Modeling the HIV latent reservoir, latency reversal and immunotherapeutics for HIV cure

总结 艾滋病治愈的一个主要障碍是潜伏感染细胞的水库，这些细胞在接受治疗的患者中持续存在 高效抗逆转录病毒治疗（ART）。激活这些潜伏感染的细胞可以导致 在临床试验中，艾滋病毒表现出广泛不同的动态， ART停止后。艾滋病毒在大多数人中迅速反弹，而在少数人中， 在个体中，实现了延长的HIV缓解或治疗后控制（PTC）。尽管 尽管进行了大量的研究，但我们对病毒控制的决定因素缺乏清晰和一致的理解 或ART后HIV缓解的持续时间，这阻碍了有效治疗药物的开发。 实现“功能性”治愈并最终实现灭菌治愈的策略。 这项补助金解决了这一知识差距。我们的中心假设是，PTC不仅仅是由 它是由一个单一的因素;相反，它是一种从复杂的非线性相互作用中出现的现象 在免疫反应和潜在的水库之间，包括复制能力 水库和有缺陷的水库。理解这种动态相互作用将是关键， 制定有效的干预措施，以实现良好的临床结果。我们将首先描述 这些相互作用的作用，通过整合最近的生物 将发现转化为机械数学模型。我们将使用临床数据验证此模型 从后处理控制器和非控制器，将估计的模型参数与 测量的生物学和免疫学标志物，以识别预测 PTC.此外，我们将估计下一代药物的作用方式并量化其疗效。 潜伏期逆转剂（LRA）AZD 5582和一类有前途的基于双特异性抗体的药物组合物。 免疫治疗，双亲和再靶向分子。最后，我们将整合模型 这些代理如何与潜在水库与免疫系统相互作用的模型一起工作， 评价和预测LRA和免疫治疗剂的组合对 储药器和临床结果。 总之，我们的工作将为1）理解艾滋病毒控制和 ART后的反弹动力学，2）识别可能达到PTC的患者，3） 估计/预测治疗干预的影响，如LRA和/或 免疫治疗，以及4）建议有效的干预措施，以实现“功能性”治愈 根据患者的特点。

SUMMARY A major barrier to HIV cure is the reservoir of latently infected cells that persists in patients treated with highly potent antiretroviral treatment (ART). Activation of these latently infected cells can lead to HIV rebound in the absence of ART. In clinical trials, HIV exhibits widely different dynamics after ART cessation. HIV rebounds rapidly in most individuals, whereas in a small fraction of individuals, prolonged HIV remission or post-treatment control (PTC) is achieved. Despite intensive research, we lack a clear and coherent understanding of the determinants of viral control or the duration of HIV remission after ART, which hinders the development of effective therapeutic strategies to achieve a ‘functional’ cure and ultimately a sterilizing cure. This grant addresses this gap in knowledge. Our central hypothesis is that PTC is not solely driven by a single factor; rather, it is a phenomenon emerging from complex nonlinear interactions between the immune response and the latent reservoir, including both the replication competent reservoir and the defective reservoir. Understanding this dynamical interaction will be key to develop effective interventions to achieve favorable clinical outcomes. We will first delineate the roles of these interactions in determining viral control through integration of recent biological findings into a mechanistic mathematical model. We will validate this model using clinical data from post-treatment controllers and non-controllers, correlate estimated model parameters with measured biological and immunological markers to identify patient characteristics that predict PTC. Further, we will estimate the mode of action and quantify the efficacy of a next-generation latency reversing agent (LRA), AZD5582, and a class of promising bispecific antibody-based immunotherapeutics, the Dual-Affinity Re-Targeting molecules. Finally, we will integrate models of how these agents work with a model of the interaction of the latent reservoir with the immune system to evaluate and predict the impact of combinations of LRAs and immunotherapeutics on the reservoir and on clinical outcomes. Altogether, our work will provide a theoretical foundation for 1) understanding HIV control and rebound dynamics after ART, 2) identifying patients who are likely to achieve PTC, 3) estimating/predicting the impact of therapeutic interventions such as LRAs and/or immunotherapeutics, and 4) suggesting effective interventions to achieve a ‘functional’ cure according to patient characteristics.