Modeling Viral and T Lymphocyte Dynamics

描述：直到最近，艾滋病毒的治愈似乎是不可能的。然而，最近的发展表明，一些患者已经治愈或证明治疗后病毒血症控制（PTC）到无法检测的水平，对应于“功能性治愈”。此外，关于如何安全地激活HIV-1潜伏库，有重要的新想法，这被认为是从患者体内根除HIV-1的主要障碍。为了推进治愈的目标，我们需要定量地了解这些最近的临床观察结果。该资助旨在解决这一知识差距，通过利用数学建模的力量来了解PTC的动态和潜在储存库的激活，比较在这些现象中发挥作用的不同生物机制，并提出新的方案来推进艾滋病毒治疗议程。我们还建议使用数学建模来推进另一种慢性感染，丙型肝炎病毒（HCV）的治疗议程。我们的假设是：i）在治疗过程中，潜在储库衰减到足够小水平的患者更有可能 展示PTC，因此我们将开发模型来理解将潜伏期和PTC联系起来的生物学和动态过程; ii）在旨在激活潜伏感染细胞的新治疗方案下分析病毒和感染细胞动力学将导致对hw的新见解，以减少或消除这种储库，因此我们建议通过模拟临床试验数据来发展对这些疗法的定量理解;（三）通过对影响进行建模， 新的有效的直接作用的抗HCV药物，靶向特定的病毒蛋白，并有多种协同作用，我们将能够帮助设计有效的药物组合，是必要的HCV治愈。总而言之，我们的目标是在涉及HIV（以及HCV）的研究中帮助临床合作者，只要我们认为严格的分析可以带来新的见解或改善患者的治疗方法。这些研究也可能提出有趣的理论问题，并推动未来的建模工作。

DESCRIPTION: Until recently a cure for HIV did not seem possible. However, recent developments suggest that some patients have been cured or demonstrate post-treatment control (PTC) of viremia to undetectable levels, corresponding to a "functional cure". Further, there are important new ideas on how to safely activate the HIV-1 latent reservoir, which is believed to be the main obstacle to HIV-1 eradication from a patient. To advance the goal of cure we need to understand these recent clinical observations in quantitative detail. This grant aims to address this gap in knowledge, by leveraging the power of mathematical modeling to understand the dynamics of PTC and activation of the latent reservoir, to compare different biological mechanisms at play in those phenomena and to propose new protocols to advance the HIV cure agenda. We also propose to use mathematical modeling to advance the cure agenda for another chronic infection, hepatitis C virus (HCV). Our hypotheses are: i) that patients whose latent reservoir decays to sufficiently small levels on treatment are more likely to exhibit PTC, and thus we will develop models to understand the biological and dynamic processes that link latency and PTC; ii) that analyzing viral and infected cell kinetics under new therapeutic protocols aiming at activating latently infected cells will lead to new insights into hw to reduce or eliminate this reservoir, and thus we propose to develop a quantitative understanding of these therapies by modeling clinical trial data; iii) that by modeling the effects of new potent direct-acting antivirals for HCV, which target specific viral proteins and have multiple synergistic effects, we will be able to help design the potent drug combinations that are necessary for HCV cure. Altogether, our objectives are to assist clinical collaborators in studies involving HIV (as well as HCV) whenever we feel that rigorous analysis can lead to new insights or to improved treatments for patients. These studies may also raise interesting theoretical questions and drive future modeling efforts.