Use of agent-based simulations to design and interpret HIV clinical trials

Abstract

In this study, we illustrate the utility of an agent-based simulation to inform a trial design and how this supports outcome interpretation of randomized controlled trials (RCTs). We developed agent-based Monte Carlo models to simulate existing landmark HIV RCTs, such as the Partners in Prevention HSV/HIV Transmission Study. We simulated a variation of this study using valacyclovir therapy as the intervention, and we used a male circumcision RCT based on the Rakai Male Circumcision Trial. Our results indicate that a small fraction (20%) of the simulated Partners in Prevention HSV/HIV Transmission Study realizations rejected the null hypothesis, which was no effect from the intervention. Our results also suggest that an RCT designed to evaluate the effectiveness of a more potent drug regimen for HSV-2 suppression (valacyclovir therapy) is more likely to identify the efficacy of the intervention. For the male circumcision RCT simulation, the greater biological effect of the male circumcision yielded a major fraction (81%) of RCT realizations' that rejects the null hypothesis, which was no effect from the intervention. Our study highlights how agent-based simulations synthesize individual variation in the epidemiological context of the RCT. This methodology will be particularly useful for designing RCTs aimed at evaluating combination prevention interventions in community-based RCTs, wherein an intervention׳s effectiveness is challenging to predict.

Keywords: Agent-based simulation; Clinical trial; HIV; HIV treatment and prevention; Mathematical modeling.