QUANTITATIVE METHOD FOR MODELING HIV INFECTION DYNAMICS

描述(改编自摘要)：互动的动态性质 人类免疫缺陷病毒(HIV)和人类免疫系统之间的关系 很复杂，尽管最近很重要，但人们仍然知之甚少 关于病毒和T细胞复制和清除动力学的研究结果 以及识别艾滋病毒进入的细胞表面重组子。发展中 准确描述和更深入地了解 艾滋病毒感染急性期和早期阶段的免疫系统 对于评估新的、有前景的治疗方案至关重要。 确定性或随机性系统形式的数学模型 速率方程，提供了最自然和最方便的形式框架 艾滋病毒与人类免疫缺陷病毒之间相互作用的描述 人类的免疫系统。各种简化的生物模型为这些 相互作用已经被转化为这样的数学模型 由众多研究小组发表。这些模型中的大多数都专注于 对长期进程而不是急性/早期阶段的描述 艾滋病毒感染。还没有认真和系统地研究过 这些模型的数学和概率性质。通常，这些 模型已经与来自少数几个精选患者的数据进行了统计拟合 几乎不重视评估的模型和方法 患者之间的变异性来源。最后，不小心和 对这些模型进行了全面的比较研究 他们准确地描述系统模式的能力 纵向收集的病毒学和免疫学数据并预测 临床结果。 这位首席调查员建议对 艾滋病毒与人体免疫系统相互作用的数学模型 并特别强调了这些模型在描述 艾滋病毒感染的急性和早期阶段。他和他的同事们将改进 建立这些数学模型并从中推导出来的公式 在统计模型中，可观测到的重要变化源 模型变量的相似之处得到认可。他们将发展和发展 实施正式的统计方法以将这些模型与来自 基于数据的急性/早期HIV感染和感染的临床研究 模型的比较研究。通过现有和正在进行的协作 与临床研究人员一起，他们将使用模型和方法来解决 在临床背景下提出的具体科学问题 学习。

DESCRIPTION (adapted from the Abstract): The dynamic nature of interactions between the human immunodeficiency virus (HIV) and the human immune system is complex and remains poorly understood in spite of recent important findings about the kinetics of viral and T-cell replication and clearance and the identification of cell-surface-corecptors for HIV entry. Developing accurate descriptions and a deeper understanding of the interactions between HIV and the immune system during the acute and early stages of HIV infection is critical to the evaluation of new, promising therapeutic regimens. Mathematical models, in the form of system of deterministic or stochastic rate equations, provide the most natural and convenient framework for formal descriptions of interactions between HIV and various compartments of the human immune system. Various simplified biological models for these interactions have been translated into such mathematical models and published by numerous research groups. Most of these models are focused on descriptions of the long-term course rather than the acute/early stage of HIV infection. No serious and systematic study has been made of the mathematical and probabilistic properties of these models. Typically, these models have been fit to data from few, select patients using statistical models, and methods that give virtually no serious attention to assessing sources of variability across patients. Finally, no careful and comprehensive comparative study has been made of these models with respect to their ability to describe accurately systematic patterns in longitudinally-collected virolgical and immunological data and to predict clinical outcomes. This Principal Investigator proposes to perform a systematic assessment of mathematical models for interactions between HIV and the human immune system with a particular emphasis on the utility of these models for describing acute and early stage of HIV infection. He and his colleagues will refine the formulation of these mathematical models and derive from them statistical models in which important sources of variation in observable analogs of model variables are acknowledged. They will develop and implement formal statistical methods to fit these models to data from clinical studies of acute/early HIV infection and perfrom a data-based comparative study of models. Through existing and ongoing collaborations with clinical researchers, they will use the models and methods to address specific scientific questions that are posed in the context of clinical studies.