QUANTITATIVE METHODS FOR MODELING HIV INFECTION DYNAMICS

人类免疫缺陷病毒与艾滋病毒/艾滋病之间相互作用的动态性质 病毒（艾滋病毒）和人体免疫系统是复杂的，仍然很差 尽管最近关于动力学的重要发现， 病毒和T细胞的复制和清除以及细胞的鉴定， HIV进入的表面辅助受体。 准确描述和 更深入地了解艾滋病毒和免疫系统之间的相互作用， 在艾滋病毒感染的急性和早期阶段， 评估新的、有前途的治疗方案。 数学模型，以确定性或随机性系统的形式 速率方程，提供了最自然和方便的框架， 正式描述艾滋病毒与不同区室之间的相互作用 人体免疫系统。 各种简化的生物模型， 这些相互作用已经被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 对长期病程而非急性/早期阶段的描述 艾滋病毒感染。 目前还没有一个系统的、严肃的研究。 这些模型的数学和概率特性。 这些模型 通常适用于少数选定患者的数据， 统计模型和方法，几乎没有认真考虑 评估患者之间的变异性来源。 最后， 没有仔细和全面的比较研究这些模式， 尊重他们准确描述系统模式的能力， 纵向收集病毒学和免疫学数据， 随后的临床结果。 我们建议对数学模型进行系统的评估， 艾滋病毒和人类免疫系统之间的相互作用， 强调这些模型用于描述急性和早期 HIV感染的阶段。 我们将完善这些 数学模型，并从中推导出统计模型， 承认模型的可观测类似物的重要变化来源 变量 我们将制定和实施正式的统计方法， 将这些模型与来自急性/早期HIV临床研究的数据进行拟合 感染，并对模型进行基于数据的比较研究。 通过与临床研究人员现有的和正在进行的合作， 将使用模型和方法来解决特定的科学问题 在临床研究中提出的问题。

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 kinetic of viral and T-cell replication and clearance and the identification of cell- surface co-receptors 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 systems 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 have focused on descriptions of the long-term course rather than the acute/early stage of HIV infection. There has been no serious and systematic study of the mathematical and probabilistic properties of these models. These models have typically 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, there has been no careful and comprehensive comparative study of these models with respect ot their ability to accurately describe systematic patterns in longitudinally collected virological and immunological data and to predict subsequent clinical outcomes. We propose 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 stages of HIV infection. We will refine the formulation of these mathematical models and derive from them statistical models that acknowledge important sources of variation in observable analogs of model variables. We will develop and implement formal statistical methods to fit these models to data from clinical studies of acute/early HIV infection and perform a data-based comparative study of the models. Through existing and ongoing collaborations with clinical researchers, er will use the models and methods to address specific scientific questions that are posed in the context of clinical studies.