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Updated: Apr 30, 2026

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
Published on: May 9, 2025
Use of agent-based simulations to design and interpret HIV clinical trials
Diego F Cuadros1, Laith J Abu-Raddad2, Susanne F Awad3
1Infectious Disease Epidemiology Group, Weill Cornell Medical College in Qatar, Cornell University, Qatar Foundation, Education City, Doha, Qatar; Department of Healthcare Policy and Research, Weill Cornell Medical College, Cornell University, NY, USA.
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.
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