Speaker
Description
Background:
The WHO first-line HIV-1 treatment regimen changed to include dolutegravir in 2019 in response to increasing drug resistance. Drug resistance while on dolutegravir-containing therapy is rare, but has been observed even in previously untreated individuals. Previous work has analysed patterns of resistance in clinical data and postulated that for some drug combinations, resistance emerges in a predictable sequential order.[1] Furthermore, it has been suggested that these patterns may be explained by drug level variability over time resulting from drug pharmacokinetics/pharmacodynamics and imperfect adherence.[1]
Methods:
We have developed a stochastic model of patients on a standard dolutegravir-containing regimen (tenofovir/lamivudine/dolutegravir) with imperfect adherence, based on previous work by Feder and colleagues.[1] As drug concentration (D) changes, the dynamics of subpopulations with resistance to no/one/two/all-three drugs are simulated. Viral fitness (within-host R0) of sensitive virus varies with D in a relationship based on pharmacodynamic properties (e.g. half-maximal inhibitory concentration (IC-50)). Resistant virus R0 is described by an altered-dose response curve incorporating parameters reflecting resistance mutation characteristics (e.g. fold-change in IC-50, fitness cost). The resistance mutation found most commonly at treatment failure conveying at least intermediate resistance with a single-step mutation defines resistance for each drug.
Results:
Initial results suggest 4.7- and 11.9-days following a dose of tenofovir/lamivudine/dolutegravir there is a period where R0 of a resistant subpopulation is higher than sensitive R0 and greater than one (mutation selection window). Furthermore, the long half-life of tenofovir may make it vulnerable to resistance in the context of intermittent adherence.
Conclusions:
We hope our model will help provide a mechanistic understanding of how drug resistance evolves to this key regimen. Understanding how drug resistance is acquired at an individual level is vital to forecast resistance at a population level and ensure long-term sustainability of HIV-1 treatment.
- Feder AF et al. eLife. 2021 Sep 2;10:e69032.
