BACKGROUND: A key research priority for developing an HIV cure strategy is to define the viral dynamics and biomarkers associated with sustained post-treatment control. The ability to predict the likelihood of sustained post-treatment control or non-control could minimize the time off antiretroviral therapy (ART) for those destined to not control and anticipate longer periods off ART for those destined to control. METHODS: Mathematical modeling and machine learning were used to characterize virologic predictors of long-term virologic control using viral kinetics data from several studies in which participants interrupted ART. Predictors of post-ART outcomes were characterized using data accumulated from the time of treatment interruption, replicating real-time data collection in a clinical study, and classifying outcomes as either post-treatment control (plasma viremia ≤400 copies/mL at 2 of 3 time points for ≥24 weeks) or non-control. RESULTS: Potential predictors of virologic control were the time to rebound, the rate of initial rebound, and the peak plasma viremia. We found that people destined to be non-controllers could be identified within 3 weeks of rebound (prediction scores: accuracy, 80%; sensitivity, 82%; specificity, 71%). CONCLUSIONS: Given the widespread use of analytic treatment interruption in cure-related trials, these predictors may be useful to increase the safety of analytic treatment interruption through the early identification of people who are unlikely to become post-treatment controllers.

Analytical antiretroviral treatment interruption (ATI) is an important feature of HIV research, seeking to achieve sustained viral suppression in the absence of antiretroviral therapy (ART) when the goal is to measure effects of novel therapeutic interventions on time to viral load rebound or altered viral setpoint. Trials with ATIs also intend to determine host, virological, and immunological markers that are predictive of sustained viral control off ART. Although ATI is increasingly incorporated into proof-of-concept trials, no consensus has been reached on strategies to maximise its utility and minimise its risks. In addition, differences in ATI trial designs hinder the ability to compare efficacy and safety of interventions across trials. Therefore, we held a meeting of stakeholders from many interest groups, including scientists, clinicians, ethicists, social scientists, regulators, people living with HIV, and advocacy groups, to discuss the main challenges concerning ATI studies and to formulate recommendations with an emphasis on strategies for risk mitigation and monitoring, ART resumption criteria, and ethical considerations. In this Review, we present the major points of discussion and consensus views achieved with the goal of informing the conduct of ATIs to maximise the knowledge gained and minimise the risk to participants in clinical HIV research.