Integrated Assessment of HIV-1 Cure Strategies Through Reservoir Burden Reduction and Rebound Risk Modeling in Humanized Mouse Systems

Abstract

The pursuit of an HIV-1 cure requires coordinated evaluation of therapeutic strategies that target viral reservoirs, prevent rebound, and maintain long-term remission. While numerous interventions have demonstrated partial success, quantitative frameworks for comparing their curative potential remain limited. In this study, we established an integrated assessment pipeline to evaluate HIV-1 cure strategies using humanized mouse models. A total of 72 HIV-1–infected NOD/SCID/IL2Rγ-null mice were assigned to four intervention arms: suppressive antiretroviral therapy alone, antiretroviral therapy combined with latency-modulating agents, antiretroviral therapy combined with CRISPR-based proviral targeting, and a multimodal strategy integrating both approaches. Reservoir burden was quantified across lymphoid and non-lymphoid tissues using droplet digital PCR, while viral rebound probability following treatment interruption was estimated through longitudinal plasma viral load monitoring and stochastic modeling. Multimodal intervention resulted in the greatest reduction in total proviral DNA (61% relative to baseline), compared with antiretroviral therapy alone (22%) and dual-therapy arms (34–46%). Rebound modeling indicated a 3.4-fold increase in median time to viral rebound and a 52% reduction in rebound probability over 30 days in the multimodal group. Sensitivity analyses revealed that reservoir size reduction accounted for approximately 68% of rebound delay, whereas intervention durability contributed the remaining variance. These findings demonstrate that integrated quantitative evaluation of reservoir dynamics and rebound risk provides a practical framework for comparing HIV-1 cure strategies and guiding translational prioritization.