QUANTITATIVE METHOD FOR MODELING HIV INFECTION DYNAMICS

描述（改编自摘要）：互动的动态本质 人类免疫缺陷病毒（HIV）和人体免疫系统之间的关系 是复杂的，仍然知之甚少，尽管最近的重要 关于病毒和T细胞复制和清除动力学的发现 以及识别HIV进入细胞表面的受体。 发展中 准确的描述和更深入的理解之间的相互作用 艾滋病毒和免疫系统在艾滋病毒感染的急性和早期阶段 对于评估新的、有前途的治疗方案至关重要。 数学模型，以确定性或随机性系统的形式 率方程，提供了最自然和方便的框架，正式 描述艾滋病毒和病毒的各个部分之间的相互作用， 人体免疫系统 各种简化的生物模型， 相互作用已经转化为这样的数学模型， 由多个研究小组出版。 这些模型中的大多数都集中在 长期过程的描述，而不是急性/早期阶段 艾滋病毒感染。 没有认真和系统的研究已经取得了 这些模型的数学和概率特性。 通常这些 模型已经拟合了来自少数选择患者的数据，使用统计学方法， 模型和方法，几乎没有认真考虑评估 患者之间的变异性来源。 最后，不小心， 对这些模式进行了全面的比较研究， 他们准确描述系统模式的能力 收集的病毒学和免疫学数据， 临床结果。 本主要研究者建议对以下内容进行系统评估： HIV与人体免疫系统相互作用的数学模型 特别强调这些模型用于描述 艾滋病毒感染的早期和急性阶段。 他和他的同事们将 这些数学模型的公式化以及由此推导出来的 统计模型，其中可观测变量的重要来源 模型变量的类似物是公认的。 他们会发展， 实施正式的统计方法，以使这些模型与来自 急性/早期艾滋病毒感染的临床研究，并从一个基于数据的 模型的比较研究。 通过现有和正在进行的合作 与临床研究人员，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 问题研究

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.