QUANTITATIVE METHODS FOR MODELING HIV INFECTION DYNAMICS

人类免疫缺陷之间相互作用的动态本质 病毒(HIV)和人类免疫系统是复杂的，仍然很差 尽管最近关于动力学的重要发现被理解 病毒和T细胞的复制和清除以及细胞- HIV进入的表面共受体。开发准确的描述和 更深入地了解艾滋病毒与免疫之间的相互作用 系统在艾滋病毒感染的急性和早期阶段是关键的 对新的、有前景的治疗方案的评估。 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框架 艾滋病毒与不同隔间相互作用的正式描述 人类免疫系统的。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和 由众多研究小组发表。这些模型中的大多数都专注于 关于长期进程的描述，而不是急性/早期阶段的描述 艾滋病毒感染的可能性。目前还没有认真和系统的研究。 这些模型的数学和概率性质。这些型号 通常与来自少数精选患者的数据相吻合 几乎没有认真考虑的统计模型和方法 评估患者之间的变异性来源。最后，已经有了 没有仔细和全面地比较研究这些模型与 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并预测 随后的临床结果。 我们建议对以下数学模型进行系统评估 HIV与人类免疫系统之间的相互作用 强调这些模型在描述急性和早期疾病时的实用性 艾滋病毒感染的各个阶段。我们将完善这些条款的提法 数学模型，并从中推导出统计模型 承认可观察到的模型类比中的重要差异来源 变量。我们将开发和实施正式的统计方法，以 将这些模型与急性/早期HIV临床研究的数据进行匹配 并对这些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，呃 将使用这些模型和方法来解决特定的科学问题 是在临床研究的背景下提出的。

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.