Modeling Viral and T Lymphocyte Dynamics

摘要 最近的多项研究已经提供了概念证明，即艾滋病毒-1感染的“功能疗法”， 也就是说，在不继续治疗的情况下长期控制艾滋病毒是可以实现的。维斯康蒂研究 确定了14名HIV+患者，他们在初级HIV-1期间接受了抗逆转录病毒治疗(ART) 感染，并将其病毒的后处理控制(PTC)保持在检测到的限度以下 停止治疗后的中位数为89个月。CHAMP(抗逆转录病毒治疗后的艾滋病毒控制 药物暂停)研究已经确定了14个治疗中的67个治疗后控制者 中断研究涉及700多名参与者。 确定为什么有些人在治疗后将艾滋病毒控制在无法检测到或较低的水平 停药，我们需要更好地了解导致病毒感染的因素 水库，这决定了它的大小，它的维持和重新激活的动态可能 导致停药后病毒反弹。在这里，我们建议开发一套新的 帮助理解上述研究中导致功能性治愈的因素的模型 并更全面地了解如何实现功能性治愈。我们会 与领先的实验科学家合作，他们将提供新的数据集，使我们能够 实现以下具体目标。目的1.了解HIV潜伏蓄积的机制 水库急性期播种率的建立及影响因素 感染。建立早期建库机理模型。我们将测试这些 根据协作者收集的丰富数据集建立模型，并估计关键参数值以 准确描述建库动态。有了这些洞察力，我们将 将模型扩展到解释有关播种、周转和遗传组成的最新数据39 蓄水池的。目标2.以定量的方式详细了解决定 抗逆转录病毒治疗中断后的治疗控制持续时间。我们将研究新的模式， 考虑到患者特定的因素，如抗逆转录病毒治疗方案和细胞相关RNA水平 在预测ATI后病毒反弹的时间。当反弹的时间很长时， 我们的目标是阐明新的因素，如依赖于时间的水库复活或免疫率。 导致PTC延长的控制。目标3.利用从数学建模中获得的见解 推动乙肝的治疗议程。我们将利用之前成功的HIV和 建立新一代丙型肝炎病毒感染模型并研究其对病毒感染的影响 不同的治疗方法单独或结合使用。

SUMMARY Multiple recent studies have provided proof-of-concept that a “functional cure” of HIV-1 infection, i.e. long-term control of HIV without continued treatment, is achievable. The VISCONTI study identified 14 HIV+ patients, who received antiretroviral treatment (ART) during primary HIV-1 infection, and maintained post-treatment control (PTC) of their virus below the limit of detection for a median of 89 months after stopping therapy. The CHAMP (Control of HIV after Antiretroviral Medication Pause) study has identified 67 post-treatment controllers from 14 treatment interruption studies involving more than 700 participants. To determine why some individuals control HIV to undetectable or low levels after treatment discontinuation, we need a better understanding of the factors that lead to establishment of viral reservoirs, that determine its size, the dynamics of its maintenance and its reactivation possibly leading to viral rebound after treatment cessation. Here we propose to develop a set of new models to help understand the factors that led to functional cure in the studies mentioned above and to understand more generally how functional cure can be achieved. We will collaborate with leading experimental scientists, who will provide novel datasets allowing us to fulfil the following specific aims. Aim 1. To understand the mechanism of HIV latent reservoir establishment and the factors determining the rate of reservoir seeding during acute infection. We will develop mechanistic models of early reservoir establishment. We will test these models against rich datasets collected by collaborators and estimate key parameter values to accurately describe the dynamics of reservoir establishment. With the insights gained, we will extend the model to interpret recent data39 on the seeding, turnover and the genetic composition of the reservoir. Aim 2. To understand in quantitative detail the factors that determine the duration of post-treatment control after ART interruption. We will study new models that account for patient specific factors such as the ART regime and the level of cell-associated RNA at the time of ATI in predicting time to viral rebound after ATI. When the time to rebound is long, we aim to elucidate new factors such as a time-dependent rate of reservoir reactivation or immune control that lead to prolonged PTC. Aim 3. Using insights gained from mathematical modeling to propel the cure agenda for HBV. We will leverage previous modeling successes of HIV and HCV infection to develop a new generation of models of HBV infection and study the effects of different therapies singly and in combination.