral MOI is low and is allowed to mix freely with host cells, viral interference is insufficiently strong to prevent resistance evolution. Because resistance suppression depends on susceptible viruses interfering with resistant ones, pocapavir’s elimination of susceptible viruses ultimately undermines this interference. This leads to the surprising observation that under certain conditions, treating with less drug and treating later in infection can lead to less resistance evolution and better control of the viral population. These results have implications for therapeutic strategies surrounding the dosage and timing of pocapavir for treating poliovirus. More broadly, the model provides a framework for interrogating strategies that exploit microbial interference, and can be used to examine properties of novel therapeutics that may successfully treat infections while also suppressing the evolution of antimicrobial resistance.
